Marker-based optical motion capture (MoCap) is a vital tool in applications such as virtual production, and movement sciences. However, reconstructing scattered MoCap data into real motion sequences is challenging, and data processing is time-consuming and labor-intensive. Here we propose a novel framework for MoCap auto-labeling and matching. In this framework, we designed novel clusters of reflective markers called auto-labeling encoded marker clusters (AEMCs), including clusters with an explicit header (AEMCs-E) and an implicit header (AEMCs-I). Combining cluster design and coding theory gives each cluster a unique codeword for MoCap auto-labeling and matching. Moreover, we provide a method of mapping and decoding for cluster labeling. The labeling results are only determined by the intrinsic characteristics of the clusters instead of the skeleton structure or posture of the subjects. Compared with commercial software and data-driven methods, our method has better labeling accuracy in heterogeneous targets and unknown marker layouts, which demonstrates the promising application of motion capture in humans, rigid or flexible robots.

Cardiovascular image registration is an essential approach to combine the advantages of preoperative 3D computed tomography angiograph (CTA) images and intraoperative 2D X-ray/digital subtraction angiography (DSA) images together in minimally invasive vascular interventional surgery (MIVI). Recent studies have shown that convolutional neural network (CNN) regression model can be used to register these two modality vascular images with fast speed and satisfactory accuracy. However, CNN regression model trained by tens of thousands of images of one patient is often unable to be applied to another patient due to the large difference and deformation of vascular structure in different patients. To overcome this challenge, we evaluate the ability of transfer learning (TL) for the registration of 2D/3D deformable cardiovascular images. Frozen weights in the convolutional layers were optimized to find the best common feature extractors for TL. After TL, the training data set size was reduced to 200 for a randomly selected patient to get accurate registration results. We compared the effectiveness of our proposed nonrigid registration model after TL with not only that without TL but also some traditional intensity-based methods to evaluate that our nonrigid model after TL performs better on deformable cardiovascular image registration.

A key challenge in robotics is to create efficient methods for grasping objects with diverse shapes, sizes, poses, and properties. Grasping with hand-like end effectors often requires careful selection of hand orientation and finger placement. Here, we present a fingerless soft gripper capable of efficiently generating multiple grasping modes. It is based on a soft, cylindrical accordion structure containing coupled, parallel fluidic channels, which are controlled via pressure supplied from a single fluidic port. Inflation opens the gripper orifice for enveloping an object, while deflation allows it to produce grasping forces. The interior is patterned with a gecko-like skin that increases friction, enabling the gripper to lift objects weighing up to 20 N. Our design ensures that fragile objects, such as eggs, can be safely handled, by virtue of a wall buckling mechanism. In reverse, the gripper can be deflated to reach into an opening or orifice then inflated to grasp objects with handles or cavities. The gripper may also integrate a lip that enables it to form a seal and, upon inflating, to generate suction for lifting objects with flat surfaces. In this article, we describe the design and fabrication of this device and present an analytical model of its behavior when operated from a single fluidic port. In experiments, we demonstrate its ability to grasp diverse objects, and show that its performance is well described by our model. Our findings show how a fingerless soft gripper can efficiently perform a variety of grasping operations. Such devices could improve the ability of robotic systems to meet applications in areas of great economic and societal importance.

Lower-limb assisted exoskeletons are widely researched for movement assistance or rehabilitation training. Due to advantages of compliance with human body and lightweight, some cable-driven prototypes have been developed, but most of these can assist only unidirectional movement. In this paper we present an untethered cable-driven ankle exoskeleton that can achieve plantarflexion-dorsiflexion bidirectional motion bilaterally using a pair of single motors. The main weights of the exoskeleton, i.e., the motors, power supplement units, and control units, were placed close to the proximity of the human body, i.e., the waist, to reduce the redundant rotation inertia which would apply on the wearer’s leg. A cable force transmission system based on gear-pulley assemblies was designed to transfer the power from the motor to the end-effector effectively. A cable self-tension device on the power output unit was designed to tension the cable during walking. The gait detection system based on a foot pressure sensor and an inertial measurement unit (IMU) could identify the gait cycle and gait states efficiently. To validate the power output performance of the exoskeleton, a torque tracking experiment was conducted. When the subject was wearing the exoskeleton with power on, the muscle activity of the soleus was reduced by 5.2% compared to the state without wearing the exoskeleton. This preliminarily verifies the positive assistance effect of our exoskeleton. The study in this paper demonstrates the promising application of a lightweight cable-driven exoskeleton on human motion augmentation or rehabilitation.

