In logistics applications, the vision-based technology for grasping target objects in the air is relatively mature. However, when operating across the air and water such as grasping marine products from the water, the visual information collected by the camera will be disturbed by ripples and bubbles on the water surface, resulting in low grasping efficiency. Therefore, we introduce a grasping strategy based on single-visual mapping for multi-step (SVMMS) strategy to achieve cross-medium operations involving stacked objects. Specifically, we design a multifunctional integrated Deep Q-learning-based network model to extract visual features from the scene to effectively detect stacked objects and outputs their hierarchical relationships. Moreover, we quantify the underlying relationship between motion logic during action execution and changes in RGB-D during action execution to help the robot achieve efficient and collision-free operations. Our approach also incorporates a time-series design with prioritized experience replay to globally optimize the action sequence. Additionally, we propose a novel sim2real method by combining domain randomization to address the difference in object sizes between the simulation and the real world. Extensive experiments in both simulation and physical environments show that SVMMS-Grasp significantly outperforms existing methods in terms of task success rate, stability, and operational efficiency.

To address complex mission tasks, multirotors benefit from in-flight reconfiguration that enhances their morphological adaptability. This paper presents the Center-Driven Scissor Extendable Airframe (CDSEA), a novel one-degree-of-freedom (DOF) morphing airframe designed to replace traditional fixed-size airframes. The CDSEA allows a quadrotor to achieve significant morphological changes during flight, with rotors deploying radially from a central point. This capability facilitates substantial variations in footprint radius and ensures smooth transitions. The paper details the mechanical design, as well as kinematic and dynamic analyses, and discusses the actuator selection strategy for the CDSEA. Experimental results with a prototype demonstrate that the CDSEA achieves a footprint-radius deformation ratio of 2.5 and a morphing time of 0.3 seconds, surpassing existing solutions. Additionally, the design improves obstacle avoidance and wind resistance. These results underscore the CDSEA's potential as an advanced solution for enhancing UAV adaptive navigation performance in complex environments.

High maneuverability is essential to the autonomous operation of underwater robots. To achieve real-time maneuvering motion, the control strategy must take into account nonlinear hydrodynamic effects, which are extremely difficult to accurately capture during motion and therefore a balance must be struck between accuracy and real-time computational efficiency. Therefore, this paper proposes a data-driven approach to model the dynamics of the underwater robot using Sparse Identification of Nonlinear Dynamics (SINDy). Compared with existing works, our method does not require any physical prior knowledge and only uses a short period of onboard sensor data. Subsequently, the learned dynamic model is incorporated into a model predictive controller (MPC) to enable precise attitude control. Finally, the proposed method is implemented on our developed fully vectored propulsion underwater robot, and a series of attitude tracking experiments are conducted in an indoor water tank. Experimental results reveal that our approach significantly improves the model accuracy and reduces the attitude tracking errors by over 79% at a control frequency of 20 Hz, which proves the effectiveness and real-time performance of the method.

Conventional soft sensors often suffer from challenges such as crosstalk, hysteresis, and limited sensitivity, which hinder their performance and broader applicability. This paper presents a multi-axis piezoresistive soft force sensor with a square-column-shaped sensing structure designed to reduce the spatial footprint and mitigate partial axial coupling effects. By integrating a Wheatstone bridge-based resistive compensation strategy, the sensor achieves self-decoupling in multi-axis force measurements. Furthermore, a generalized Preisach hysteresis model is implemented to effectively compensate for hysteresis-induced nonlinearities and input-output loop effects, significantly enhancing sensing accuracy and precision. Extensive experimental validations confirm the effectiveness of the proposed self-decoupling and hysteresis compensation methodologies, demonstrating notable improvements in sensor reliability and performance. The findings of this study establish a comprehensive framework for advancing multi-dimensional soft force sensing technologies, with promising implications for high-precision engineering and biomedical applications.

This paper presents a rapid 3D printing framework that enhances the efficiency of commercially available layered manufacturing-based 3D printers. Unlike traditional methods that simplify printing regions to a single point or rely on predefined entry and exit points, our approach utilizes an improved Traveling Salesman Problem (TSP) algorithm to autonomously generate an optimized, cyclic printing path, while automatically assigning entry and exit points for each region. This minimizes non-printing paths and improves efficiency. Additionally, we propose a principal axis calculation method for irregular shapes, aligning better with geometric orientation. This optimization enhances infill uniformity and surface smoothness. Simulations and experimental results demonstrate that the proposed framework improves printing efficiency while maintaining print quality, with promising applicability to large-scale and complex 3D printing models.

This paper addresses the consensus issue of multiagent systems with both input amplitude and rate constraints. We propose simple yet effective distributed control algorithms that integrate a velocity damping term with nonlinear saturated functions for both undirected and directed graphs. Leveraging the interplay between Barbalat’s lemma and graph theory, we show that all agents can achieve consensus without violating predefined input amplitude and rate constraints through the presented control algorithms. Moreover, we employ the developed framework to solve the rendezvous control problem of quadrotor unmanned aerial vehicles (UAVs) with motion limits. To illustrate and validate our proposed approach, we conduct extensive simulations and comparative experiments. Note to Practitioners—Most existing control methods for multiagent systems achieve consensus but neglect the constraints on the amplitude and rate of the control signal. However, in practice, the control signals are invariably subject to limitations in their amplitude and rate due to factors such as actuator saturation, considerations for ride comfort, and actuator wear. This neglect leads to a degradation in system performance and in severe cases results in the loss of closed-loop stability. This work primarily focuses on developing new control methods that can achieve consensus without violating the predefined input amplitude and rate limitations. The experiments on rendezvous control of quadrotor UAVs show the practical applicability of the presented algorithms, which yield satisfactory control performance as verified by theoretical analysis. This research contributes to the advancement of distributed control for multiagent systems, particularly in scenarios where input constraints are a critical consideration.

