Various forms of biohybrid robots have been developed; however, creating robots with multiple degrees of freedom remains a challenging task. In this paper, we developed a multi-joint biohybrid robot by using skeletal muscle tissue. To achieve this, we first developed a modular bio-actuator actuated by skeletal muscle tissues. The objective of this study was to enhance the contraction force of the actuator and establish optimal experimental conditions for creating high-performance robots. By applying continuous electrical stimulation for five days during culture of bio-actuator, we were able to increase the contraction force by more than threefold. Additionally, we determined the appropriate electric field based on the electrode distance, which enabled us to establish an optimal experimental setup. We also confirmed that connecting the actuators in series can significantly increase the moving distance. Connecting two actuators in series resulted in a total movement distance equivalent to the sum of the distances of each actuator. This finding suggests the potential to create robots with a larger operational workspace. Using these actuators, we first constructed a manipulator with a rotational joint. This research is expected to contribute not only to the development of various robots utilizing bio-actuators but also to advancements in biology technology.

Human-Robot collaboration in surgery represents a significant area of research, driven by the increasing capability of autonomous robotic systems to assist surgeons in complex procedures. This systematic review examines the advancements and persistent challenges in the development of autonomous surgical robotic assistants (ASARs), focusing specifically on scenarios where robots provide meaningful and active support to human surgeons. Adhering to the PRISMA guidelines, a comprehensive literature search was conducted across the IEEE Xplore, Scopus, and Web of Science databases, resulting in the selection of 32 studies for detailed analysis. Two primary collaborative setups were identified: teleoperation-based assistance and direct hands-on interaction. The findings reveal a growing research emphasis on ASARs, with predominant applications currently in endoscope guidance, alongside emerging progress in autonomous tool manipulation. Several key challenges hinder wider adoption, including the alignment of robotic actions with human surgeon preferences, the necessity for procedural awareness within autonomous systems, the establishment of seamless human-robot information exchange, and the complexities of skill acquisition in shared workspaces. This review synthesizes current trends, identifies critical limitations, and outlines future research directions essential to improve the reliability, safety, and effectiveness of human-robot collaboration in surgical environments.

Ambiguity in natural language instructions poses significant risks in safety-critical human-robot interaction, particularly in domains such as surgery. To address this, we propose a framework that uses Large Language Models (LLMs) for ambiguity detection specifically designed for collaborative surgical scenarios. Our method employs an ensemble of LLM evaluators, each configured with distinct prompting techniques to identify linguistic, contextual, procedural, and critical ambiguities. A chain-of-thought evaluator is included to systematically analyze instruction structure for potential issues. Individual evaluator assessments are synthesized through conformal prediction, which yields non-conformity scores based on comparison to a labeled calibration dataset. Evaluating Llama 3.2 11B and Gemma 3 12B, we observed classification accuracy exceeding 60% in differentiating ambiguous from unambiguous surgical instructions. Our approach improves the safety and reliability of human-robot collaboration in surgery by offering a mechanism to identify potentially ambiguous instructions before robot action.

This paper presents the design, development, and preliminary evaluation of a robotic dressing assistance system integrated into a mobile walker, RoboSnail, to support frail elderly individuals during toileting. The system features telescopic linear arms and adaptable roller grippers that automate the lowering and raising of trousers and underwear, addressing challenges in confined restroom environments. The compact design ensures unobstructed user mobility when not in use, while safety and adaptability are prioritized through mechanisms such as adaptable roller grippers and pivoting arms. Preliminary experiments demonstrated reliable trouser-lowering performance with a 95% success rate. Future improvements will focus on enhancing gripper adaptability, expanding stroke length, and conducting user trials to validate the system’s usability and effectiveness. This work represents a step toward autonomous toileting solutions that enhance independence, privacy, and quality of life for older adults with mild mobility impairments.

In the context of medical imaging and machine learning, one of the most pressing challenges is the effective adaptation of pre-trained models to specialized medical contexts. Despite the availability of advanced pre-trained models, their direct application to the highly specialized and diverse field of medical imaging often falls short due to the unique characteristics of medical data. This study provides a comprehensive analysis on the performance of various fine-tuning methods applied to pre-trained models across a spectrum of medical imaging domains, including X-ray, MRI , Histology, Dermoscopy, and Endoscopic surgery. We evaluated eight fine-tuning strategies, including standard techniques such as fine-tuning all layers or fine-tuning only the classifier layers, alongside methods such as gradually unfreezing layers, regularization based fine-tuning and adaptive learning rates. We selected three well-established CNN architectures (ResNet-50, DenseNet-121, and VGG-19) to cover a range of learning and feature extraction scenarios. Although our results indicate that the efficacy of these fine-tuning methods significantly varies depending on both the architecture and the medical imaging type, strategies such as combining Linear Probing with Full Fine-tuning resulted in notable improvements in over 50% of the evaluated cases, demonstrating general effectiveness across medical domains. Moreover, Auto-RGN, which dynamically adjusts learning rates, led to performance enhancements of up to 11% for specific modalities. Additionally, the DenseNet architecture showed more pronounced benefits from alternative fine-tuning approaches compared to traditional full fine-tuning. This work not only provides valuable insights for optimizing pre-trained models in medical image analysis but also suggests the potential for future research into more advanced architectures and fine-tuning methods.

This paper presents the design and development of a single actuator tendon driven two-finger linkage gripper that can perform both strong pinch and adaptable cylindrical grasp. The gripper mechanism consists of an anthropomorphic linkage finger with an additional revolute joint driven by a single actuator and a fixed thumb. The gripper can achieve a maximum pinch force of 11.7 N and an adaptable grasping ranging from 30 mm to 145 mm diameter, making it suitable for various applications, such as pick-and-place tasks in robotics and automation. Moreover, complaint design makes it suitable for the safe physical human robot interaction. In addition, proposed linkage finger’s characteristics were evaluated through kinematic analysis, simulation and experimental tests of prototype. The proposed gripper design is simple, low-cost, and easy to implement, making it an attractive alternative to more complex and expensive gripper designs.

Objective:While neuroscience research has established a link between vision and intention, studies on gaze data features for intention recognition are absent. The majority of existing gaze-based intention recognition approaches are based on deliberate long-term fixation and suffer from insufficient accuracy. In order to address the lack of features and insufficient accuracy in previous studies, the primary objective of this study is to suppress noise from human gaze data and extract useful features for recognizing grasp intention.Methods:We conduct gaze movement evaluation experiments to investigate the characteristics of gaze motion. The target-attracted gaze movement model (TAGMM) is proposed as a quantitative description of gaze movement based on the findings. A Kalman filter (KF) is used to reduce the noise in the gaze data based on TAGMM. We conduct gaze-based natural grasp intention recognition evaluation experiments to collect the subject's gaze data. Four types of features describing gaze point dispersion ($f_{var}$), gaze point movement ($f_{gm}$), head movement ($f_{hm}$), and distance from the gaze points to objects ($f_{d_{j}}$) are then proposed to recognize the subject's grasp intentions. With the proposed features, we perform intention recognition experiments, employing various classifiers, and the results are compared with different methods.Results:The statistical analysis reveals that the proposed features differ significantly across intentions, offering the possibility of employing these features to recognize grasp intentions. We demonstrated the intention recognition performance utilizing the TAGMM and the proposed features in within-subject and cross-subject experiments. The results indicate that the proposed method can recognize the intention with accuracy improvements of 44.26% (within-subject) and 30.67% (cross-subject) over the fixation-based method. The proposed method also consumes less time (34.87 ms) to recognize the intention than the fixation-based method (about 1 s).Conclusion:This work introduces a novel TAGMM for modeling gaze movement and a variety of practical features for recognizing grasp intentions. Experiments confirm the effectiveness of our approach.Significance:The proposed TAGMM is capable of modeling gaze movements and can be utilized to process gaze data, and the proposed features can reveal the user's intentions. These results contribute to the development of gaze-based human-robot interaction.

In this paper, we fabricated a soft sensor based on PEDOT:PSS for thin film structure. The developed soft sensor can measure the contraction force at real time to be embedded in a modular bio-actuator [1]. The modular actuator generated contraction forces at 0.3 mN when applying electric pulse stimulation. To measure millinewton contraction forces and make a built in sensor, we fabricated a soft sensor using PEDOT:PSS-PDMS film. To verify that the sensor can measure the force of the actuator and can be integrated to the actuator, we analyzed characteristic of the sensor. First, we measure Young's modulus of the sensor and compare them with the bio-actuator. From the previous research [2], the Young's modulus of the bio-actuator and sensor were 45.8 kPa and 165 kPa, respectively. In addition, we simulated the sensors to estimate the change of the displacement according to the applied force. Next, we have experiments by stretching sensors using stepping motor to measure the resistance change of the sensor. From the simulation data, the displacement change is 23 µm when applying 0.3 mN of forces and then we detect the displacement change smaller than is 20 µm from the experiments. Finally, we analyzed the movement of the bio-actuator when applying stimulation using high speed camera and time response of the developed sensor. The actuator was contracted to the maximum after 150 ms from the electrical stimulation and the sensor detected the repeated motion at 10 Hz without time delay. As a result, the proposed sensor can measure the force of bioactuator at real time.