We present a real-time monocular simultaneous localization and mapping (SLAM) system with a new distributed structure for multi-UAV collaboration tasks. The system is different from other general SLAM systems in two aspects: First, it does not aim to build a global map, but to estimate the latest relative position between nearby vehicles; Second, there is no centralized structure in the proposed system, and each vehicle owns an individual metric map and an ego-motion estimator to obtain the relative position between its own map and the neighboring vehicles’. To realize the above characteristics in real time, we demonstrate an innovative feature description and matching algorithm to avoid catastrophic expansion of feature point matching workload due to the increased number of UAVs. Based on the hash and principal component analysis, the matching time complexity of this algorithm can be reduced from O (log N ) to O (1). To evaluate the performance, the algorithm is verified on the acknowledged multi-view stereo benchmark dataset, and excellent results are obtained. Finally, through the simulation and real flight experiments, this improved SLAM system with the proposed algorithm is validated.

Aquatic-aerial multimodal vehicle is a new concept aircraft that can freely shuttle between water and air. Some of the natural organisms provide the inspiration to realize this multi-locomotion. Most of current prototypes use rigid link mechanisms or hinges to morph the structure thus to adapt to the aquatic-aerial environment, which is commonly complicated and bulky. In this paper, we present a novel prototype with pneumatically-driven soft fins and arms that can fold and spread just like the flying squid. The fins and arms can augment the lift force during flying by spreading and reduce drag force during swimming by folding. The performance of the morphable structures was investigated in wind and water tunnel. The results explain the tradeoff strategies of multimodal-locomotion between water and air, and verify the feasibility of the novel aquatic-aerial vehicle with soft morphable structures.

Remoras employ their adhesive discs to rapidly attach to and detach from a wide range of marine surfaces. By analyzing high-speed images of remoras' (Echeneis naucrates) hitchhiking behavior, we describe the fish's detachment mechanism as a lip curling up to break the seal between the disc and substrate. By mimicking the kinematic and morphological properties of the biological disc, we fabricated a multi-material biomimetic disc (whose stiffness spans four orders of magnitude) that is capable of both attachment and detachment. Detachment is realized by a flexible cable-driven mechanism that curls the anterior region of the silicone soft lip, allows leakage under the disc, and equalizes the internal pressure to the external pressure. The disc lamellae with attached carbon fiber spinules can be rotated by hydraulic soft actuators whose internal pressure is precisely tuned to the ambient underwater pressure. During attachment, increasing the rotational angle of the lamellae and the preload of the disc significantly enhanced the adhesive forces. We found that curling up the soft lip and folding down the lamellae rapidly reduced the pulling force of the disc by a factor of 254 compared to that under the attached state, which lead to detachment. Based on these mechanisms, underwater maneuvers involving repeated attachment and detachment were demonstrated with an integrated ROV unit that had a self-contained actuation and control system for the disc. This study lays a foundation for the development of fully untethered robotic systems for underwater hitchhiking in real-world marine environments.

This paper presents a soft actuator embedded with conductive liquid metal and shape memory epoxy (SME) which function together to enable self-sensing, tunable mechanical degrees of freedom (DoF), and variable stiffness. We embedded thermoplastic shape memory epoxy in the bottom portion of the actuator. Different sections of the SME could be selectively softened by an implanted conductive silver yarn located at different positions. When an electric current passes through the conductive silver yarn, it induces a phase transition that changes the epoxy from stiff state to compliant state. Each section of SME could be softened within 5 s by applying a current of 200 mA to the silver yarn. To acquire the strain curvature, eGaIn was infused into a microchannel surrounding the chambers of the soft actuator. A spiral-shaped eGaIn sensor was also attached to the tip of the actuator to perceive the contact with reliable dynamic force response. Systematic experiments were performed to characterize the stiffness, tunable DoF, and sensing property. We show the ability of the soft composite actuator to support a weight of 200g at the tip (as a cantilever) while maintaining the shape and the ability to recover its original shape after large bending deformation. In particular, seven different motion patterns could be achieved under the same pneumatic pressure of the actuator due to selectively heating the SME sections. A gripper which was fabricated by assembling two actuators to a base was able to grasp the weight up to 56 times of a single actuator through an appropriate motion pattern. For demonstration purposes, the gripper was used to grasp various objects by adjusting the DoF and stiffness with real-time feedback of the bending strain and the contact force.