Morphing quadrotors that can be potentially applied to confined spaces such as warehouses, tanks, and pipelines have flourished in recent years. Most work has focused on the mechanical feasibility of the morphing systems and high-level flight controller design, with limited discussions on low-level control. In this paper, a constrained model predictive control (MPC) is proposed and applied to solve the attitude control problem of a morphing quadrotor. Prior to controller design, a custom-built morphing quadrotor is introduced with the kinematic and dynamic models established and corresponding issues and challenges presented. In the controller, to eliminate the steady-state error, an embedded integrator is adopted by exploiting the differential variables; then, the constraints of the morphing quadrotor are incorporated into the MPC formulation to simulate real flight conditions, and an orthonormal function is employed to approximate the control input sequences in the controller to alleviate the computational burden. In the comparative studies, several scenarios are considered to demonstrate the effectiveness of the proposed control strategy in attitude control.

Due to the low motion efficiency and maneuver-ability of underwater robots with six degrees of freedom, it is challenging for them to respond quickly to the attitude requirements during underwater autonomous manipulation. This paper presents a novel autonomous underwater robot with fully vectored propulsion and a model predictive control method to achieve more agile and efficient movements autonomously. In detail, we first design a robot with eight vector-distributed thruster layouts for fully vectored propulsion and construct the software architecture based on the robot operating system (ROS). Then, we establish the hydrodynamic model by adopting the Fossen approach and construct a 13-dimensional system state-space equation, which is discretized using the explicit fourth-order Runge-Kutta method. To achieve autonomous manipulation, model predictive control is employed along with physical constraints of the custom-built robot to enable real-time prediction and optimization of the robot’s states for control purposes. Finally, numerical simulations and experiments of the Point-to-Point Motion are conducted to test the robot’s performance. Experimental results reveal that the average error of each direction is 0.0027 m, 0.0031 m, and 0.0368 m in the x-axis, y-axis, and z-axis, respectively, and 0.8502°, 2.1941°, 0.2408° corresponding to three attitude angles, which verify the performance of employing MPC to control an autonomous underwater robot with fully vectored propulsion.

The work in this paper delves into the challenge of whole elongated body's obstacle avoidance during path following for a class of bionic snake robots. Currently, most studies focus solely on preventing the robot's head from colliding with obstacles through designed controllers. However, due to the unique elongated structure and biomimetic locomotion modes of snake robots, it is unavoidable that the rest of the robot's body could still collide with obstacles. To resolve this problem, we propose a novel real-time optimization obstacle avoidance strategy for a class of terrestrial snake robots with multi-link elongated body using model predictive control (MPC). Moreover, by leveraging the elongated body characteristics of the robot, an improved path guidance strategy is also developed. The effectiveness of the proposed strategies is verified and validated through extensive simulations and experiments on a custom-built nine-link elongated snake robot. The results demonstrate that all links of the robot can well avoid obstacles while continuing to track the given path.

This article studies the tracking control of a quadrotor unmanned aerial vehicle (UAV) under time-varying external disturbances. An event-triggered sliding mode control (SMC) strategy is proposed by introducing a new triggering condition form of desired trajectory, quadrotor position, and velocity. In the sense of Lyapunov theory, the stability of the entire closed-loop control system is analyzed, and it is proved that the tracking error is adjusted to an adjustable set around zero. We show that the Zeno phenomenon can be avoided; that is, a positive minimum inter-event time is assured. One of the salient features of the proposed strategy is that it can reduce the update frequency of the control efforts, thereby ensuring desirable tracking performance under limited communication bandwidth. Comparative simulation and experimental results are provided to show the efficacy of our framework.

In this paper, to achieve the goal of aiding the blind and visually impaired (BVI) to read any text not written in Braille, a custom-built, finger-wearable, and electro-tactile based Braille reading system with its Rapid Optical Character Recognition (R-OCR) method is developed. The R-OCR is capable of processing text information in real time using a miniature fish-eye imaging device mounted at the finger-wearable system. This allows real-time translation of printed text to electro-Braille along with natural movement of user's fingertip as if reading any Braille sign or book. An electro-tactile neuro-stimulation feedback mechanism is further proposed and incorporated with the reading system, which facilitates a new opto-electrotactile-feedback-based text line tracking control approach that enables text line following by user's fingertip during reading. Extensive experiments were designed and conducted to test the ability of blindfolded participants to read through and follow the printed text lines based on this optoelectrotactile-feedback method. The experimental results show that as the outcome of the opto-electrotactile-feedback, the users who involved in the feedback loop were able to maintain their fingertips within a$2mm$distance of the text while “reading” through a printed text line. Our work is a significant step to aid the BVI users with a portable means to read any printed texts to Braille through the following and the translation, whether in the digital realm or physically, on any surface.