The dynamic load attached to the load gravity imposes an excessive burden to human shoulders during load carriage, resulting in possible muscle injuries and additional physical exertion. This paper proposes an active suspension backpack, capable of transferring partial load from human shoulders to pelvis and alleviating the dynamic load through separated panels and motor actuation, to reduce pressure on human shoulders and improve walking metabolic efficiency. Based on the human body motion in the vertical direction, the dynamical model of the human-backpack system with shoulder interaction force measured by a soft ballonet with an embedded air pressure sensor is introduced, and an impedance controller has been implemented to maintain a relatively small and constant pressure on the shoulder. In an experimental case study, we presents preliminary results of three healthy subjects performing a treadmill walking with a 20kg load in ACTIVE configuration where the shoulder pressure shows a decrease by 30% along with a reduction of the metabolic energy consumption by 16.4%, compared with the load LOCKED case.

In-hand pivoting is one of the important manipulation skills that leverage robot grippers' extrinsic dexterity to perform repositioning tasks to compensate for environmental uncertainties and imprecise motion execution. Although many researchers have been trying to solve pivoting problems using mathematical modeling or learning-based approaches, the problems remain as open challenges. On the other hand, humans perform in-hand manipulation with remarkable precision and speed. Hence, the solution could be provided by making full use of this intrinsic human skill through dexterous teleoperation. For dexterous teleoperation to be successful, interfaces that enhance and complement haptic feedback are of great necessity. In this paper, we propose a cutaneous feedback interface that complements the somatosensory information humans rely on when performing dexterous skills. The interface is designed based on five-bar link mechanisms and provides two contact points in the index finger and thumb for cutaneous feedback. By integrating the interface with a commercially available haptic device, the system can display information such as grasping force, shear force, friction, and grasped object's pose. Passive pivoting tasks inside a numerical simulator Isaac Sim is conducted to evaluate the effect of the proposed cutaneous feedback interface.

Microinjection technology is applied widely in biomedical research for the purposes of gene manipulation and microinsemination. Generally, microinjection is performed under an optical microscope environment through image presentation of the targets. To perform the microinjection process, it is necessary to place multiple cells in the same droplet and perform multiple injections. This process requires observation at different magnifications for the injection and embryo transfer processes, with the operator required to change the magnification and light intensity each time. The complexity of the process can lead to variations in the accuracy, reproducibility, and productivity of the course of multiple microinjections. To simplify the microinjection process and reduce the workload on the operator, we propose a micromanipulation system that enables both wide-range and high-resolution video shooting with free viewpoint selection. The effectiveness of the proposed system is verified through microinjection experiments using porcine embryos.

In spite of recent high attention of the biohybrid robot system, the previous researches focused on actuation system depend on simple on/off control without feedback control. To solve this problem, we proposed a soft sensor for feedback control of a bio-actuator driven by skeletal muscle. The proposed soft sensor can measure contraction forces of the proposed bio-actuator [1]. The bio-actuator was constructed with tendon structure and culture template made by polydimethylsiloxane (PDMS). It generated contraction forces at 0.3 mN when applying electrical stimulation. To measure that kind of small amount of contraction forces (0.3 mN), we fabricated a soft sensor using liquid metal, Galinstan, and HTV-2000. At first, we measured the Young’s modulus of the bioactuator and sensor and then fabricated the soft sensor having 68.52 kPa of Young’s modulus that is similar the bioactuator (45.8 kPa). Next, we simulated the sensor to estimate the resistance change according to the applied force. Since the resistance change is too small, we design the circuit to amplify the signal. Then, we detect very small resistance at milli-ohm. In addition, we analyzed time response to detect signal of actuator faster than 200 ms. As a result, the proposed sensor can measure the force of bioactuator without time delay.

Adjustable autonomy is an attractive paradigm to deploy autonomous robots that require occasional interaction with humans or partner robots. In multi-robot applications, autonomy levels such as teleoperation and fully autonomous are extended to team levels, and depending on the task might have complex hierarchical relations.This paper presents a preliminary work on multi-robot coordination strategy based on evaluating the robot’s level of autonomy. With appropriate assumptions, choosing the level of autonomy can be interpreted as a cooperative planning problem. To this end, we propose to encode the robot’s task and motion plans as a Behavior Tree (BT) to monitor the execution and react to external disturbances. Our approach combines an informative path planning with BT synthesis to obtain a plan that allows a robot to explore and act depending on the uncertainty in an environment representation. We demonstrate how a robot can switch between the single and cooperative execution depending on the exploration’s outcome in a navigation among movable objects scenario.

In this paper, we have constructed actively perfusable multiple hepatic lobule-like vascular networks in a 3D cellular structure by using magnetic tweezers. Without well-organized channel networks, cells in a large 3D tissue cannot receive nutrients and oxygen from the channel, and therefore, the cells will be dead after few days. To construct well-organized channel networks, we fabricated a hepatic lobule like vascular networks by using magnetic fields in our previous works. However, the size of the hepatic lobule like vascular network was more than five times larger than real hepatic tissue. To improve the previous research, we have proposed several things. First, we have constructed the vascular network having similar size of the real thing in this step. Second, we have cultured the constructed structure for a long-time (more than two weeks) to verify the biocompatible condition. Third, we assemble the constructed hepatic tissues to make a large size of organ, liver. Finally, an actively perfusable system have been adopted to implement a bioreactor system by adding micro pump.

In recent years, vision-based analysis systems of micro-objects in a microchannel have been actively developed. However, it is difficult to focus on high-speed micro-objects in a microchannel because the general height of a microchannel is approximately 10-100 μm, whereas the depth of focus of the objective lens is approximately 1-4 μm. Therefore, we propose a high-speed well-focused image-capturing microscope, which is a system with an objective lens attached to a vibration machine that moves the focus position rapidly by oscillating it up and down to capture well-focused images using a histogram-based algorithm. The proposed microscope system is verified experimentally to capture well-focused images of moving micro- objects.

Using a rehabilitation robot to activate motion intention and reflex response simultaneously is an effective approach to aiding recovery from paralysis caused by neurological disorders. Mechanical motions supported by conventional robots are, however, not enough to activate reflex. In this paper, we propose a grasp-training robot that can stimulate the grasp reflex of a paralyzed hand by pushing the hand onto an elastic bar while supporting the grasping movements. In addition to this feature, we discuss the robot design in relation to its usability and wearability for ease of use in clinical practice. Experimental results obtained from healthy subjects show that the proposed robot can support grasping in a way similar to the traditional range-of-motion exercise used by therapists for grasp rehabilitation. Combining this appropriate grasping-motion support and the mechanism for pushing the hand onto an elastic bar succeeds in activating the grasp reflex of a completely paralyzed patient in a clinical test that involves monitoring electromyography signals from the paralyzed hand.

This study presents the high-precision microinjection of fluorescent micro-gel beads into Caenorhabditis elegans trapped in a suction microchannel. In our previous works, we demonstrated survival microinjection by a conventional micromanipulation technique. However, the focal planes differed between the tip of the microinjection tool and the target axon inside the C. elegans body. To resolve this problem, we here propose a suction microchannel that traps C. elegans during the microinjection operation. The focal plane of the target nerve axon matches that of the fluorescent microbead in the microinjection tool, enabling high-precision microinjection into the interior of the C. elegans body under a microscopic view. In an experimental evaluation, the positioning accuracy of the injection into C. elegans was within the target accuracy (15 μm). The head-flrst navigation alignment of C. elegans along the microchannel was controlled by electrotaxis. Injection of the fluorescent micro-gel bead into the C. elegans body was quantitatively confirmed by confocal microscopy.

In this paper, we introduce a walking load control strategy with a cane-type robot for gait training. The population of elderly people is increasing in most of the developed countries, and there is a growing demand for caregivers. Assistive robots are expected as a solution to provide aid in order to reduce the burden of caregivers in gait training of elderly people. Our research group has been developing a series of cane-type walking assistive robots named Intelligent Cane on admittance control to provide safe and efficient gait training. We propose an adaptive design method of the admittance control model in order to control user's walking load for the purpose of rapid improvement of user's physical strength. In the proposed method, the cane robot automatically adjusts control parameters of an admittance control model based on a correlation between a set of admittance parameters and a user's walking energy consumption. We conducted experiments to evaluate the proposed adaptive control strategy through a convergence error between estimated walking load and target one while walking training. We confirm the advantage of using the cane robot in rehabilitation.

In this research, we fabricated movable toroidal cell structures inside a microfluidic device for tissue engineering applications. A photo-crosslinkable biodegradable hydrogel gelatin methacrylate (GelMA) was employed to encapsulate biological cells for assembling cell structures. The UV light power and the concentration GelMA hydrogel were optimized to achieve both fabrication of microstructures and live condition of cells. The two-layered toroidal cell structures were fabricated which can mimic the multi-layered structure of blood vessels. The movable microstructures were achieved by the water repellent coating on the substrate surface. Finally, on-chip fabrication of GelMA microstructures and peeling off of the fabricated microstructures were achieved using a microfluidic chip. The results indicate that the fabricated movable GelMA microstructures can be used for further three dimensional assembly to achieve vascular-like tube structures.