Shape memory alloy (SMA) actuators exhibit high strain, high energy density, and self-sensing ability, which are promising characteristics for application in soft robot systems. This paper proposes a new SMA actuator with high accuracy that is driven by antagonistic SMA and super-elastic SMA (SSMA) wires or pairs of SMA wires that is intended to be used in miniature flexible structures. A multifeedback control methodology is presented for the actuator that uses feedback from both the SMA and SSMA wires. The prestress was chosen to minimize the gap between the heating and cooling paths of the strain-to-resistance (S-R) curve for both antagonistic SMA and SSMA. A radial basis function neural network was used to establish the S-R curve model for both self-sensing feedback and SSMA feedback. To achieve better system accuracy and stability, a data-fusion algorithm (based on the support function) was used to combine the multifeedback data. Accurate and stable motion control is demonstrated through multistep response, sinusoidal tracking, and force-disturbance tests. The experimental results show that the combination model using all the feedback has superior accuracy compared to the models that use self-sensing feedback or SSMA feedback. In addition, the maximum standard deviation within the SMA-SSMA antagonistic platform and the paired-SMA antagonistic platform can be reduced to 0.036% and 0.026%, respectively. A soft joint with two degrees of freedom is illustrated to demonstrate how the current research concept could potentially be implemented in bionic soft robots.

There have been increasing demands for developing robotic system combining camera and inertial measurement unit in navigation task, due to their low-cost, lightweight and complementary properties. In this paper, we present a Visual Inertial Odometry (VIO) system which can utilize sparse depth to estimate 6D pose in GPS-denied and unstructured environments. The system is based on Multi-State Constraint Kalman Filter (MSCKF), which benefits from low computation load when compared to optimization-based method, especially on resource-constrained platform. Features are enhanced with depth information forming 3D landmark position measurements in space, which reduces uncertainty of position estimate. And we derivate measurement model to access compatibility with both 2D and 3D measurements. In experiments, we evaluate the performance of the system in different in-flight scenarios, both cluttered room and industry environment. The results suggest that the estimator is consistent, substantially improves the accuracy compared with original monocular-based MSKCF and achieves competitive accuracy with other research.

Intelligent unmanned autonomous systems are some of the most important applications of artificial intelligence (AI). The development of such systems can significantly promote innovation in AI technologies. This paper introduces the trends in the development of intelligent unmanned autonomous systems by summarizing the main achievements in each technological platform. Furthermore, we classify the relevant technologies into seven areas, including AI technologies, unmanned vehicles, unmanned aerial vehicles, service robots, space robots, marine robots, and unmanned workshops/intelligent plants. Current trends and developments in each area are introduced.

The quality of holes has important influence on the mechanical strength, assembly quality and life of aircraft, and inferior quality holes may even cause airplane crash and casualties. The perpendicular accuracy of holes during drilling is crucial one of all the factors influencing the quality of holes. In order to improve the perpendicular accuracy during drilling, this paper presented an attitude adjustment mechanism and attitude adjustment algorithm for the end effector. For the mechanism, it adjusts the drill bit attitude by using double eccentric discs and a spherical pair. After the surface normal vector at drilling point is obtained, double eccentric discs will rotate define angels calculated by using attitude adjustment algorithm based on the shortest time principle to achieve the coincidence of the surface normal vector and the drill bit axis vector if the angle between the normal vector and drill bit axis vector is greater than 0.5°. To demonstrate the method mentioned above, simulation and experiment are carried out on the aeronautical drilling robot. The results show that the attitude adjustment mechanism and attitude adjustment algorithm can increase the perpendicular accuracy of holes during drilling and satisfy the demand in automatic aircraft assembly.

This paper presents a novel design for the soft continuum manipulator based on beehive structure. Our design inspiration derives from the beehive hexagon structure, which has some characteristics of compact layout, low material consumption, thinner thickness of wall, and higher structure strength. The manipulator includes several same modules which composed of many hexagon cell units, the deformation of these cell units synthesize the module macroscopic movement. By installing several modules in series, we can form the manipulator arm. For module fabrication, we adopt 3D printing technology and use the silicone rubber as the flexible material; these measures ensure that the complex shape of the module can be achieved and make the module easier to deform elastically. Based on pneumatic technology, we build the control system and verify its operation via some experiments. In the gravity environment, three-section (about 180mm long at uninflated state) manipulator's maximum bending angle reaches about 90°, its elongation is close to 2:1. We also do a five-section experiment to acquire the manipulator's motion under different section combinations. The experiments verified that the manipulator has both good flexibility and operational capabilities.

Fish caudal fin is a prominent example of biological propulsion, in which the caudal peduncle, fin rays and fin membrane together form a dynamic locomotory system. In this paper, we developed a bio-robotic model to mimic the caudal fin structure and kinematics of Bluegill Sunfish (Lepomis macrochirus). We coupled controlled oscillations in both heave and pitch directions to the robot to model the caudal peduncle motion of swimming fishes. Synchronized multi-axis force transducer and particle image velocimetry were then used to quantify the hydrodynamic forces and wake flow in the vertical plane. We found that changing the flow speed and the phase between the caudal fin ray and peduncle locomotion resulted in significantly different lift and thrust force. DPIV results showed that the vortex jet angle changed with flow speed and phase φ. According to current experiment, we hypothesized that the fish caudal fin may function as a “flexible vectoring propeller”, and may be responsible for the three-dimensional maneuverability of fishes.