This paper presents our comparative study on how the flight performances of an in-flight morphing quad-rotor are affected by the morph induced inertia variation. A custom-built in-flight morphing quad-rotor was employed in numerical and experimental tests for the study and analysis. In these tests, the quad-rotor is controlled to follow a predefined path and/or to hover in an environment with the constant wind disturbance. Our numerical results indicate that the morphing-size-down quad-rotor exhibits more agile in flight attributed to the compact volume/size, while the big-size one shows more flight stability in a disturbed and windy environment. Compared to regular scaled aerial vehicles whose volume/size changes follow a weight change proportionally, the numerical results reveal that our morphing quad-rotor that changes its volume with identical mass can acquire more merits towards high flight performances. Experimental validations further prove that through adaptatively transform its size in a complex and constrained environment, the in-flight morphing quad-rotor is not only capable of well performing path following tasks when encountering obstacles on the path or nearby the path, but also enhances the flight performance of withstanding external torques by extending its size so as to increase its moment-of-inertia. In summary, our in-flight morphing quad-rotor can acquire higher flight performances by adaptatively morphing when flying in complex environments.

In this paper, we investigate the consensus problem of multiple unmanned aerial vehicles (UAVs) in the presence of environmental constraints under a general communication topology containing a directed spanning tree. First, based on a position transformation function, we propose a novel dynamic reference position and yaw angle for each UAV to cope with both the asymmetric topology and the constraints. Then, the backstepping-like design methodology is presented to derive a local tracking controller for each UAV such that its position and yaw angle can converge to the reference ones. The proposed protocol is distributed in the sense that, the input update of each UAV dynamically relies only on local state information from its neighborhood set and the constraints, and it does not require any additional centralized information. It is demonstrated that under the proposed protocol, all UAVs reach consensus without violation of the environmental constraints. Finally, simulation and experimental results are provided to demonstrate the performance of the protocol.

This paper focuses on designing, modeling and validating a novel scalable multicopter whose deformation mechanism, called SNIAE-SSE, relies on a combination of simple non-intersecting angulated elements (SNIAEs) and straight scissor-like elements (SSEs). The proposed SNIAE-SSE mechanism has the advantages of single degree-of-freedom, fast actuation capability and large deformation ratio. In this work, enabled by the SNIAE-SSE mechanism, a quadcopter prototype with symmetrical and synchronous deformation is firstly developed, which facilitates a novel and controllably scalable multicopter system for us to analyze its modeling, as well as to validate its flight performance and dynamics during the deformation in several flight missions including hover, throwing, and morphing flying through a narrow window. Experimental results demonstrate that the developed scalable multicopter can maintain its stable flight behavior even both the folding and unfolding body deformations are fast performed, which indicates an excellent capability of the scalable multicopter to rapidly adapt to complex and dynamically changed environments.

In this paper, we investigate the perception-aware path finding, planning and following for a class of snake robots autonomously serpentining in an unmodeled and unknown environment. In the work, the onboard LiDAR sensor mounted on the head of the snake robot is utilized to reconstruct the local environment, by which and the modified rapidly-exploring random tree method, a feasible path from the current position of the robot to a local selected target position can be obtained. Next, the parametric cubic spline interpolation path-planning method and potential functions are applied to make the path more smooth so as to prevent the multi-link and elongated robot body from hitting obstacles. To steer, a time-varying line-of-sight control law is designed to ensure that the robot moves to the local target position along the generated path by the perception-aware method. The robot will repeatedly perform the above search-find-move strategy until it reaches the final predefined target point. Simulation and experimental results demonstrate a good performance of the proposed perception-aware approach, that is, the elongated and underactuated snake robot is capable of autonomously navigating in an unknown environment.

This paper investigates the curve path following problem for a class of planar underactuated bio-inspired snake robots. The time-varying line-of-sight (LOS) guidance law and the cubic spline interpolation (CSI) path-planning method are employed. Existing studies focus on straight line path following which only gives a solution for snake robot motion control in relatively simple environments. Considering the snake robot's many degrees of freedom and excellent mobility in terrains, we propose a more applicable solution of curve path following for snake robots on the ground. The improved LOS helps the snake robot to steer aggressively at a sharp turning point. Furthermore, to avoid the sideslip of the snake robot caused by the ground friction change, an integral controller is introduced in the design of the heading reference. Simulations and experiments on an 8-link custom-built snake robot are conducted and the results demonstrate and validate the effectiveness of the proposed curve path following algorithm.

In this paper, a simple tracking control scheme is proposed for quadrotor systems with uncertain dynamics. It precludes the necessity for prohibitive analytic computation of the derivatives of the desired (virtual) attitude that is typically employed in controlling quadrotor systems. Moreover, this control scheme is approximation-free in the sense that it does not incorporate any adaptive laws, observers, or command filters to compensate for unknown parameters in the dynamics and the absence of the analytic differentiation, thus exhibiting remarkably low complexity levels and making its implementation straightforward. The thrust saturation is approached in the position control design which also enables the singularity in desired attitude extraction to be avoided entirely. It is demonstrated that based on the proposed scheme, the tracking errors can be made arbitrarily small by appropriately selecting design parameters. Extensive simulations and experiments are performed to verify the effectiveness of our scheme.

This study is designed to validate the feasibility of generating identifiable moving patterns using electro-tactile stimulation. An electro-tactile display is built using an array of 16 contacts to deliver the electrical signal to the fingertip skin. This signal can have varying voltages, frequencies or duty cycles to form the most comfortable sensation. Moving patterns can be generated by individually or collectively switching on or off the contacts on the display. This is done to stimulate a moving pattern. In this case, a moving pattern is comparable to a group of frame-by-frame pictures constructing a movie. Similarly, by toggling the contacts in a specific order, a moving pattern can be achieved. A program on a single-board computer (Raspberry Pi) was used to control and generate 6 different patterns. These patterns are delivered to the display and consequently to the fingertip skin of the participants. A total of 8 subjects participated in this study. They filled a questionnaire to indicate the corresponding movement. The results of these experiments were analyzed and a conclusion regarding the direction of the movement was drawn. It became clear that the direction of the movement had a significant impact on the recognition of the patterns.