Conventional humanoids have achieved walking and running by independent controllers, even though a transition between these independent motions should be added to connect them while ensuring stability. In contrast, human selects walking/running at low/high speed in terms of energy efficiency, and transits between them naturally. This fact implies that human gait shares the inherent controller among walking and running despite their quite different appearances. Hence, we propose a “unified bipedal gait,” which includes walking, running, and the transition. The unified bipedal gait has the inherent controller: passive dynamic autonomous control (PDAC) with a damping and spring loaded inverted pendulum (D-SLIP) model. The PDAC constrains the humanoid natural dynamics by a virtual holonomic constraint (VHC) that degenerates the natural manifold of the states for stabilization. Compliance in the D-SLIP is capable to yield the required characteristics of walking/running: low/high compliant legs for walking/running. Thus, a novel VHC is designed to extract the required characteristics of walking/running from the D-SLIP dynamics and form the proper manifold. As a result, we achieved the unified bipedal gait that bifurcates to walking and running via the natural transition. The high energy efficiency was confirmed in this unified bipedal gait at any gait speed.

This paper presents a novel In situ nanomanipulation integrated with scanning electron microscope- computed tomography (SEM-CT) imaging system for 3D nanomanipulation. In our previous works, a nanorobotic manipulation system was established inside an environmental-SEM (E-SEM) for water-contained samples, including biological organism, based on a real-time high resolution SEM observation. However, the SEM image is limited in two dimensional (2D) and surficial information from the signals of secondly electrons. For nanosurgery applications, such as nanoinjection, it is needed to evaluate the sample in 3D space with its internal information after manipulation. The SEM-CT imaging system is developed for In situ nanomanipulation based on SEM observation. The CT is an effective method to obtain the internal 3D information as a non-destructive manner. The imaging resolution of our SEM-CT system is in less than 400 nm. A Caenorhabditis elegans (C. elegans) was used as a target of biological sample. To improve the contrast of SEM-CT imaging of C. elegans, the X-ray was tested by generating using brass and copper materials. Finally, the nanoinjection was demonstrated with SEM-CT imaging system to C. elegans using the nanoinjector which was fabricated by focused ion beam (FIB) process.

This paper proposes a quasi-passive dynamic autonomous control (Q-PDAC) for a three-dimensional (3-D) bipedal gait of humanoid robots from start points to goal points. The major approach for 3-D traveling is currently footstep planning by a constantly stable gait with an emphasis on its accurate and secure traveling. However, energy would potentially be wasted when the robot accurately travels according to the planned footsteps. In contrast, a limit-cycle-based gait possesses the good efficiency by a gait speed control, although the accurate and secure traveling is difficult for it. Its gait speed control is unfortunately not enough to freely travel on 3-D spaces: shortages of a turning speed control, trackability of horizontal speed, and stability of the bipedal gait. Hence, the Q-PDAC supplies three proper angular momenta by hip and ankle joints to achieve the turning motion and enhance the trackability of horizontal motion. Three angular momenta are simply designed consistent in the PDAC dynamics, and achieved the sufficient gait speed control for 3-D traveling. As a result, the robot can efficiently travel from the start point to the goal point while following a leader point not to collide with walls.

In this paper, we propose a new method to assemble microstructures with biological cells towards in vitro 3D cellular structures. The proposed assembly method uses self-assembly process of magnetized toroidal microstructures. Biocompatible toroidal hydrogel microstructures are prepared by electrodeposition method, and ferrite particles are put on the fabricated structures using poly-L-lysine (PLL). The microstructures are magnetized by the magnetic field at 3 T, and assembled by the magnetic self-assembly process. Biological cells were encapsulated in the microstructures and cultured to achieve high density of cells inside structures. The magnetized microstructures were assembled automatically. The magnetic force generated from the ferrite embedded microstructures was estimated and compared to the fluid resistance applied to the microstructures. The proposed method can be applied to achieve 3D in vitro cell structures with vascular networks for tissue engineering applications.

This paper proposes a new thin fixture that improves comfortableness and makes it easy for a user to wear a grasping support exoskeleton. Easiness of wear is one of important factors for the system performance improvement in addition to physical support functions of the system. The fixture consists of a C-shaped SMA wire and an air chamber. The SMA wire generates a holding force to fix the exoskeleton to a user's finger. The air chamber deforms the SMA wire to open its ends for attachment and detachment. This fixture reduces wearer's burden due to a lightweight, about 1[g], and no hindrance of a finger motion due to thin profile, 2[mm]. The fixture is evaluated through some experiments from the viewpoint of holding force, contact pressure, finger skin temperature, attaching time and detaching time. This fixture can maintain blood flow by changing the holding force that depends on pressure of compressed air. Time spent for donning and doffing a grasping force support system becomes 80 or more percent shorter than one of Velcro.

This paper describes a magnetic resonance imaging (MRI) compatibility assessment of our lower-extremity motion simulator called LoMS which provides gait-like motion for a wearer within his/her lying posture during functional MRI (fMRI) imaging. We confirmed that the existence and the movement of LoMS do not decrease the fMRI image quality when the distance between LoMS and the head coil of MRI is practical distance (more than 400 mm). We also confirmed that LoMS can operate properly in MRI environment, which is to measure own joint angle avoiding the noise from fMRI imaging. Then we show that the brain activity related to gait motion can be imaged during gait-like motion.

Walking capability composed of stability and efficiency is one of the most important issues in the field of humanoid robots. An effective swing of the arms is expected to enhance the walking capability under the constraints from the limited body. We propose an arm-swing method to enhance the stability and efficiency by selecting optimal arm-swing strategy depending on the walking conditions. In this research, we select the optimal strategy between the support of the center of gravity (COG) tracking for stability and the walk without arm-swing for efficiency. To support the COG tracking, we employ a predictive control. States are defined as an inverted pendulum model and inputs are given as an inertial force of arm-swing. Input and output weights in the predictive control are adjustable by a support weight introduced in this paper. Selection of the optimal support weight by a selection algorithm for locomotion (Su-SAL) switches the two strategies by adjusting the ratio of input and output (I/O) weights. Su-SAL maximizes the efficiency while keeping the stability in comparison with the case of the constant support weight.

Fall prevention is one of the most important functions of walking assistance devices for user's safety. It is preferable that these devices obviates factors which induce falling over rather than helping them recovering from falling motion. Tandem stance, where both legs form a line along walking direction, is a factor of falling. It is often observed in turning motion because a swing leg moves in lateral direction as well as forward. Generally, upper body's turning of a person proceeds before lower limb's turning during walking, and the behavior of the lower limb is constrained by upper body turning. It is thus possible to control behavior of the lower limb for tandem stance prevention by constraining behavior of the upper body. This paper therefore introduces a tandem stance prevention method for safer walk of the elderly or physically challenged person. The method adjusts admittance of cane robot's turning motion according to the positions of a support leg and a swing leg. The cane robot measures user's leg position and estimates a walk phase of the user. By adjusting an admittance model of the cane robot based on the walk phase, the cane robot resists to turn while support leg is on the same side of the turning direction. As a result, the tandem stance is avoided. Through experiments, we confirmed that the cane robot successfully controls user's upper body's behavior to prevent the user from being in tandem stance.

In this paper, we conducted a new method to assemble microstructures inside a droplet named “Lab in a Droplet (LiD)”. The method can realize the assembly of micro-nano structures inside a droplet size. The surface tension is used to assemble microstructures automatically. Micro-scale or nano-scale objects are ejected from an inkjet nozzle. They are gathered at the center of the droplet and assembled by the surface tension. We conducted preliminary experiments to check whether the self-assembly of microstructures can be achieved by LiD. The experimental results show that the self-assembly of microbeads is conducted inside a droplet. The nano-scale objects can be patterned on a substrate depend on their sizes. A microstructure made of photo-crosslinkable resin was prepared, and microbeads were assembled with the microstructure inside a droplet. The method can be used for autonomous assembly of micro-nano structures in high precision.

This paper presents a fabrication method of multi-graphene box structure by a nanomanipulation in a Field Emission Scanning Electron Microscope (FESEM). To bend the multi-graphene in plastic deformation region, the bending stress were measured using a silicon cantilever based on the nanomanipulation. In this study, defects were introduced inside the multi-graphene on the folding line of the multi-graphene by irradiating an electron beam assisted with oxygen gas. From experimental bending stress measurement, the bending stress was dropped with electron beam irradiation in oxygen gas environment. The fabrication of 3D box structure of multi-graphene was demonstrated from a cubic net of multi-graphene which was fabricated by a Focused Ion Beam (FIB) etching process. For bending the one side of the cubic net graphene, a tungsten probe was used after reforming by FIB etching as end-effector of nanomanipulator. The multi graphene was bent to form a box structure in 3D space.

In this study, we describe a novel method of fabricating shape-controlled calcium alginate gel microcapsules. Alginate-poly-L-lysine (PLL) hydrogel microcapsules with predefined shapes were constructed based on electrodeposition method. Firstly, electrolysis of water in alginate solutions with calcium carbonate particles induced alginate gelation on micro-patterned electrode to form 2D gel structures. Then, these structures will be detached from the electrode surface and treated with the alginate-PLL microcapsules system. By passive control based on the micro-pattern geometric confinement and electrodeposition parameters, we succeeded in producing calcium alginate-PLL microcapsules with diverse shapes (such as sphere rod and cubic). The shape and size of the calcium alginate microcapsules could be tuned by adjusting the geometric design of micro-pattern on electrode and the apply voltage of electrodepostion. The preparation conditions of size- and shape-controlled calcium alginate-PLL microcapsules and influence factors were studied. This proposed method can lead to more accurate and creative studies of fabricating biocompatibility scaffold for tissue engineering.