This paper presents modular self-reconfigurable robots for grasping an unknown object based on a grasp quality metric. The presented self-reconfiguration approach makes use of basic motions performed by individual robots to change the structure. The method to solve for forward kinematics as well as configuration representation is proposed based on relationship between robotic modules. This method can be used to update the estimated contact points in self-reconfiguration. Incorporating a grasp quality metric of form closure into self-reconfiguration, the structure for grasping can be evaluated until a desired metric is obtained. Grasping and self-reconfiguration simulation experiments are presented, showing the availability and effectiveness of the proposed approach.

This paper presents a biomimetic robotic fish that swims using thunniform kinematics for advanced underwater mobility. Propulsion and maneuvering of the robotic fish are achieved with a lunate caudal fin that undergoes combined translational and rotational motion. A parallel four-bar propulsive mechanism attached to the rear of the rigid torpedo-shaped body is used to deliver motor rotation to the caudal fin. Oscillatory control signals for the tail joints are generated with a CPG controller composed of two unidirectionally coupled Hopf oscillators. Coupling terms that allow direct specification of phase relation between oscillators are formulated. The maximum speed of the robotic fish can reach 2.0 m/s and excellent maneuverability has been exhibited. The outstanding swimming performances present exciting possibilities for real-world deployment of the robotic fish.

Aiming at the robot drilling perpendicularity in aircraft assembly, a surface normal measurement method is presented and a drilling end effector is designed. Four laser ranging sensors are uniformly distributed around the drill to measure the surface normal as four non-coplanar points define a unique circumscribed sphere and the sphere center can be calculated. By this principle, the method measures four points coordinates on the curved surface in the drilling area using four laser ranging sensors. If the four laser ranging sensors are close enough to each other, it is reasonable to assume that the drilling point is on the sphere surface. Therefore, the connection line of the sphere center and the drilling point is the surface normal at the drilling point. The angle θ between the normal and the axis of the drill is calculated and if θ is larger than 0.5 degree, the drilling end effector will adjust the attitude of the drill to make sure θ is smaller than 0.5 degree to meet the requirement in aircraft assembly. A novel adjusting mechanism is designed in the end effector which can keep drill vertex immobile when adjusting drill position. Thus, it is not required to remove the drill vertex to the mark point. Simulation results of three kinds curved surfaces show that the surface normal measurement method is accurate and efficient. Experiments on aviation drilling system results also demonstrate the adjusting mechanism is effective with high accuracy.

The propulsive efficiency is the key issue related to the practical application of the robotic fish. The negative work of the muscle of the biological fish reveals the efficient propulsion mechanism of swimming. In this paper, a distributed control system is presented for the robotic fish in an experiment platform. In order to study the relationship among the parameters, the negative work and the propulsive efficiency, this system can real time control each joint of the robotics fish and feedback the information. So the system is composed of three parts: the master-slave controller, the network and the driver of the joint motor. FPGA is chosen to accomplish the motor control and the data transition. Also the network based on LVDS has a high transfer rate to guarantee real-time and reliability of the system operation.

This paper presents a monitoring system of building electricity using IPv6 to establish a network. This smart metering system consists of three parts: the host software, the network and the sensor nodes. The network, whose data transmits via Zigbee wireless communication protocol, is designed based-on IPv6 protocol, and builds the IPv6 protocol on IEEE 802.15.4 wireless network. The Sensor node has a unique IP address and the sampling rate is set according to the host system. With real-time measurement of power, current and voltage values including RMS, instantaneous value and peak value, each node achieved accurate data sampling and communication stability. The host software is designed for building test characteristics, having a tree hierarchy and friendly interface to user. The reliability and accuracy of this monitoring system are verified in the experiment.

In this paper, techniques of force-feedback control are applied to the hydrodynamic study of a laboratory robotic fish. The experimental apparatus which allows a robotic model to accelerate from rest to a steady speed under self-propelled conditions is clearly described. In the current apparatus, the robotic fish is mounted on a servo guide rail system and the towing speed is not preset but determined by the measured force acting on the body of the fish. Such an apparatus enables the simultaneous measurement of power consumption, thrust efficiency and speed of a robotic model obtained under self-propelled conditions. The thrust efficiency of the robotic fish can be estimated based on a 2-D vortex ring force estimation method. By comparing the thrust performance of carangiform body-shaped robotic swimmer with different typical BCF (body and caudal fin ) swimming modes, i.e. anguilliform, carangiform and thunniform, we show that the robotic swimming fish with the thunniform kinematic movement not only reaches a higher steady swimming speed but is also more efficient than the other two modes However, in the start phase, using the anguilliform kinematic movement, the robotic swimmer accelerates faster among all kinematic movements. Ultimately, we found that the robotic fish always produce a double-row wake structure no matter which swimming mode used.