Inspired by the inchworm locomotion mechanism, this paper presents our recently developed self-deformable capsule-like robot. The robot has the actuated deformation capability that relies on a novel rigid elements-based morphing structure (REMS) and its soft actuation mechanisms. When the robot deforms, it generates the crawling locomotion behavior and thus friction waves between the robot and contact surface to facilitate the inchworm-like crawling movement. The paper starts reviewing the deformable properties of natural biological entities like capsules, presents state of the art of the current capsule-like robots, and details the bio-inspired design of the self-deformable capsule-like robot by describing the model of robot kinematics and its locomotion mechanism. Both simulation and experimental results validate the excellent performance of this capsule-like robot. The developed self-deformable capsule-like robot has the advantage of crawling on varied surfaces and it also has the capabilities to crawl in a variety of narrow pipes based on the deformation elicited locomotion nature of the robot.

This paper investigates the straight path following problem for a class of underactuated bio-inspired snake robots on ground with unknown and varied friction coefficients. Existing works usually design control input requiring the exact values of these friction coefficients, which however rely on the specific operating terrain and may not always be known a priori. By virtue of backstepping technique, we present a novel adaptive controller that can compensate for unknown and varied friction coefficients in real-time. Moreover, it is proved via LaSalle-Yoshizawa theorem that the path following errors converge to zero asymptotically and all the parameter estimates are bounded. Simulations and experiments on an 8-link snake robot are carried out to illustrate the effectiveness of the proposed controller.

The paper presents the development of a novel deformable quad-rotor enabled aerial gripper. The mechanism of our deformable quad-rotor is based on simultaneous expansion or contraction of the quad-rotor body, which is generated by controlling a rigid elements based morphing structure (REMS). Such deformation results in a highly deformable quad-rotor that can not only perform morphological adaptation in response to environmental changes and obstacles, but also improve the flight performance by contracting to facilitate the agility/maneuverability or by expanding to enhance the stability. Meanwhile, inspired by the wasp grasping behavior, such controllable expansion and contraction from the REMS ingeniously enable a new function of aerial gripper. In this paper, we start to detail the mechanism and design of the REMS based deformable quad-rotor, then present the quad-rotor deformation enabled aerial gripper design, its dynamics modeling, the grasping function and analysis. The simulation was conducted in order to graphically show the elicited aerodynamic flow situation during expansion or contraction of the quad-rotor with and without carrying payload. Experiments were further implemented to validate the grasping function of the gripper and the flight performance of the quad-rotor. Finally, two case studies on the new aerial gripper were performed. All results demonstrate the excellent performance of the deformable quad-rotor enabled aerial gripper, that is, it has the advantages of both flight maneuverability and grasping capability during performing tasks.

Inspired by natural earthworm locomotion behavior and segmental muscle motion mechanism, this paper presents our recently developed compliant modular earthwormlike robot with the novel segmental muscle-mimetic design unit that is capable of efficiently mimicking earthworms' segmental muscle contraction and extension functions. The new class of segmental muscle-mimetic design unit relies on the curvature of scissor mechanisms that can be extended and contracted smoothly through controlled servo motors. The paper starts reviewing natural earthworm locomotion behavior, details the bio-inspired concept and design of both the segmental muscle-mimetic unit and the multi-segment earthworm-like robot prototype, and then presents the robot's locomotion models and analysis of the locomotion efficiency of the robot. Simulation and experimental results validate that both the design and the prototyped multi-segment earthworm-like robot have the excellent performance such as its muscle-like contractions behavior, peristaltic locomotion behavior, and highly competitive moving speed.

To improve the obstacle surmounting performance of the quad-rotor vehicle, this paper focuses on designing, kinematically and dynamically characterizing a novel deformable quad-rotor that is based on the scissor-like foldable structures. The foldable structure allows that the volume of the quad-rotor can be tuned to dynamically adapt variously sized obstacles and small spaces. To generate the controllable deformation, the actuated angulated elements that are the essential components of the scissor-like foldable structure play an important role. The element design, its actuation mechanism and the corresponding configuration patterns for the new quad-rotor are presented in the paper in detail. The simulations on deformation properties and obstacle surmounting ability are then performed to verify the deformation capability of the structure. In addition, experiments were extensively conducted to test the controlled deformation of the structure as well to investigate the deformation induced effects to the activated quad-rotor airframe and its aerodynamics. All implementation results validate the effectiveness of the proposed deformable quad-rotor design, that is, it enables the new quad-rotor having excellent obstacle surmounting performance, adaptability, flight maneuverability, as well as minimal aerodynamics influences during deforming.

A pixel-by-pixel scanning that is usually performed by a single point-like sensor or probe is being widely used in the applications such as scanning probe microscopy techniques. Typically, their scanning time is several seconds to minutes long due to a raster scanning that needs to be conducted for capturing every single point on the surface of the sample area. To improve the scanning efficiency, recent research has been focused on investigating effective scanning patterns and methods. This work presents an adaptive local scanning method for efficiently sampling indiscrete objects like string-like one-piece connected objects under the microscopy. An initial scanning pattern is firstly investigated. Once the initial scanning reaches the object, an adaptive sinusoidal scanning method that can on-line adjust its scanning frequency and amplitude by predicting both the curvatures and the shape of the object is employed. The method also addresses scanning intersections and bifurcations associated with objects. Based on extensive implementations, it is validated that our method has high performance as it has high scanning efficiency and the scanned results match objects with high precision and high accuracy.