This paper proposes a finger-mounted walk controller for a complete paraplegic patient wearing a powered exoskeleton. The wearable controller mounted on both hands of the patient compensates impaired efferent and afferent nerves of the patient through healthy index fingers. The user controls his hip joint angle through force sensors of the controller as if he controls a position of his swing leg voluntarily. Simultaneously, he perceives hip joint angles through an electric stimulation device of the controller. This paper introduces a walking robot which simulates the patient body with lofstrand crutches on his arms for preliminary experiments before a clinical trial. The finger-mounted walk controller is used to control a position of the robot's swing leg. A 5-meter walk experiment is conducted to evaluate feasibility of the controller. We confirmed that the user controlled a stride based only on the electric stimulation feedback and no visual feedback, and that the robot finished walking 5-meter in three minutes.

In this study, cell-laden alginate-poly-L-lysine (PLL) hydrogel structures with arbitrary shapes were constructed based on electrodeposition method. Electrolysis of water in alginate solutions with calcium carbonate particles induced alginate gelation on micro-patterned anode electrode, and cell-laden alginate gel structures were formed. The several different shapes of gel were generated at one time by predefined micro-patterns. The micro-patterned electrode was fabricated by coating photoresist on Fluorine-doped tin oxide (FTO) glass slide. Alginate-PLL encapsulation technique was introduced to this platform forming alginate-PLL hydrogel structures. This proposed method can lead to more accurate and creative studies of fabricating cell-laden scaffold for tissue engineering.

This study presents the survival microinjection into Caenorhabditis elegans (C. elegans) with in vivo observation based on micromanipulation. The microinjections were achieved with micro-gel beads which are enable to encapsulate chemicals for injection. In this study, a fluorescent material was used to evaluate the injection positional precision inside the C. elegans. The fluorescent microbead was picked up at the tip of a micropipette injection tool and injected by a piezo actuated microinjector. The distance between the injected micro-gel bead and closest nerve axon was measured as 20.3 μm and 16.5 μm by in vivo observation of a confocal microscopy. The two types of pipette tools were used to evaluate the success and survival rates of microinjection, and the smaller pipette (pipette A, 0.8 μm in diameter) showed higher rates as 50 % and 67 % respectively.

A cane-type robot called intelligent cane has been developed to support the elderly during walking. By supporting a part of a user's body weight, the cane robot aims to reduce a load applied to a user's affected leg. Therefore, while the user's affected leg is a support leg, it is preferable that the cane robot stops to sufficiently support the user. In our previous work, the cane robot is controlled based on horizontal component of force applied to the cane robot and moment around a vertical axis. In this paper, virtual friction force, which is proportional to vertical component of force, is proposed to improve a walking assistance capability of the cane robot. In addition, virtual frictional coefficients are arranged based on the user's state inferred by a laser range finder. By employing the proposed method, the cane robot moves easily in the both legs support phase, stops in the healthy leg support phase, and supports the user reliably in the affected leg support phase.

This paper proposes a pneumatic tubular body fixture for a wearable assistive device in order to hold a user body in simple wearing actions and with comfort. The pneumatic body fixture, called active cuff, is composed of multiple sets of a pneumatic actuator module which are actively transformed by compressed air. This transformed module wraps and holds a part of a user's body so that a wearable assistive device can be mounted on the user's body with less effort in a short time. The elastic material of the pneumatic actuator module also contributes a tactile and pressure sensation of a contact with the environment as if we could feel those sensations through our clothes. The pneumatic actuator is modeled by a beam structure and then deformation of the pneumatic actuator is simulated by finite element method for an active cuff design. The maximum holding force of the developed active cuff is about 6 kilograms, which is enough to hold an upper limb. The active cuff changes the holding points to keep blood flow of the holding area iteratively and alternatively using three couples of pneumatic actuator modules of the active cuff. Through some experiments, we confirmed that the active cuff enhanced the convenience and comfort of the wearable robot from the viewpoints of easiness to wear and the contact pressure distribution.

In this paper, we achieved three dimensional (3D) assemblies of multi-cell spheroids towards 3D in vitro cell structures. The 3D assembly of cells in vitro is one of the important techniques to reveal cell growth, differentiation and hystogenesis. The techniques can be used for applications in tissue engineering, drug screening, and cell characterization. The multi-cell spheroids were used as building blocks for 3D structure, and thermoresponsive gel was used for spheroids assembly. The mouse myoblast cells C2C12 and mouse fibroblast cells NIH 3T3 were cultured in an ultra-low atachment surface flask. The cells were naturally aggregated in the flask and cell spheroids were prepared in self-assembly process. The rat liver cell RLC-18 was also cultured to prepare spheroids. The thermoresponsive Gel probe (GeT probe) we proposed was employed for assembly of the prepared spheroids in 3D. The handled spheroids by GeT probe were cultured inside the thermoresponsive gel and the cell viability was confirmed. The cultured structure was handled by the GeT probe for further assembly. The results validate that the GeT probe can manipulate spheroids with keeping live condition of cells and achieve 3D cell assembly inside the thermoresponsive gel with arbitrary and precise patterning.

This paper introduces superiority of pinching force accuracy and band when our developed pinching force support system augments a human's pinching force, allowing direct contact of human fingers and fixing distribution ratio of the supporting force. A user with our exoskeleton support system adjusts his/her pinching force according to a task based on his/her sensory feedback information that is made available by a direct contact with a pinching object. In addition to the direct contact, the exoskeleton pushes a user's finger with a constant rate of supporting force for reduction of the affecting force on the human finger, and then the rest of the supporting force directly acts on the pinching object. In contrast, most of conventional gripping assistive robots interfere with haptic sense of a user finger and with stable and dexterous manipulation based on the tactile sense because they covers a user's fingers with their exoskeleton. Through some experiments, this paper reports that our exoskeleton achieves high precision and wide band of the pinching force, comparing with the human performance and with performance of different structure of the exoskeletons.

This paper introduces a method to improve the performance of a Bioelectrical Potential (BEP) based Human-computer interface. The BEP interface used was design to be used by physically challenged patients that remain with the ability to dexterously control a set of superficial muscles. The proposed method uses the BEP signal coming from superficial muscles as a force actuating over a simulated inertia on a cursor type interface. Also a simulated friction is implemented to improve stability of the movement of the cursor, and improve the naturalness of the feeling when using. The performance of the method is measured via an extension to 2D of the Fitts' law model and compared with 2 previously presented methods and improvement is shown.

This paper proposes a novel human-computer interface system, with architecture flexible enough to adapt to various types of physical disabilities and able-bodied person, and also capable of connecting to various devices via a wireless protocol, using a tablet PC as a central system with which a user are interacting. For this interface system surface Electromyogram (EMG) of various muscles which a user still has control, are used as input signals for controlling a tablet. The aim of this system is to extract additional intention of user while user doing deskwork. The characteristic EMG patterns, which are observed when agonistic and antagonistic muscles contract together, are utilized for extracting operational intention. Since these patterns are rarely observed while user doing deskwork or other actions of daily life, this methodology can discriminate the derivation of EMG whether intentional or not. Then the operability of interface system are evaluated by Fitts' law based test GUI. The experimental results show the validity of our proposed interface system comparering with other alternative interface systems.

This paper introduces contribution of the thumb sensation to precisions of human's pinching force control when the human cooperatively pinch an object with the exoskeleton, which augments human pinching force based on a surface electromyography. A human hand should contact with a grasping object directly, while the exoskeleton pushes the human hand for grasping support, because tactile feedback from the hand is very important for human to handle an object stably and dexterously. However the exoskeleton may crush the human fingers with excessive force. The exoskeleton distributes the assistive force to the pinching object in two routes: directly and through a human finger. In our previous study, the accuracy of the pinching force is improved when the distribution factor of the index finger assistance keeps constant. This paper reports improvement of the pinching force when the fixed ratio of the pinching force assistance is applied to the index finger and thumb. In addition, we reveal the contribution of the thumb sensation.

This paper describes a novel motion simulator for the lower extremities of human in a magnetic resonance imaging (MRI) environment. This motion simulator provides a wearer with physical supports to move their lower extremities or physical constrains as well as floor reactive force on bottoms of their feet during gait-like motion in an MRI room so that brain activities could be simultaneously measured. An MRI is one of the most powerful tools to measure activities in any part of brain but a device attached on a subject is limited because the material used for the device should be nonmagnetic. This paper shows the compatibility of the motion simulator that consists of Mckibben-type pneumatic artificial muscles and nonmagnetic materials. Also this paper shows the performance of the floor-reactive-force generator mounted on the soles of the motion simulator.

This paper deals with a method of locomotion selection based on Falling Risk and moving efficiency. The robot estimates information from sensors by solving state equation. The robot evaluates the Falling Risk as an indicator of uncertainty. Falling Risk is derived from measured information by using Bayesian Network. Locomotion selection during walking is modeled as a Semi-Markov Decision Process and the most appropriate locomotion is selected by using the greedy algorithm. As a result, the robot can move in the environment that is difficult to travel by single locomotion mode, maintaining the maximum moving efficiency.