This paper presents a learning method to acquire fish-liking swimming with a CPG-based locomotor controller. The proposed method converts the related CPG parameters into dynamical systems that evolve as part of the CPG network dynamics. The teaching signals are derived from the kinematic model of carangiform swimming with trajectory approximation method. A novel coupling scheme for the CPG network, which are modeled as a chain of coupled Hopf oscillators is proposed to eliminate the influence of afferent signals on amplitude of the oscillator. The learning rules of intrinsic frequency, coupling weight and amplitude are formulated with phase space representation of the oscillators. The frequency, amplitudes and phase relations of the teaching signals can be encoded by the CPG network with the adaptation mechanisms. Numerical experiments are carried out to validate the effectiveness of the proposed learning rules.

Inspired by the swarm behaviours of social insects, research into the self-assembly of swarm robots has become an attractive issue in the robotic community. Unfortunately, there are very few platforms for self-assembly and locomotion in the field of swarm robotics. The Sambot is a novel self-assembling modular robot that shares characteristics with swarm robots and self-reconfigurable robots. Each Sambot can move autonomously and connect with the other. This paper discusses the concept of combining self-assembly and locomotion for swarm robots. Distributed control algorithms for self-assembly and locomotion are proposed. Using five physical Sambots, experiments were carried out on autonomous docking, self-assembly and locomotion. Our control algorithm for self-assembly can also be used to realize the autonomous construction and self-repair of robotic structures consisting of a large number of Sambots.

This paper presents a novel self-assembly modular robot (Sambot) that also shares characteristics with self-reconfigurable and self-assembly and swarm robots. Each Sambot can move autonomously and connect with the others. Multiple Sambot can be self-assembled to form a robotic structure, which can be reconfigured into different configurable robots and can locomote. A novel mechanical design is described to realize function of autonomous motion and docking. Introducing embedded mechatronics integrated technology, whole actuators, sensors, microprocessors, power and communication unit are embedded in the module. The Sambot is compact and flexble, the overall size is 80×80×102mm. The preliminary self-assembly and self-reconfiguration of Sambot is discussed, and several possible configurations consisting of multiple Sambot are designed in simulation environment. At last, the experiment of self-assembly and self-reconfiguration and locomotion of multiple Sambot has been implemented.

This paper presents an underwater cooperative box-pushing scenario in which three autonomous robotic fish that sense, plan and act on their own move an elongated box from some initial location to a goal location. With the onboard monocular camera, the robotic fish can estimate the pose of the object in the swimming tank. Considering the complexity of the underwater environment and the limited capability of a single robotic fish, we address the task by decomposing it into three subtasks and assigning them to capable robotic fish. With one robotic fish observing the box at the goal location and two robotic fish pushing the left and right ends of the box, the box can be moved gradually towards the goal location. The subtask consists a series of behaviors, each designed to fulfill one step of the subtask. The robotic fish coordinate through explicit communications and distribute the subtasks with a market-based dynamic task allocation method. Task reallocation mechanism that permits robotic fish to auction its assigned task to capable ones is used to cope with unexpected changes in the environment and the limited sensing range of the robotic fish. Experiments are conducted to verify the feasibility of the proposed methods.

Self-assembly is a process during which pre-existing components are autonomously organized into some special patterns or structures without human intervention. In this paper, we propose a new control algorithm on distributed self-assembly which is implemented on the Sambot robot platform. A directional self-assembly control model is proposed, in which a configuration connection state table is used to represent the configuration of the robotic structures composed of multiple Sambots. There are three types of Sambots, docking Sambots, SEED Sambot and Connected Sambots. All docking Sambots adopt behavior-based controller that is independent of target configuration. The SEED Sambot and Connected Sambots are used to implement configuration growth. Self-assembly experiments of snake-like and quadruped configurations are conducted on the Sambot platform with five Sambots. The experimental results show the effectiveness and scalability of the distributed self-assembly algorithm.

Hydrodynamic investigation of carangiform robotic fish has been carried out by using a novel experimental method. The laboratory robotic fish model which follows an exact replica of Saithe, is self-propelled on a servo towing system. The forward towing speed is determined by the fluid force acting upon the robotic fish, as the fish undulate its body in the water. The importance of the self-propelled method which allows for simultaneous measurement of internal and extern force and flow analysis of robotic fish has been demonstrated in the hydrodynamic experiment.