In this paper, we focus on developing a new constant-voltage-driver (CVD) based electrotactile display system. The system owns the feature of on-line identifying the bio-impedance parameters of fingertip skin for individual tactile preference tuning and haptic rendering enhancement. The identification method relies on a discrete-time extended least squares (ELS) iterative approach with forgetting factor (FF), which serves as an adaptive law to on-line estimate parameters of the first-order bio-impedance model of fingertip skin when the stimulation current control is performing in z-domain. Experimental results demonstrate the performance of the developed CVD electrotactile display, as well verify the effectiveness of the proposed on-line identification method. That is, it is capable of quickly estimating parameters of the fingertip skin bio-impedance model. The significance of our work is that it will greatly improve the tactile/haptic rendering performance of electrical stimulation (electrotactile) systems and benefits the development of electrotactile based haptic rendering devices and applications.

We address the general object tracking with arbitrary shape using rangefinders, which is a key module for detecting surrounding traffic and infrastructure for an autonomous driving vehicle. An Expectation-Maximization (EM) algorithm with locally matching is proposed for motion estimation between two consecutive range images. The complexity of the algorithm is O(N) with N the numbers of scan points. Quantitative performance evaluation of the algorithm using a benchmarking vehicular data set. Results of road tests show the effectiveness and efficiency of the implemented system.

This paper presents our recently developed humanoid neck system that can effectively mimic motion of human neck with very low motion noises. The feature of low motion noises allows our system to work like a real human head/neck. Thus the level of acoustic noises from wearable equipments, such as donning respirators or chemical-resistant jackets, induced by human head motion can be simulated and investigated using such a system. The objective of this investigation is to facilitate using head-worn communication devices for the person who wears the protective equipment/uniform that usually produces communication-noise when the head/neck moves. Our low motion-noise humanoid neck system is based on the spring structure, which can generate 1 Degree of Freedom (DOF) jaw movement and 3DOF neck movement. To guarantee the low-noise feature, no noise-makers like gear and electro-driven parts are embedded in the head/neck structure. Instead, the motions are driven by seven cables, and the actuators pulling the cables are sealed in a sound insulation box. Furthermore, statics analysis of the system has been processed completely. Experimental results validate the analysis, and clearly show that the head/neck system can greatly mimic the motions of human head with an A-weighted noise level of 30 dB or below.

Research in rehabilitation engineering shows that electrodes can produce tactile sensations with appropriate electrical signals tailored to stimulate the multiple tactile receptors located under the fingertip skin. However, electrical stimulation that is suitable in terms of current or voltage level for tactile sensations experienced from an individual cannot be guaranteed for every user; the dynamic range is largely dependent on the user. An identification method is then necessary for characterizing the parameters of the skin-electrode interface circuit model as to improve rendering consistency and comfort for every user regardless of skin condition. In this paper, we focus on developing a custom-built electro-tactile display terminal for data collection and an identification method to determine the individual bio-impedance parameters based on the well-known skin-electrode interface circuit model: the Cole-Cole circuit model. The goal of this work is to develop an online identification and stimulation current control approach for enhancement of electro-tactile-based rendering in applications such as rehabilitation, sensory substitution, telepresence, etc.

In this paper, we present a new mathematical model for designing micro electrode geometry and electric field for carbon nanotubes application. The micro electrode design is based on the assumption that the electrical potential at any point (x,y,z) created by a micro electrode of interest is defined by a polynomial that obeys Laplacepsilas equation. By substituting this polynomial into Laplacepsilas equation the corresponding equipotentials can therefore be determined, and these in turn can be used to define the required micro electrode boundaries for use in carbon nanotube deposition, manipulation, and implementation using dielectrophoresis for electronics and sensing application. Simulation and preliminary experimental results are presented for the developed models.

This paper introduces our recently developed high precision robot localization system employing position sensitive detectors (PSD). A lateral effect PSD is an ideal position sensitive device with a resolution of approx. 0.5 mum. Such a device can be used to enhance the precision capabilities of robot localization or robot calibration. The developed PSD guided localization system is comprised of a structured laser pointer system attached to the robot end-effector and a PSD fixture. It is capable of feeding back the movement information of the TCP relative to the PSD frame. This is achieved by detecting the position of the laser beams emitted from the laser pointers onto the PSD surface. The system was well designed, mapped, and constructed and hence allows it to perform precision localization of the robot. Simulations and preliminary experiments demonstrated the effectiveness of the developed PSD guided localization system including hardware, software, and algorithms. Therefore, it is capable of improving the localization performance of robots as well as promoting the application of precision robot calibration.