For multi-contact robot motion, a closed chain is formed by robot links and the environment. This paper proposes a new methodology named “key joint method” for reducing the energy cost by adjusting an internal stress inside a closed chain. Firstly, we analyze the internal stress theoretically taking the degrees of freedom (DOF) and the number of position actuated joints into consideration, then a practical key joint method is proposed by changing a suitable redundant position controlled joint to be force control. After that, a parametric family is introduced for representing various of possible motions subjected to the robot dynamics and other constraints. Finally, a general optimization method is proposed for planning an energetically efficient multi-contact robot motion taking the motion trajectories and internal stress into consideration. As an example, the pace gait ladder decent motion is taken to explain the principle and realization of the proposed method. As experimental evaluation shows, the key joint method is effective for reducing the energy cost in the multi-contact motion.

This paper investigates force accuracy of a human finger in three types of support conditions of an exoskeleton. The exoskeleton augments pinching force of a wearer's index finger in proportion to it based on surface electromyography. Three supporting manners of the pinching force are evaluated by switching a fingertip part of the exoskeleton. One is that the assistive force is applied to the wearer's finger so that the force could be sensible by the wearer. Another case is that the assistive force is directly delivered to a grasping object without a wearer's fingertip. The other is that a part of the force directly affects the object and the rest affects the wearer's finger. Through pilot experiments, transitions of the accuracy through training in these cases are compared each other.

This paper proposes an active air mat that improves comfortableness and easiness to wear an exoskeleton on a forearm. They are ones of important factors for the system performance evaluation in addition to physical support functions of the system. The active air mat which is installed in interface parts of the exoskeleton enables a wearer to attach and release the exoskeleton in an easy way and a short time by quickly inflating the air chambers to hold a human arm or deflating them to release. The air mat adaptively fills a gap between a human arm of various sizes and an exoskeleton. In addition, the air mat minimizes constriction of blood flow by changing contacting areas with a human arm from the periphery to the trunk. The exhaust air from the deflating air chamber is used to ventilate around skin surface so that humidity of the skin could keep low by the ventilation. The active air mat is evaluated through some experiments from the viewpoint of pressure distribution, blood flow, wearing time, releasing time, body-holding rigidity, and temperature and humidity of a human skin in resting and working states.

Biped walking improves the circulation of blood as well as bone density of the lower limbs, thereby enhancing the quality of life (QOL). It is significant not only to healthy people but also to physically challenged persons such as complete spinal cord injury (SCI) patients. The purpose of this paper is to propose an estimation algorithm that infers the intention related to the forward leg-swing in order to support the gait for complete SCI patients wearing an exoskeleton system called a Hybrid Assistive Limb (HAL), and to verify the effectiveness of the proposed algorithm through a clinical trial. The proposed algorithm infers the patient's intention in synchronization with the deviation of the center of the ground reaction force (CoGRF) that is observed immediately before a person starts walking. The patient conveys this intention by inducing the deviation of the CoGRF, using crutches or handrails with both of his/her arms. In the clinical trial, we confirmed that the algorithm inferred the patient's intention to swing the leg forward, and achieved a smooth gait in synchronization with it. As a result, the gait speed and cadence of the SCI patient with HAL during the 10-meter walking test increased to 6.67 [m/min] and 20 [steps/min], respectively after several trials.

This paper describes a 3-D biped walking over rough terrain. The robot is modeled as the special 3-D inverted pendulum that can change the length. The dynamics of the 3-D inverted pendulum is modeled as 2-D autonomous system by applying the Passive Dynamic Autonomous Control (PDAC) that is based on the assumption of point-contact of the robot foot and the virtual holonomic constraint as to robot joints. We analyze the stability of the 2-D autonomous system by use of Poincarée map, and derive the stable range over rough terrain. By applying the virtual compliance control to an actual robot “Gorilla Robot III”, the angle of the pendulum is modified. Finally, the 3-D biped walking over rough terrain is realized by use of the Gorilla Robot III.

This paper reports support effects of an exoskeleton system for activities of a hand and an upper limb of a healthy person. The support system augments human forces of a hand, a wrist joint and an elbow joint based on bioelectric potential of each muscle so that the upper limb could be assisted by the exoskeleton with a certain rate of wearer's force. Actuators in the assistive system are replaced with powerful ones to supports human hand, wrist and elbow activities with larger force and torque. Through experiments it was confirmed that a wearer receives physical support from the system for activities of a hand, a wrist and an elbow joint and then we evaluate rate of assistance by comparing the magnitude of the bioelectric potential between under a supported phase and under an unsupported phase.

This paper proposes the basic technologies in order to develop a wearable hand assistive system for daily life support. Current prosthetics have some problems for wearability. We focus on the load caused by weight of wearable system. The actuator is one of the heaviest parts in wearable systems. Therefore we propose to use the McKibben pneumatic artificial muscle which is lightweight and compact in size. At first, we propose a new method to control air pressure of artificial muscle without pressure sensor in order to reduce the size of system. Second, we investigate variable stiffness of human finger to perform human finger dexterity and simulate it by using our proposed polyarticular tendon drive system.

This paper describes walk-to-brachiate transfer of a multi-locomotion robot (MLR). The MLR has multiple types of locomotion such as biped walking, quadruped walking and brachiation. This transfer is carried out through vertical ladder climbing as the robot must raise its body to start brachiating. As a result we have designed two stable transfer motions from walk to climb and from climb to brachiate, while contact situations and constraints of the robot are changing during the transfers. In addition, we have proposed a control algorithm by considering the reaction force from environment, and the setting of parameter is based on a kinetic model of the robot in order to tolerate relative position errors between the robot and its environments such as rungs of the ladder. The robustness of the designed motions with error corrections is experimentally verified.

The applicative field of activities of robots which have only one locomotion strategy is limited. As a mean of enhancing the mobile range, it is necessary to have various locomotion modes. Therefore, we focus on dynamic transitions between several kinds of locomotion modes adapting to environmental changes. In this paper, we aim to realize a stable locomotion along some unknown test courses with transition between biped and quadruped walks. To achive this transition, we propose a method to get environmental information and internal conditions. Robot plans locomotion based on recognition of test courses and estimate stability of walking using Bayesian Network. The effectiveness of proposed method is verified by experiments.

This paper proposes a three-dimensional biped dynamic walking algorithm based on passive dynamic autonomous control (PDAC) which is previously proposed. The robot dynamics is modeled as an autonomous system of a three-dimensional inverted pendulum by applying the PDAC concept that is based on the assumption of point contact of the robot foot and the virtual constraint as to robot joints. Due to autonomy, there are two conservative quantities named ldquoPDAC constantrdquo, that determine the velocity and direction of the biped walking. We also propose the convergence algorithm to make PDAC constant converge to arbitrary value, so that walking velocity and direction is controllable. Numerical simulation results validate proposed algorithm.

This paper addresses a three-dimensional biped dynamic walking control based on Passive Dynamic Autonomous Control (PDAC). In our previous work, the robot dynamics is modeled as a two-dimensional autonomous system of a three-dimensional inverted pendulum by applying the PDAC concept. In addition, the convergence algorithm based on conservative quantities named ¿PDAC constant¿ was proposed, so that walking velocity and direction is controllable. In this paper, we apply our control framework to an experimental robot ¿Multi-locomotion Robot¿; then the performance and the efficiency of the proposed control algorithm are verified by experiments.

This paper introduces a cooperative control algorithm that designs a stable biped walk satisfying a wearer's intention relating to his/her walk such as a timings to start and stop walking, walking speed and waking direction. Using this algorithm an exoskeletal walking support system could help a paraplegia patient walking comfortablly. At first, a pair of gloves with several DOFs is developed to convey a wearer's intention to the walking support system. He/she swings both his/her index fingers as to simulate foot motions of his/her walking. The amplitude and period of the swing corresponds to a step length and period of the walk, respectively. Pronation/supination of the wrist joint of his/her right arm corresponds to a walk direction. The cooperative control algorithm based on a cart-table model designs trajectories of each joint for stable walking pattern that satisfies the intention expressed by the wearer's hand motion and then the designed walking pattern is executed in realtime by the walking support system. As the first trial, a small humanoid robot ¿HRP-2m¿ is used for safety as a control target that will be a combination of a wearer and the walking support system in the final situation. Through some experiments we confirm that our proposed algorithm enables the humanoid robot to start and stop stable walk with variable step length in the desired walking direction according to operator's intentions.

This paper introduces an exoskeleton assistive hand that supports human hand and wrist activities by using user’s bioelectric potential to control the exoskeleton movement. The exoskeleton has three active joints for an index finger, three active joints for combination of a middle finger, a ring finger and a little finger and two active joints for a thumb. It also has two passive joints between the index finger part and the combined part of the three fingers. Our proposed poly-articular tendon drive mechanism simulates a mechanical compliance of a human finger so that the exoskeleton could realize comfortable and stable grasping. This paper proposes a new mechanism “dual sensing system” and a new control algorithm “bioelectric potential-based switching control” so that the exoskeleton could synchronize wearer’s hand activities without any force sensor. A tendon-driven mechanism and a dual sensing system enable wearer’s fingers to move freely when they does need power assist but precise position control or force control. A bioelectric potential-based switching control enables the exoskeleton to augment their grasping force only when wearer’s fingers generate a relatively large grasping force. A five-parallel-link mechanism is used to assist wrist activities of a wearer. Through experiments it is confirmed that the exoskeleton does not disturb a wear’s pinch of a small object and that it augments grasping force for a heavy work.