We propose a BEST (Background subtraction and Enhanced camShift Tracking) method for a scout robot tracking a moving object in real time. A modified back subtraction method based on time axis is used to segment the moving object in a complicated environment. The centroid and area are chosen as the feature to judge target. We proposed a novel method that combines Camshift, AWS (Adaptive Window Selecting method) and Kalman predicting algorithm together to track the detected object. Experiments based on a DSP image processing system in a scout robot indicate the feasibility and robustness of our method.

Entry position of the graft is very important in anterior cruciate ligament (ACL) reconstruction. However the determination of entry position is very difficult to the surgeon. In this paper, a navigation and evaluation system assisted by the 6-DOFS robot is implemented for the simulation evaluation and planning insertion points based on quadrant method for the femur and Stäublis method for the tibia on the lateral X-ray image of knee joint. Meanwhile, the implementation of the key technologies such as image correction, image registration, C-arm calibration, video tracking, bone surface reconstruction, image fusion, 6-DOFS robot, and virtual simulation are introduced. Finally, Experiments about the tunnel planning method and real time tracking of surgical apparatus are implemented on 8 bone of plastic models (Sawbone, Swiss) and 10 bones of the goat. In the experiment, the tibia rotates around the femur under the surgeon's implementation to evaluate the planning result with the virtual simulation and evaluation module. The positioning error is 1.59mm from analysis on 30 space targets. The virtual reconstruction ACL is satisfied with two important criteria of the best isometry and collision detection between graft and intercondylar surface of femur. The results are well accepted in operations. In order to satisfying with the request of exact operation in ACL reconstruction, we have developed 6-DOFS passive robot to assist the surgeons entry positioning and drilling of implant tunnels, implementing exact operation in knee joint.

This paper describes the design of a biomimetic inspired fish swimming like UUV based on 2-D ocillating foil machanism which plays guiding role in biomimetic propulsion research field, the relation between vorticity control and motion control parameters for 2-D ocillating foil has been built, a fuzzy logic vorticity controller is designed to achieve straight line maneuverable swimming and thrust efficiency can be ensured at the same time. Experimental result of field test shows that an obiviously improved vehicle performance is obtained. Meanwhile, burst-and-coast manevering is found to be a more effective swimming mode for the vihicle while compared with steady swimming.

Componentization is an important method to improve the reusability of robot software and reduce the difficulty of system design. In this paper, we propose a component based design framework for robot software architecture. First, the robot system is functionally decomposed into reusable components. On this basis, the static model and run-time model of component are established, and a component interface definition language based on the model is designed. Second, a lightweight middleware is proposed according to the communication mode between robot components, and a component development tool and a visual component assembly environment based on the middleware are designed to facilitate the developers. Finally, an application based on the framework is introduced to verify the validation of the design framework.

With the rapid development of robot technology, It is becoming increasingly difficult to design and maintain robot systems. This makes it necessary to reuse hardware and software modules to lower the difficulty and the cost for the robot system design. In this paper we present a model of modular robot-F-Model. It uses functional component modules to construct function-oriented robot applications. Firstly the background of modular robot system is analyzed, and several basic conceptions in F-Model are elaborated. Then, the main framework of the model is constructed, and the model of functional component and its property are introduced to make a more in-depth description of the framework. Finally, the feasibility of F-Model is established by a simple instance.

As a distributed computing system, a CNC system needs to be operated reliably, dependably and safely. How to design reliable and dependable software and perform effective verification for CNC systems becomes an important research problem. In this paper, we propose a new modeling method called TTM/ATRTTL (Timed Transition Models/All-Time Real-Time Temporal Logics) for specifying CNCsystems. TTM/ATRTTL provides full supports for specifying hard real-time and feedback that are needed for modeling CNC systems. We also propose a verification framework with verification rules and theorems and implement it with STeP and SF2STeP. The proposed verification framework can check reliability, dependability and safety of systems specified by our TTM/ATRTTL method. We apply our modeling and verification techniques on an open architecture CNC (OAC) system and conduct comprehensive studies on modeling and verifying a logical controller that is the key part of OAC. The results show that our method can effectively model and verify CNC systems and generate CNC software that can satisfy system requirements in reliability, dependability and safety.