This paper presents a novel automated manufacturing process for mass production of nano devices from advanced material such as carbon nanotubes (CNTs). CNTs have been found to be a promising and advanced material for nanoelectronics due to their size and excellent mechanical and electrical properties. Conventional electronic devices replaced by CNT are possibly to be miniaturized, and CNT based nano devices can provide better performance. Therefore, researchers have focused on developing different methods to manufacture CNT based nano devices in recent years. Since the size of CNTs is in nano scale, traditional robotic manipulation cannot be applied. Electrical assembly of CNT based devices is one of the promising methods to manipulate CNT to desired position. Building nano device by a single CNT is challenging, therefore, most people have concentrated on manipulating bundled CNTs. However, the electrical properties of bundled CNTs are difficult to control. As a result, device cannot benefit from quantum properties of a single CNT. Therefore, an automated process for manufacturing single CNT based nano devices is necessary for this application. A CNT deposition system is developed to manipulate a single CNT across microelectrodes precisely and repeatedly by using dielectrophoresis (DEP). Moreover, certain types of CNTs can be selected by using a micro chamber to filter other unnecessary types of CNTs. The system can potentially be used to fabricate an array of CNT based devices, and a fast and feasible batch nano assembly of consistent nano devices can be achieved.

Carbon nanotubes (CNTs) are good candidates for many electronics and sensing applications. These applications will require moving (deposit) and orienting carbon nanotubes to specific location, and separating CNTs with semiconducting and metallic band structure. In this paper, a new mathematical model describing precisely the rotational motion of carbon nanotubes in viscous medium (acetone) is presented. This new mathematical model correctly assumes that carbon nanotubes form a line shape after undergoing AC electric field compare to existing model that assumes carbon nanotubes to be a spherical particle. The new mathematical model is based on a newly developed model for applied torque due to electrorotation. It is also a method for controlled assembly of the CNTs on microstructures that have the plausibility to be scaled to wafer- level manufacturing. Simulation results are presented for the developed models. The developed model can be used to detect the position of carbon nanotubes and further implemented in the separation of semiconducting and metallic band structure carbon nanotubes.

This paper presents our development of a network-enabled human/robot cooperative interface for tele- diagnostics of breast pathology. To enhance telepresence capabilities, our human/robot interface is comprised of an anthropomorphic arm/hand equipped with haptic and tactile sensing, ultrasound imaging capabilities, a physician interface capable of rendering both haptic and tactile information, and two-way audio and video. This cooperative and multimedia interface was tested via the Internet and enables tele-diagnostics. Preliminary experiments had demonstrated the effectiveness of the developed human/robot tele-diagnostic interface. That is, it will greatly enhance and improve the diagnostic performance as well as promote the tele-diagnostics of breast pathology in remote areas a reality.

A robotic device with haptic, tactile, and ultrasound capabilities, which can acquire and render information of breast pathology was developed. A physician interface that can examine the human breast remotely and accurately, using such a robotic device was also developed. Such a robotic device can be used to do screening or focused breast exams for patients in remote areas without convenient access to physicians. Because of in-situ ultrasound imaging, examination by the robotic device may prove to be more accurate than examination by the physicians own hand. In addition, the robotic device can also be used to train healthcare professionals in breast pathology

In this paper, a new pneumatic end effector system for micro/nano fluidic handling, nanomanufacturing, and micro/nano manipulation is presented. The new micro pneumatic end-effector system consists of a DC micro-diaphragm pump and compressor, one region of flexible latex tube, a Polyvinylidene Fluoride (PVDF) sensor for in-situ measurement of micro force, and a micro steel tip. The micro steel tip of the new pneumatic end effector system has an internal diameter (ID) of 20 mum used for handling nano entities such as carbon nanotubes, DNA, micro/nano particles as well as for microfluidic handling and droplet control. The DC micro-diaphragm pump is automatically controlled via a voltage driver interfaced with a computer in order to effectively and efficiently control suction force and pressure during microfluidic handling and droplet control in nano manufacturing. The new pneumatic end effector system with force sensing can significantly improve the success rate for handling/depositing micro/nano entities in the case of carbon nanotubes. The experimental results show the success rate of placing carbon nanotubes between electrodes can reach close to 80%. Ultimately, the technology will provide a critical and major step towards the development of automated manufacturing process for batch assembly of micro devices, manufacturing of nano devices, microfluidic droplet control, and drug delivery

This paper presents the development of a tactile-haptic interface for quantifying surface texture properties such as roughness, veins, and softness of automobile interior. This interface will assist the designer to quantify and classify the comfort index of automobile interior design for quality control, as well as provide customers a sensory experience of surface textures so as to determine the desired surface characteristics for each individual customer. To realize this purpose, a high resolution optical tactile sensor for accurately capturing interior surface textures is developed. Based on the intensity information of the achieved 2-D tactile image, the contact area map and the 3-D shape of the surface texture is recovered. In addition, a high performance haptic electrotactile array device was fabricated for rendering the tactile sensation of surface texture in the fingertip of the designer/customer. Calibration and experimental results verified the high performance of the developed tactile haptic interface. This interface can be further developed to be an effective and efficient knowledge based evaluation system for improving automobile interior design

This paper aims at investigating and characterizing force behavior and mechanical properties of living drosophila embryos using an in situ modeled PVDF (polyvinylidene fluoride) piezoelectric microforce sensing tool with a resolution in the range of sub-muN. Drosophila embryo is one of the most studied organisms in biological research, medical research, genetics and developmental biology, and has implications in the cure of human diseases. In order to achieve high efficiency and accuracy during microinjection of genetic material into a drosophila embryo, it is absolutely necessary to allow close monitoring of the magnitude and direction of microinjection forces acting on the embryo during injection. In this paper, a microrobotic biomanipulation platform integrating a two-axis (2-D) modeled PVDF micro-force sensor is used to implement force sensing during microinjection of living drosophila embryos. Micro injection forces and membrane deformation of embryos in different stages of embryogenesis are found. Ultimately, the technology will provide a critical and major step towards the development of automated biomanipuation for batch microinjection of living embryos in genetics