An animal has a characteristic ratio of forefoot and rear legs so that its morphology can adapt to the living environment. Likewise, the structure of robot should be better fitted the locomotion in the working environment. This paper derives an optimal structure of the quadruped robot, which minimizes the sum of joint torques of the robot. Minimization of the joint torque allows to reduce the joint acceleration in walking motion, and hence to reduce energy consumption. Numerical simulation analyzed joint torques in each limb length and slope angle under walking on a slope. The optimal rate of rear leg length (RRL) is derived by the simulation as the physical structure. Our analysis suggests that the joint torque will increase as the slope angle becomes steeper in the case that the rear legs are shorter than forelegs. On the other hand, the joint torque will decrease as the slope angle is declined in the case that the forelegs are shorter than the rear legs. Experimental results validated the simulation analysis.

This paper introduces a new wearable handling support system for a person who has trouble in motor capability of his or her upper limb. The support system is used as not only a support system to make his upper limb active in daily life but also a rehabilitation system to reduce manual loads of physical therapists. The system measures three rotation angles of patientpsilas head: pitch, roll and yaw to control three degrees of freedom of the support system; angle of elbow joint, angle of wrist joint and hand close/open, respectively. Hemiplegia patient who has paralysis of one half of the patient body can use both arms cooperatively by wearing the handling support system on the paralysis side. In our experiments, the system helps pouring task from POP bottle to a glass, while an upper limb on paralysis side of a user grasps the POP bottle and the other upper limb grasps the glass.

This paper introduces a vertical ladder climbing of the humanoid robot only by the posture control without any external sensors. The humanoid robot does not have any special structure for fixing the body to the ladder. The robot maintains the body on the ladder by its grippers like human does. As a problem of this locomotion, a free gripper position of the climbing robot is not controllable because a yawing of the robot body around the axis connecting a supporting gripper and foot on the ladder is not fixed. To solve this problem, the momentum around AOY caused by the gravity is used to control the yaw motion of the body so that the various gait such as pace gait and trot gait could be realized in a ladder climbing maneuver. The algorithm of ladder climbing with recovery motion is experimentally verified by using ldquomulti-locomotion robot(MLR)rdquo which is developed to achieve various types of locomotion such as biped, quadruped walking and brachiation.

As one of dynamics-based control of biped walking, some researchers presented the control method to take advantage of robot dynamics directly by use of point-contact state between a robot and the ground. We proposed passive dynamic autonomous control (PDAC) previously (2004) as one of point-contact methods. PDAC expresses the robot dynamics as a 1-dimensional autonomous system based on the two concepts: 1) point-contact 2) virtual constraint (proposed by Grizzle et al. (2001) and Westervelt et al. (2004)). We actually realized 3D dynamic walking by means of proposed method, however stability is not proved and the convergence domain is not clear. Thus, this paper finds the convergence domain of the previously proposed controller and proves the stability by the Liapunov theory. Finally, the correctness of stability proof is confirmed by the numerical simulation.

The purpose of the present study is to control human biological rhythm and life cycle by optimization of awakening timing. We developed a wearable interface for controlling awakening time named "BRAC (biological rhythm based awakening timing controller)". BRAC could estimate bio-rhythm by pulse wave from finger tip and send awake signal to user. An ordinary alarm clock operates according to set times that have to be set in advance. However, humans have a rhythm in their sleep, which affects one's sleep depth and wake-up timing. We consider the simplest way to control or reset human's bio-rhythm or life style is to optimize the awakening timing and the sleeping hours. We examined the relationship between controlling awakening timing based on autonomous nerve rhythm and equilibrium function. Our findings suggest indicate that the prototype "BRAC" could evaluate user's biological rhythm and awakes user at the time optimized for physical function of equilibrium.

This paper describes a control for the brachiation robot with holonomic constraint. In our previous work, the brachiation controller is composed of two actions: swing-back and locomotion. The purpose of swing-back is to excite a robot so as to achieve the locomotion successfully, while locomotion action is to move forward by releasing the ladder with the backward arm in the direction of locomotion and gripping the target ladder with another arm. However, the conventional control can not apply brachiation in irregular ladder. And the convetional control was not consider energy efficiency. Thus, a novel method to achieve brachiation in irregular ladder and an energy-efficient brachiation by exacting a swing-back during locomotion is proposed. Experimental results show that the proposed method can improve the locomotion action as much as over 30% in energy consumption.

This paper proposes the control method of biped walking with heel-off motion. Heel-off motion made it possible to avoid the problem for the impact shock at foot-contact to break the stabilization of walking. The 3D motion is separated into lateral and sagittal motion and each motion is designed individually under the assumption that each motion is possible to be treated independently each other. We adopt the approximate 1-mass model in both planes and derive the dynamics based on these models. It is assumed that the lateral motion is relevant to heel-off motion. On the other hand, in the sagittal plane, there are two phases: 1) the center of rotation (contact point) is ankle joint. 2) the center of rotation is toe. In phase 2), heel-off motion is designed to diminish the impact shock at foot-contact. By applying PDAC to the dynamics, phase around the contact point can be derived. By means of this phase of dynamics, it is possible to inspect heel-off motion analytically. We design the stabilizing controller for each plane and confirm the convergency of dynamics with the numerical simulation

In this paper, we propose an environment-adaptive antipersonnel mine detection system called Advanced Mine Sweeper. Advanced Mine Sweeper is developed based on sensing technologies, access-control technologies and system integration technologies for safe and effective demining procedure after the Level II survey. Advanced Mine Sweeper consists of a sensing vehicle/unit, an access vehicle, and an assist vehicle. The sensing vehicle/unit is composed of an integrated sensor and a small-reaction sensor head manipulator. The access vehicle is parked facing a mine field in order to control the sensing unit position in a global area using its boom. The assist vehicle is parked keeping some distance from a mine field. It controls the sensing vehicle/unit and access vehicle and then displays the processed sensing information for landmine detection, receiving sensing information and sensing position. By using this system, experiments in the field buried dummy landmines were carried out for the utility and performance evaluation

We propose an energy-based control method for a multilocomotion robot to improve the stability of continuous brachiation. The target continuous brachiation is an effective locomotion from one bar to another exchanging a kinetic energy with potential energy like a pendulum. Our control strategy for the continuous brachiation is to control the swing-back action so that the robot pumps up the feasible energy to grasp a target bar, and then the locomotion action is designed based on the symmetric motion of a pendulum in order to conserve the total energy: summation of the kinetic and potential energy. The proposed controller is implemented on a new type of mobile multilocomotion robot named “Gorilla Robot III” whose dimensions are mimicking those of a gorilla. Continuous brachiation on various uniform ladders is experimentally achieved with this robot. The experimental results show the validity of our control algorithm. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 1025–1043, 2006.

In this paper, we develop the lateral motion control based on Passive Dynamic Autonomous Control (PDAC) in order to solve two following problem in previous paper: 1) the step-length control in the sagittal plane results in the delay of one step cycle since walking period is not controlled taking the sagittal control effect into consideration 2) error of the lateral dynamics is big since the effect of the sagittal motion on the lateral dynamics is neglected. At first, the walking period is controlled, by adjusting the amplitude of side-to-side rocking motion. Secondly, the value to lengthen the lateral inverted pendulum is decided according to the sagittal motion effect on it. By means of this new lateral control in addition to sagittal step-length control, the 3-dimensional stable dynamic walking based on the robot inherent dynamics is realized.

In this paper, we present a control method to realize continuous brachiation. The target brachiation is basically divided into two actions: a swing action and a locomotion action. In order to realize the continuous brachiation effectively and stably, it is necessary to control these actions according to the total energy of the system. Because brachiation has been modeled as a pendulum-like motion and the amplitude of the oscillation determines whether the robot can grasp the target bar or not. In consideration of this point, an energy based control method is proposed and introduced into the swing action controller. The purpose of this method is to control the angular velocity of the swing action in order to satisfy the desired energy evaluated by the distance of bars. Experimental results show that the robot can successfully achieve smooth, continuous brachiation.

In this paper, the new control method to realize 3D natural dynamic walking based on the 3D robot inherent dynamics is proposed. The proposed method describes robot dynamics by use of a 3D inverted pendulum model and applies passive dynamic autonomous control (PDAC) to it. By utilizing the polar coordinate system to express the robot state around the contact-point between robot and the ground and applying PDAC, it is possible to express the 3-dimensional dynamics as 1-dimensional autonomous system. Due to autonomy, this 1D dynamics has the conservative quantity named PDAC constant. We build the stabilizing controller by means of PDAC constant and analyze the walking based on the 1D dynamics. Finally the proposed method is tested by experiment.

The purpose of this research is to control human state and biological rhythm. The system has to be adaptive and intelligent because it must deal with human information including personal differences. As a first step to achieve the function, we try to estimate a human's state in sleep using a wearable sensor device, under less physical movement than daytime. In the next step, we try to control human biological rhythm using the method to estimate human sleep state. We consider the simplest way to control human's sleep is to control awakening timing and sleep time. The proposed system can estimate human sleep quality and rhythms, and provide stimuli based on wake up timing. The system uses only pulse wave to estimate sleep quality because the pulse wave can be measured more easily than PSG.

This paper proposes an algorithm to estimate human intentions during walking. Not only walk start or stop but walking cycle is considered as the intentions in this paper. The algorithm is embedded into a walking support system, a wearable robot "Robot Suit HAL-3", for paraplegia patients. The estimation of patients' intentions is indispensable for effective and comfortable motion support, but the biological signals such as myoelectricity which is used for the support by HAL-3 cannot be measured properly. The proposed algorithm, therefore, estimates patients' intentions from other channels such as a floor reaction force and a body posture. The effectiveness of this algorithm is investigated through experiments with two types of patients. One has a sensory paralysis on both legs, especially a left leg has severe trouble. The other has troubles in sensory and motor ability on both legs. We show HAL-3 supports patients' walk comfortably, estimating patient intentions.