In this paper, we propose to implement hybrid operating systems based on two-level hardware interrupts. To separate real-time and non-real-time hardware interrupts by hardware, we show that it is easier to build up hybrid systems with better performance. We analyze and discuss the key issues for implementing a hybrid system based on this and implement a hybrid system called RTLinux-THIN (Real-Time LINUX with Two-level Hardware Interrupts) on the ARM architecture by combining ARM Linux kernel 2.6.9 and muC/OS-II. We conduct experiments on a set of real application programs including mplayer [20], Bonnie [4] and iperf [13] and compare the interrupt latency distributions for RTLinux-THIN (with and without cache locking), RTAI and Linux on a hardware platform based on Intel PXA270processor [12]. The experimental results show that RTLinux-THIN improves real-time interrupt latencies and provides better predictability.

This paper introduces a workflow for robot assisted neurosurgery. The system consists of a robot for precise positioning and a vision system for intro-operative registration. The vision system uses two cameras and templates to automatically track dynamic targets. In order to accurately position the end of the robot during operation, the robot arm must occupy the least space, be easy to move and be well balanced. Cylindrical configuration is chosen in this case as a suitable type of arm. Based on the Jacobian matrix of robot and the conditioning number of the matrix, the optimal dexterous region of the robot is found to satisfy desired dexterity. The successful clinical application verifies the effectiveness of the robot system

Robot assistant surgical system is currently a research focus. This paper introduces a tele-neurosurgery system joined developed Beihang university and General Navy Hospital of PLA, China. The content describes the system structure, important procedures, modules, safety and convenience consideration. The system has successfully performed three teleneurosurgery operation between Beijing and Yan'an, Shanxi province via public Internet. The experiment results proved the system is feasible, safe and low-cost

The reconfigurable tracked mobile robot was developed for all-terrain recon. Based on the unique characters of reconfigurable robot, modular mechanical and electrical structure and control method were all discussed. The tracked robot was composed of four basic locomotion modules, three joint rods and two rotational articulations. By the different configurations of all the modules, the mechanical reconfiguration of the tracked vehicle was realized. The master-slave control system was adopted. Based on the ARM real time embedded control system, the reconfiguration was realized when the mechanical structure of the robot was reconfigured. The tracked robot was validated that it has the excellent adaptable ability in complex terrain and has easy and simple reconfigurable performance when it executed recon in the building interior simulating the real task

To reduce the yawing, rolling and pitching of the fish robot and to improve the efficiency of tail fin propulsion, the strength environment of the tail fin thruster was analyzed, the fish robot's shape is optimized under a novel design principle, which was abbreviated as SPC (stability first, propulsion second, control third), of bionic fish robot, the result was analyzed by computer fluid dynamics simulation using the lift-drag ratio as the key parameter. The experiments of three fish robots of different scales were done. The biggest one, which was 2m in length, reached the maximal speed of 1.5m/s at the frequency of 1.6Hz. And the yawing of all three fish robots were below 5/spl deg/. The experiments have shown that owing to the improvement of the stabilization the velocity and propulsion efficiency were also improved, and the Strouhal number got into the best region of 0.2-0.3.

Haptic rendering has the potential to increase the quality of human-computer interaction with virtual environment by accommodating the sense of touch. In this paper, a 7 DOF arm type exoskeleton device is designed and implemented. Human user can haptically interact with virtual environment by using this light-weight device. The principles of measuring user's arm motions are presented, which include the dimensional mechanism. The motion of each joint of the proposed haptic device is nearly independent. The virtual contact force is also calculated in real time to meet the stringent requirement of real time haptic rendering. Experiments results show promising feasibility of the arm type exoskeleton device.

This work introduces a robot system for minimally invasive frameless stereotactic neurosurgery. The system consists of a robot arm for precise positioning of surgical tools, a vision system for intro-operative registration, and a preoperative planning system. The robot is a custom designed accurate arm with five degree-of-freedom. The vision system uses two cameras to automatically generate the target position of the robot The robot can be controlled autonomously as well as interactively through an intuitive way. Experiments and clinical trials approve the robot system is effective and powerful.

Telesurgery is an interdisciplinary field of teleoperated robotics and robot-assisted minimally invasive surgery, and has good promising future. In this work, the structure and work flow of the tele-neurosurgery are addressed at first. Then the key technologies involved, including our newly developed surgical robot, untouched methodology in localizing marks for registration, video overlay and surgical simulation, video transmission and network communication, and safeguards, are discussed, which guarantee the safety and feasibility of the clinical telesurgery. In the end, the first remote clinical stereo tactic neurosurgery is presented.

According to the biplanar imaging principle, this paper proposes a novel fluoroscopy-guided robot navigating system for distal locking of intramedullary nails which only needs two X-ray projection images from lateral and AP views of the nail respectively. Error distributions are analyzed based on the mathematical model and the structural model. The system performance is also tested and evaluated through preliminary experiments with plastic bones and cadaver limbs. It is shown that this system has enough positioning accuracy and stability with a compact robot structure, and it can dramatically decrease the operating time. The modular design makes it applicable for most kinds of intramedullary nails existed nowadays.