Structural health monitoring and inspection is very important for many civil, mechanical and aerospace systems. It is a critical step in maintaining and improving the structural integrity of these systems. In this paper, we propose to develop an automated, intelligent inspection system for these engineered structures, which employs a team of intelligent climbing robots and a command robot to collaboratively carry out the inspection task. To support autonomous navigation, a Miniature Active Camera (MaCam) module is designed, which can be used in the pose calibration of the robot. The robot pose error model is introduced. Based on that, the path planning problem for a single robot is studied and a hierarchical algorithm is developed to generate a path that satisfies the navigation requirements of the robot. Both the error model and the path planning algorithm is verified in experiments.

So far, in-situ PVDF (polyvinylidene fluoride) films bonded to the surface of flexible cantilever structure act as the micro-force sensors, they are mostly modelled using quasi-static relationships. However, such sensors are usually a significantly compliant and easily deformable structure in order to reach highly sensitive performance in micromanipulation. As a result, this may be reasonable to consider bandwidth measurement and high frequency response for achievement of high accuracy, and thus a dynamic analysis of such sensors become essentially necessary. In this paper, a cantilever beam based micro-force sensor was designed based on the infinite dimensional system model (distributed parameter model) using the Bernouli-Euler formulation. Furthermore, in order to enable an engineering implementation, we used a zero frequency term to effectively replace the high order modes of the dynamic sensing model in the prescribed frequency range. The corrected model can efficiently minimize the effect of removed higher order modes, and then the micro-force measurement can be obtained accurately with this corrected in-bandwidth dynamic model. Preliminary simulation and experimental results both verified the performance of the developed dynamic micro-force sensor and the effectiveness of the corrected model.

This paper aims at developing an active force sensing technology for micromanipulation and microassembly using in-situ piezoelectric polyvinylidene fluoride (PVDF) films symmetrically bonded to the surface of a flexible cantilever beam structure. The designed micro-force sensing beam has both sensing and actuating layers. The sensing layer can detect the deformation signal due to the external micro-force acting at the sensor tip, the signal is then fed back to the actuating layer through a servoed transfer function or servo controller, as a result, a counteracting bending moment generated by the actuating layer can be used to balance the deformation of sensor beam in real time. Once balanced, the sensor tip will maintain in the equilibrium position as if the sensor stiffness is virtually improved, yielding accurate motion control of the sensor tip. Especially, the micro-force can be obtained by calculating the balance force through the counteracting servo voltage applied to the actuating layer. The developed active structure greatly enlarge dynamic range of micro-force sensor and enhance the manipulability during micromanipulation/microassembly when the sensor is mounted at the end-effector. Preliminary calibration and experimental results both verified the performance of the developed active micro-force sensor and the effectiveness of the models.

This paper aims at developing a force-guided micromanipulation technology with in-situ PVDF beam force sensing and hybrid force/position control based on an infinite dimensional system model. By using the designed PVDF force sensing cantilever composite structure with high sensitivity, the micro contact force/impact signal and its derivative can be extracted and processed. As the sensor structure installed at the end of micromanipulator is a soft beam, when manipulation is performed, the cantilever beam is necessary to be considered as a distributed parameter flexible link, then we developed a hybrid micro contact force/position control scheme on the basis of an infinite dimension system model. Experimental results verify the performance of the developed micro force sensing and hybrid control scheme. Ultimately the technology will provide a critical and major step towards the development of automated manufacturing processes for batch assembly of micro devices.

This paper aims at advancing micromanipulation technology with in situ polyvinylidene fluoride (PVDF) piezoelectric force sensing during microassembly and packaging process. Based on the previously developed PVDF 1-D sensor, by employing the parallel beam structure, a novel 2-D force sensor with relatively high natural frequency and sensitivity is optimally designed. The sensor can detect micro force and force rate signals, which can be fed back so as to greatly, improve the reliability of microassembly. Preliminary calibration and experimental results on assembly of surface MEMS devices both verified the performance of the new 2-D sensor that demonstrates a high sensitivity and a resolution in the range of /spl mu/N. Ultimately the technology would provide a critical and major step towards the development of automated micro-manufacturing processes for batch assembly of micro devices.

This paper aims at developing the force-guided microassembly technology with in-situ PVDF piezoelectric force sensing and control. By using the designed force sensors with the effective signal processing techniques, the micro contact force/impact signal and its derivative can be extracted and processed. Furthermore, based on a new sensor-referenced control scheme, micro mirrors can be reliably assembled by regulating the micro contact force. Experimental results verify the performance of the developed micro force sensing and control system. Ultimately the technology will provide a critical and major step towards the development of automated manufacturing processes for batch assembly of micro devices.

This paper addresses visual servoing of a robot manipulator with uncalibrated intrinsic and extrinsic parameters of the vision system and unknown physical parameters of the manipulator. A novel sliding mode visual feedback scheme is proposed to solve the problem of the robust trajectory tracking of a planar manipulator in the image frame without calibrating the camera parameters. The controller does not use visual velocity so as to achieve high and robust performance with low sampling rate of the vision system. It is proved by Lyapunov direct method that the tracking error of the robot converges to an arbitrarily small neighborhood of zero. The simulation is included to demonstrate the effectiveness of the controller proposed.