This paper proposes passive trajectory control (PTC), a new control method of Acrobot, and discusses its application to biped walking robots. PTC makes the first joint passive and makes the point contact between the whole robot system and the ground, then actuates other joints according to the motion of the passive joint. Due to this interlock, the whole robot system becomes autonomous and the controller is independent of time. Hence, PTC makes it possible to design the robot motion based on not the trajectory of time, but the dynamics around the contact point. In this paper, we design the lateral motion of bipedal walking by means of PTC and realize the dynamic stable motion.

This paper proposes a control method of vehicle cooperative behavior in an intersection and junction without infrastructures such as a signal system, a road-vehicle communication system, and so on. The vehicle cooperative behavior enables vehicles to pass through an intersection one by one or to interflow at junction one by one without vehicle collision like a weaving and zipping manner. These behaviors are achieved by generating a special-temporal pattern of a reaction diffusion system, where a mutual communication between vehicles is realized only by TVC device. The mutual communication between vehicles can be expressed in the diffusion system of a certain morphogen so that only simple broadcasting communication could be enough for vehicle communication. Van der Pol model is used as one of the reaction diffusion system. Finally, the proposed algorithm for vehicle cooperative behavior is experimentally verified using actual autonomous mobile robots.

In this paper we propose a method to insert a long peg into a tandem shallow hole using search trajectory generation without force feedback. Automation of the assembly in a factory progressed in recent years. However the many processes where workers should assemble products by themselves still remain now. We call these processes "difficult assembly". The difficult assembly has the feature that a mating part has a unique shape. The RCC (Remote Center Compliance) is an effective method for assembly, but it is no longer useful on the condition that mating parts are complex. The RCC device has no durability since it is a product made from rubber, in addition a force sensor is expensive. If a robot could accomplish the assembly task without using those devices there is a advantage in terms of expense and durability. In our approach, the manipulator system inserts a long peg into the hole with switching the trajectory generation methods depending on the task condition.

This paper proposes a new type of rough terrain vehicle with the interconnected suspension expected to be used to detaining action. This interconnected suspension was proposed and based on posture control of rough terrain vehicle. This suspension has 4 leg-cylinders interconnected and by employing 2 AC motors it can control its posture readily. This suspension makes rough terrain vehicle simple in mechanism. By using this kind of interconnected suspension, the rough terrain vehicle can control its posture smoothly when it walks on rough terrain. In order to compensate the response delay time and improve the control system, we use preview control and the effect was proved in our research. The rough terrain vehicle can control its impact load on every wheel with the interconnected suspension. This kind of suspension can distribute impact load among wheels due to interconnecting every leg-cylinder. In our research, the reduction of impact load on vehicle wheels was proved by experiments. By making good use of the advantages of the interconnected suspension, it is possible that the rough terrain vehicle is actually applied to executing some special tasks such as demining action.

In this paper, we introduce an adaptive sensing method to a landform using a ground reflection of a ground penetrating radar (GPR). When GPR scans a ground surface, an antenna of GPR should be put on a ground as an ideal condition. The farther an antenna is put away from a ground, the shallower the sensing depth becomes, because a ground surface reflects most of the electromagnetic wave radiated by the antenna. Practically an antenna should be manipulated, keeping a small distance from a ground in order to avoid a collision with a ground. Besides, the distance should be controlled so as to observe the ground reflection at a constant position in B-scan image, which is eliminated by a simple algorithm. There are many sensors to measure a ground configuration, but we propose an adaptive sensing which does not require any additional sensors such as laser range finder. In addition, the ground reflection in B-scan image is precisely eliminated by manipulating the sensor head according to GPR sensor information. We show some experimental results to confirm its effectiveness and its performance.

This paper describes a robotic-head system as a multimodal communication device for human-robot interaction, and the system's potential application in home environments. Most robotic systems for natural user interaction have facial expressions, since facial expressiveness is regarded as a key component to developing personal attachment along with prosodic expressiveness. In the first part of the paper is the description of our robotic head system Character Robot Face (CRF). A deformation approach and a parametric normalization scheme are proposed to produce facial expressions of nonhuman face models with high recognition rates. In the second half of the paper, CRF is endowed with artificial emotions and assigned tasks conceivable in home environments. A coordination mechanism between the robot's mood (an activated emotion) and its task is proposed so that the robot can, by referring to the emotion-task history, select a task depending on its current mood if there is no explicit task command from the user. When the robot performs a task, a particular emotion value gets boosted according to the same emotion-task history so that the emotion is more likely to be activated.

This paper proposes a simplified generation method of regrasping motion. The regrasping motion is designed by evolutional programming (EP) in our conventional study and the obtained regrasping behavior should be adjusted according to some conditions; initial posture and dimensions of a grasping object. However, the designing process of the regrasping motion is off-line because it takes several minutes to find the optimal regrasping strategy by EP. In this paper, we therefore simplified the searching process for regrasping motion in order to apply it in the realtime process. Besides, this simplified generation method is enable to achieve a regrasping motion from arbitrary initial posture because there is no strategy that is previously designed. We show its effectiveness of the simplified generation method with numerical simulations, comparing the performance of the EP-based approach.

This paper discusses practical strategies for transition from a pinching to a power grasping, where a multi-fingered hand mounted on a robotic arm envelops a cylindrical object on a table. When the manipulation system grasps a cylindrical object like a pen on a desk, a complete enveloping is not impossible in the initial configuration. The system firstly pinches the object only with two or three fingers and then grasps it with fingers and a palm after regrasping. In this pinching-grasping transition maneuver, human unconsciously selects proper strategy according to some conditions including object dimensions and initial pinching positions. In this paper we therefore develop six possible strategies for this pinching-grasping transition and then investigate their performances for some objects with various dimensions and various grasping positions, using numerical simulations. Based on their results, a strategy selection algorithm for these conditions is proposed and some experiment results are shown.

Many entertainment and healing robots have been developed. These robots have synthetic emotions so that they select behavior based on their current emotional state. On the contrary conventional robots which have designed to perform repetitive factor or office jobs do not have such emotions. Usually human operators assign tasks in explicit manner using keyboard or voice commands. In this paper we propose a coordination mechanism between robot mood (an activated emotion) and its task. On one hand, referring to the emotion-task history of the mechanism, the robot selects a task depending on its current mood if there is no explicit task command from the user. On the other hand, when it performs a task, a particular emotion gets boosted based on the same emotion-task history so that this emotion is more likely to be activated by external stimuli.

The goal of our research is to achieve a dynamic and skillful motion by a real robot. We have previously developed a brachiation controller that can achieve two kinds of brachiation: overhand and side-hand motions. In this paper, we redesign behavior controllers in order to achieve a stable continuous brachiation without a break. We make the behavior controllers that can be controlled by the angle around a catching bar because the angle is the most dominant parameters of the brachiation motions. In addition, we introduce the action of bending elbow joints in order to realize a pendulum motion and to reduce the impact of the moment of catching a bar. Finally, we show the experimental results that the robot could successfully achieve continuous brachiation.

This paper introduces new planning and control methods for supermedia-enhanced real-time telerobotic operations via the Internet. Supermedia is the collection of video, audio, haptic information, temperature, and other sensory feedback. However, when the communication medium used, such as the Internet, introduces random communication time delay, several challenges and difficulties arise. Most importantly, random communication delay causes instability, loss of transparency, and desynchronization in real-time closed-loop telerobotic systems. Due to the complexity and diversity of such systems, the first challenge is to develop a general and efficient modeling and analysis tool. This paper proposes the use of Petri net modeling to capture the concurrency and complexity of Internet-based teleoperation. Combined with the event-based planning and control method, it also provides an efficient analysis and design tool to study the stability, transparency, and synchronization of such systems. In addition, the concepts of event transparency and event synchronization are introduced and analyzed. This modeling and control method has been applied to the design of several supermedia-enhanced Internet-based telerobotic systems, including the bilateral control of mobile robots and mobile manipulators. These systems have been experimentally implemented in three sites test bed consisting of robotic laboratories in the USA, Hong Kong, and Japan. The experimental results have verified the theoretical development and further demonstrated the stability, event transparency, and event synchronization of the systems.

Proposes adjusting methods of a regrasping strategy according to position and posture errors of a grasping object. We have already derived a generation algorithm for the regrasping strategy by evolutionary programming. The regrasping strategy however becomes inapplicable when the relative position and posture between a hand and an object is not same as those in numerical simulation. We therefore propose some adjusting methods which can change the intermediate position and posture of a grasping object. This method can avoid the limitation of joint work area and fingertip's slip so that it could extend the tolerable area of the position and posture error. We show its effectiveness for the regrasping motion with numerical simulations and experiments.

This paper explores a human-robot mutual communication system, which human users can either communicate with or use as an information terminal. In particular, we propose the deformation based facial expression system. We also propose a robotic vision system, which changes its visual attention according to the environment. Firstly, the system must have advanced abilities to express their intention by means of making facial expressions, gestures, or speech. Above all, facial expression. Reconsidering the facial action coding system and action unit from the point of what expression of the robot human recognize easily. We propose the deformation based expression system. Secondly, to realize fluent communication between human and robots, we propose a robot vision system changing its gazing communication according to the environment and situation based on visual recognition. We developed an original character robot (CR) and evaluated the proposed methods. Consequently, it was shown that human-robot mutual communication is achievable.