A computer and robot assisted telesurgical system for stereotactic neurosurgery is presented in this paper. Using the user friendly interface for surgical planning, the surgeons can make the surgical planning on the model reconstructed in the computer, and marker registration is used to create the mapping between the patient's head and the 3D-brain model. When appropriate entrance position on the skull and entrance trajectory are determined through the surgical planning, they are exported to remote physical medical robotic system, via the Internet, for real-world execution. Remote robotic system is not only used as a navigational tool to direct the surgery planning, but also used as an instrument platform to assist surgeons to accomplish the operation. This computer and robot assisted tele-neurosurgery system has been successfully used in clinical application.

The surgical training system presented in this paper provides the surgeon a virtual surgical practice environment for the robot assisted minimally invasive neurosurgery, which includes collision detection, deformation of soft issue and haptic rendering. The 3D model of the brain structure of the patient is reconstructed based on the 2D images. After the virtual robot move to the entrance pose that is planned by the user, it is fixed, and the user can control the virtual needle to insert into the virtual head to verify his planning. During needle insertion, the inner structure of patient head is displayed, and the resistance force between the needle and organs is calculated and reflected to surgeon by haptic device. An improved collision detection scheme is also proposed to meet the need of real time haptic rendering. Using this virtual training system, the surgeon can make virtual neurosurgery to take cost-effective practice and training.

This paper introduces the research project of robot assisted minimally invasive neurosurgery. Using visualization technology, the system reconstructs and displays the 3D model of the patient's inner structure in the computer. Thus the surgeons can plan the surgery on the model in the computer. Marker registration is used to create the mapping between the patient's head and the 3D-brain model. Robot arm is used as a navigator to direct the surgery planning and as an instrument platform to assist surgeons to accomplish the operation. The results of the clinical application are given to show that the robotic system is effective.

This research presents a multi-fingered hand and computer control system intended for research in dextrous manipulation. The hand mechanism is based on an anthropomorphic configuration with four identical fingers. Each finger has four degrees of freedom actuated by four DC servomotors. The fingers, palm and mechanical interface to a robotic arm are separate components of a modular design allowing the hand to be highly dexterous and flexible. Each finger is a compact module with eight position sensors, and all the four actuators are integrated into the mechanical structure of the finger module. Position control has been implemented using a DSP based computer controller. Experimental results validate that the basic functionality and requirements of the hand system were achieved.

Teleoperation is a viable alternative to project a human operator's intelligence into the places that are inaccessible or dangerous to people, or where expertise and resources are not available. Due to the distance between the human operator and remote environment, the human-machine interface is an important component for the overall system performance capabilities and efficiency. The paper proposes a new design method of multimodal interface for teleoperation. A distributed graphic predictive display subsystem based on virtual reality is implemented, and all kinds of feedback information acquired from a remote environment, such as actual live images, audio and force information are organized and presented to human operators in an appropriate, way. Experimental results demonstrate that the multimodal human-machine interface can reduce a human operator's mental workload and facilitate teleoperation. Some key technologies concerned with this multimodal interface, such as the synchronization mechanism of the distributed predictive simulation subsystem and the real time transmission of actual live multimedia via the Internet under narrow bandwidth are also developed.

This system is mainly composed of an industrial robot, dexterous hand (BH-3), graphic simulation and planning module, 6-DOF teleoperated mechanical arm (BH-TMA) and data glove with 5-fingered 11-DOF (BHG-3), etc. It consists of vision, force, torque, fiber, angle, and fingertip tactile sensors. In order to implement some complex operations in the integrated system, we propose a task-oriented hierarchical control share model. Moreover, we also express our viewpoints about share control in the teleoperated system. Finally, the experimental and simulative results are given to show that the share control construction is highly efficiency and effective.

This paper introduces the research on robot assisted, minimally invasive neurosurgery. The prototype system developed is composed of a preoperative image-guided planning, the minimal-invasive and noninvasive calibration between the virtual and actual environments, and a surgical robot for location and remote-controlled procedures based on the preoperative strategy. Finally, results of the clinical application are given to show that the robotic system is effective.

An efficient method is presented for implementing mobile robot perception-action behaviors, based on the time-varying potential field. The concept of dynamic potential is proposed to achieve the control scheme. The scheme was successfully implemented on the THMR-II mobile robot for a variety of applications. The drawbacks of known potential field methods are solved by the composition of the behavior controls. Experimental results based on sonar and vision signals are given to show that the method had good real-time response and adaptability, and was robust in dynamic environments.>