The calibration accuracy of the intrinsic and extrinsic parameters of the vision system greatly affects the performance of visual servoing. We address the problem of controlling a planar manipulator using a fixed single camera without calibrating its intrinsic parameters and the transformation matrix between the robot base frame and the camera frame, and without measuring manipulator's depth. Based on an important observation that the unknown parameters can be separated from the unknown composite image Jacobian matrix, we propose an adaptive algorithm to estimate the unknown and mixed parameters on-line. It is proved with a full consideration of dynamics of the system by Lyapunov approach that the feature points of planar manipulator approach asymptotically to the desired ones on image plane and the estimated parameters are bounded under the control of the proposed visual servo controller. The performance has been confirmed by simulations and experiments.

For the visual servoing tasks, it is required to calibrate accurately the homogeneous transformation matrix between the robot base frame and vision frame besides the intrinsic parameters of the vision system. In this paper, based on an important observation, that is, the unknown transformation matrix between the robot base frame and vision frame can be separated from the visual Jacobian matrix, and by virtue of decomposition of rotation matrix, we design a novel adaptive position-based visual servo controller for manipulators when the transformation matrix is not calibrated. It is proved with a full dynamics of the system by the Lyapunov approach that the motion of the manipulator approaches asymptotically to the desired trajectory. Simulations and experimental results both demonstrate the performance of this new controller.

The paper proposes a new haptic system for the pulse palpation via the Internet for remote diagnosis of patients without time and space restrictions. First, we design a pulse-detect sensor to obtains the pulse signals from the patient's wrist. Next, a server-client process is developed to transfer the pulse signals to the remote computer. Then, a haptic device is used to provide an interface for the doctor to feel the pulses of the patient at a remote distance. The haptic device regenerates the pulse signals by a motor-controlled cam system. To couple the doctor with the remote environment and give him a sense of telepresence, a trajectory follower is implemented: the cam follower moves up and down in accordance with the desired pulse trajectory. In addition, by considering the system as a one-dimensional manipulator, a PID force controller is realized to trace the desired force obtained from pressure sensors on the patient's side. As a result, the force felt by the doctor from the haptic device is closed to that he/she would feel from the patient's wrist directly.

To implement a visual feedback controller, it is necessary to calibrate the homogeneous transformation matrix between the robot base frame and the vision frame besides the intrinsic parameters of the vision system. The calibration accuracy greatly affects the control performance. In this paper, we address the problem of controlling a robot manipulator using visual feedback without calibrating the transformation matrix. We propose an adaptive algorithm to estimate the unknown matrix online. It is proved by the Lyapunov method that the robot motion approaches asymptotically to the desired one and the estimated matrix is bounded under the control of the proposed visual feedback controller. The performance was confirmed by simulations and experiments.

Presents an integrated tactile feedback system for a multifingered robot hand to enable a human operator to feel contacts/interactions between the robot finger and the environment remotely. The system presented consists of a finger-shaped tactile sensor measuring contact areas on the fingertip and a tactile display rendering the contact information to the human operator. The tactile sensor, designed on the total internal reflection principle, can capture high resolution and high quality tactile images on the fingertip. The tactile display with 24 pins spaced at 2.5 mm uses DC solenoids structured in multi-layers to render the contacts between the fingertip and the environment. We have integrated the tactile sensor and the tactile display into a five-fingered robot hand system and verified the performance of the integrated system by experiments.

To implement a position-based visual feedback controller for a manipulator, it is necessary to calibrate the homogeneous transformation matrix between its base frame and the vision frame besides the intrinsic parameters of the vision system. In this paper, based on an important observation that the unknown transformation matrix can be separated from the visual Jacobian matrix, we design an adaptive controller for manipulators when the matrix is not calibrated. It is proved, with a full dynamics of the system, by the Lyapunov approach that the motion of the manipulator approaches asymptotically to the desired trajectory. Simulations and experimental results both demonstrate the performance of this new controller.

This paper presents a simple and efficient algorithm to calculate the fingertip positions which ensure a form-closure grasp. The algorithm first arbitrarily chooses a grasp on the given faces of the object. If the selected grasp is not form-closure, the origin O of the wrench space lies outside of the convex hull of the primitive contact wrenches. In this case, the algorithm properly moves the fingertip positions at a fixed step on the faces so that the primitive contact wrenches move towards the origin O until the origin is eventually contained by the convex hull after iterations of the operation. The form-closure property is checked by our ray-shooting based qualitative test algorithm. The motion of the fingertip positions at every step is determined by a quadratic programming problem. Finally we have implemented the proposed algorithm and verified its efficiency with three numerical examples.

To implement a visual feedback controller, it a's necessary to calibrate the homogeneous transformation matrix between the robot base frame and the vision frame besides the intrinsic parameters of the vision system. The calibration accuracy greatly affects the control performance. We address the problem of controlling a robot manipulator using visual feedback without calibrating the transformation matrix. It is assumed that the vision system can measure the 3D position and orientation of the robot in real-time. Based on the fact that the visual Jacobian matrix can be represented in a linear form of elements of the transformation matrix, we propose a simple adaptive algorithm to estimate the unknown matrix on-line. This visual feedback controller greatly simplifies the implementation process of a robot-vision workcell and is especially useful when a pre-calibration is not possible, such as when a robot works with an active vision system carried by a mobile robot. It is proved by the Lyapunov approach that the robot position approaches asymptotically to the desired one and the estimated matrix is bounded under the control of this visual feedback controller. The performance has been confirmed by simulations and experiment.