Proposes adjusting methods of a regrasping strategy according to position and posture errors when grasping an object. We have already derived a generation algorithm for the regrasping strategy by evolutionary programming. The regrasping strategy however becomes inapplicable when the relative position and posture between a hand and an object is not same as those in numerical simulation. We therefore propose some adjusting methods which can change the intermediate position and posture when grasping an object. This method can avoid the limitation of joint work area and fingertip slip so that it could extend the tolerable area of the position and posture error. We show its effectiveness for the regrasping motion with numerical simulations and experiments.

In this paper, we firstly introduce new concept of multi-locomotion robot inspired by an animal and a developed robot "Gorilla Robot II", which can select a better locomotion from biped locomotion, quadruped locomotion and brachiation, according to an environment. We consider "Brachiation" which is one of the most dynamic motions in animal motions. Then we propose an enhanced control method for the robot in order to achieve a brachiation motion, adjusting the timing of local behaviors. We show that the developed robot successfully perform two kinds of brachiation motions.

Robotic operations carried out via the Internet face several challenges and difficulties. These range from human-computer interfacing and human-robot interaction to overcoming random time delay and task synchronization. These limitations are intensified when multi-operators at multisites are collaboratively teleoperating multirobots to achieve a certain task. In this paper, a new modeling and control method for Internet-based cooperative teleoperation is developed. Combining Petri net model and event-based planning and control theory, the new method provides an efficient way to model the concurrence and complexity of the Internet-based cooperative teleoperation. It also provides an efficient analysis tool to study the stability, transparency and synchronization of the system. Furthermore, the new modeling and control method enables us to design an Internet-based cooperative telerobotic system that is reliable, safe and intelligent. This new method has been experimentally implemented in a three site test bed consisting of robotic laboratories in the USA, Hong Kong and Japan. The experimental results have verified the theoretical development and further demonstrated the advantages of the new modeling and control method.

A method for simplification of teaching in robotic assembly is presented. Generally, an assembly task is a process in which a constraint condition between two workpieces changes. There has been much research on teaching an assembly task to a robot system by a model-based approach. However, it takes a lot of time to revise information of models that depend on the task environment when every new task is taught to a robot in these model-based approaches. We propose a method to simplify teaching by taking an approach where a human teaches a task to a robot without giving models of the task environment and task processes. Additionally, we also propose a method to realize robotic assembly that is robust to errors by executing a task as a transition process of a constraint condition. Experimental results show the effectiveness of our method.

The purpose of the study is to build a relaxation system which can control a user's body condition, changing the operation mode and intensity of the massage seat according to the user's current condition. Heart rate is an index of human conditions which can be easily measured, and it has chaotic dynamics. We show relations between the intensity of the massage operation and two indices which express chaotic properties such as correlation dimension and Lyapunov exponent. These data are indispensable for building a feedback loop between the relaxation system and a user.

We propose a method to acquire a hierarchical behavior controller which is achieved by shifting phase between local behaviors. Complex behavior is hardly obtained using any unsupervised leaning methods, because of enormous search space. In order to reduce the search space, a hierarchical behavior structure is effective. We have previously proposed a hierarchical behavior controller, which consists of two kinds of modules: behavior coordinator and behavior controller. It is applied to the control problem of a seven-link brachiation robot, which moves dynamically from branch to branch like gibbon swinging its body. Numerical simulations demonstrate that the obtained controller can successfully achieve continuous locomotion.

We have studied the generation of regrasping motion for a four-fingered robot using evolutionary programming (EP). EP has the advantage of finding the set of optimal numerical values but it requires many iterations to find it. The regrasping strategy obtained cannot be applied to other object shapes than those used in the search process. We consider that the regrasping strategy generated by EP should be reused for other sizes of object. We propose an expansion of the method for other sizes of grasped object. We show the effectiveness of the method with experimental results.

Proposes an adaptation method for a behavior-based locomotion robot. Utilization of a behavior-based controller makes the controller designing process easier and shorter, because the designer can deal with behavior controllers for simple behaviors independently, and after that can coordinate those behavior controllers in order for a robot to achieve the objective complex behavior. Some problems are still remaining. One is how to adjust the total behavior when the target task or environment is changed. We propose the method to adjust the behavior coordinator against some changes. This method adjusts the activation level of each behavior controller for the changes in fewer trials. It is applied to real brachiation robot control. The brachiation robot has a redundant mechanism to locomote from branch to branch like a long-armed ape.

The control of multi-fingered robot hands has been the subject of interest. To manipulate some object with regrasping motion, there are many parameters to be determined; the grasping points, grasping forces, regrasping phases, finger allocation and so on. It is difficult to optimize such manipulation parameters for achieving effective manipulation. We propose a generation method of regrasping motion for a four-fingered robot hand using evolutionary programming (EP). In this case, EP determines not only finger motions, but also rotation of the target object in order to increase its manipulability. In manipulating an object like a rectangular solid, it is very important to change the object directions and to grasp another face according to the task progress because the grasping faces tend to be limited to only two. The evolutionary optimization method is generally able to find optimal solutions without a supervisor after much iteration, which makes it almost impractical to apply a real robot directly. Therefore we control the real robot hand with an optimal controller that has been generated in computer simulations. We show the effectiveness of the proposed acquisition method for the regrasping motion with experimental results.

The e-world, also known as the Internet, has added a new dimension to many of the traditional concepts in industrial applications and everyday life. The use of robots has dramatically expanded the potential of e-services. Individuals with particular expertise can perform highly accurate and fairly complicated tasks remotely via the Internet. This increase in the human reachability is faced by several obstacles. Reliable and efficient robot facilitated services via the Internet face several challenges. These range from human-computer interfacing and overcoming random time delay to task synchronization and human-robot interaction. These limitations intensify when many operators in many sites are involved. This paper provides new theoretical and experimental results on these challenges. Specifically, multisite cooperative control of an Internet based mobile manipulator is presented. The two main characteristics of this system are Internet based real-time closed loop control and coordinated operation. In addition, it is shown that despite random time delay the stability and synchronization of the system were achieved using event-based control.

The authors propose an adaptation and learning algorithm to adjust behavior coordinator against small changes of the objective task or a new one. This method measures the relation between the each local behavior and the global behavior, and then determines the direction of change of the activation values from the behavior coordinator based on the measurements. The monkey-type locomotion robot, Brachiator III has 13 links and 12 joints and is able move like a real ape in a three-dimensional space. The controller is designed for a primitive case. The proposed algorithm is used when the branch interval is changed and when continuous locomotion is desired. We show the effectiveness of the proposed algorithm through experiments using Brachiator III.

The control of multi-fingered robot hands has been the subject of recent interest. To manipulate some object with it, it is necessary to determine the contact points and grasping forces at the fingertips, but it is difficult to optimize such manipulation parameters for performing effective manipulation. In this paper, we propose an acquisition method for re-grasping motion for a four-fingered robot hand using evolutionary programming (EP). In this case, EP determines not only when and where the fingers are moved, but also which finger is operated at the next contact point according to the attitude changes of object grasping with the grasping stability. Evolutionary programming is generally able to find an optimal solution without a supervisor after much iteration, which is almost impractical using a real robot. Therefore we control the real robot hand with the optimal controller that has been obtained in computer simulations. We show the effectiveness of the proposed acquisition method for the re-grasping motion with experimental results.

We propose a searching method of the grasping and manipulating an object in the 3D space by using a four-fingered robot hand, which is applicable to the real robot hand. To manipulate an object, it needs to teach contact points and forces of fingertip, but it is difficult to optimize each parameter for natural grasping. This paper shows the manipulation using evolutionary programming (EP) to optimize the motion of the fingers. In this case, EP determines not only when and where the fingers are moved, but also which finger is operated to the next contact point as the grasping attitude is changed. Moreover, the coding of individual is unique, which makes it easy to optimize the parameter. The result examines the effective in computer simulation in this paper but it would be applicable to a real robot hand.

This paper proposes a flexible transfer system (FTS) as one of the self-organizing manufacturing systems. The FTS is composed of autonomous robotic modules, which transfer a palette carrying an object. Through the self-organization of a multilayer strategic vector field corresponding to a task, the FTS can generate quasi-optimal transfer path in fully distributed way. We apply the learning automata for path generation algorithm. Simulation is conducted to evaluate the basic performance of the system and the results show the feasibility of application. Also, the developed hardware is explained.

Complex behavior is difficult to obtain using an unsupervised leaning method because of the enormous search space required. In this paper, we propose the hierarchical behavior controller which consists of three types of modules: behavior coordinator, behavior controller and feedback controller. We also propose a new learning algorithm for the behavior coordinator and the behavior controller that consists of some sub-coordinators and some sub-controllers, respectively. This algorithm selects a deficient one by evaluating each sub-coordinator or sub-controller using multiple regression analysis based on previously obtained evaluation values. This can reduce the search area and the learning times by avoiding the necessity of trying to tune good sub-coordinators or sub-controllers. The hierarchical behavior controller is applied to the problem of controlling a seven-link brachiation robot, which moves dynamically from branch to branch like gibbon swinging its body.