Aiming at mimicking water strider's water-surface locomotion, this study proposes a new miniature surface tension-driven robot. A key feature of this robot is that its actuating legs possess ellipse-like spatial trajectories like water strider by using a cam-link mechanism, and never pierces water surface when rowing. A set of simple models and equations are proposed to analyze the interaction forces between leg and water as well as the critical condition for a leg penetrating a water surface. The final fabricated robot weights about 3.9 g with a load capacity of 5.6 g. By controlling the motions of actuating legs, the robot can freely and stably walk on water with different gaits. The maximum forward and turning speeds of the robot are measured as 16 cm/s and 23 °/s, respectively. Moreover, a similarity analysis with Bond Number and Weber Number reveals that the locomotion of this robot is quite analogous to that of a water strider: surface tension force dominates the lifting force and plays a major role in the propulsion.

This paper proposes a novel CPG-based control architecture for hexapod walking robot. We investigate the CPG systems from the perspective of network synchronization. In this way the motion control of hexapod robot can be refined into the gait generation level and joints coordination level. On the first level, we develop a gait generator consists of CPG network in ring based on modified Van der Pol (VDP) oscillator to realize various stable gaits as well as gait transition for hexapod walking. The limit cycle behavior of VDP model is analytically studied by virtue of perturbation technique. On the second level, we address the problem of multi-DoF coordination of single leg via phase order modulation and amplitude adjustment of the neural oscillators. Consequently we propose a single-leg controller consists of a three-coupled CPG network and a linear coefficient converter to generator smooth and feasible trajectories in task space. The effectiveness of the proposed control architecture is demonstrated through simulation and real physical robot experiment.

The Spring-Loaded Inverted Pendulum (SLIP), or monopedal runner, is widely used to depict running and hopping in mammalian and human locomotion, which is also serving as a template for running robot design. This classic model describes quite a simple mechanical system. Nevertheless issue of seeking the accurate analytic solution revealing the characteristics of the motion during stance remains unsettled due to the nonintegrable terms contained in the system equations. Moreover, several existing analytic approximations by simply ignoring or linearizing the gravitational force can not reveal the entire dynamical behavior of nonlinear system as well as can be breakdown rapidly when applied to a non-symmetric motion case. In this paper, a novel method with perturbation technique is proposed to obtain analytic approximate solutions to the SLIP dynamics in stance phase with considering the effect of gravity. The perturbation solution achieves higher accuracy in predicting the apex trajectory and stance locomotion by comparing with typical existing analytical approximations. Particularly, our solution is validated for non-symmetric case in a large angle range. Additionally, the prediction for stance trajectory is also verified through numerical evaluation.

In this paper, an improved algorithm to measure Chinapsilas EMU spacesuit joint damping parameters for the old passive robot system is presented. The measuring principle is based on robot kinematics and dynamics. Firstly, a kinematic model of the passive robot and the EMU spacesuitpsilas arm is built according to the special mechanical structure. Secondly, improved methods of solving the inverse kinematics of the EMU spacesuit arm including flexible joints are proposed. And finally, a new algorithm that eliminates the gravity effect is implemented to calculate the damping torques of the EMU spacesuit joints. Experimental results and verification on SGI workstation proved the correctness and effectiveness of the proposed measuring method.

This paper gives an overview of the Chinese intelligent space robotic system. The system consists of a 6 DOF robot arm, a large-error tolerated gripper with two stereo cameras and onboard computer. The robot arm is composed of six identical modular joints, a big central hole in the modular joint was designed for the placement of the cables and plugs in the robot arm, which prevented them from damage of high temperature, radiation in the space environment and the motion of the robot. Joint torque sensor, joint position sensor and temperature sensors etc.., were integrated into the fully modular multi-sensory joint, which made the joint more intelligent. Also, a large-error tolerated gripper with two stereo cameras has been also designed to capture a microtarget satellite (MTS). A fault-tolerant onboard computer (OBC) with dual processing modules has been developed for the robot control. A zero gravity experimental system was developed to verify the functions of the robot arm under zero gravity environment

Based on under-actuated mechanism and coupling principle, a five-fingered, multi-sensory and biomechatronic prosthetic hand has been designed. The multi-DOF hand comprises 13 joints and is controlled by 3 motors. Actuated by only one motor, the thumb can move along a cone surface which is superior in the appearance. Also driven by one motor and transmitted by springs, the mid finger, the ring finger and the little finger can move simultaneously and envelop objects with complex shape. On the other hand, during the hand designation, the handsome appearance has been considered and its glove prototype has been designed. The hardware system and the sensory system have been developed. Through Bluetooth wireless protocol, the hand can be controlled by voice signal. Furthermore, it can also be controlled by electromyography (EMG) signal like most prosthetic hand in existence. It has been verified by experiments that the hand has strong capability of self-adaptation grasp and can accomplish precise and power grasp

Significant research have been devoted into the field of multi-robot teleoperation system over Internet. However, the low safety and efficiency due to time delay and complexity between multiple robots and operators prevent the teleoperation technology from developing. Specially, the possible collision between multiple robots has a great effect on the Internet-based multi-operator-multi-robot teleoperation system. In this paper, a task planner based on Petri net theory was proposed to assist multi-operators coordinate multi-robots. The conception of implicit elementary operation and explicit elementary operation were introduced to realize modeling and automatic plan of the system. In the multi-operator multi-robot system built by us, a supervisory controller was designed based on the place invariants not only to lead two operators' manipulation with virtual environment but also to restrict the state of two robots' motion during their work. An experiment via network was carried out to evaluate the validity of the task planner for the medical research of highly dangerous virus such as SARS, bird flu etc. The experimental results show that the safety and efficiency of the system can be improved using the task planner

A new five-fingered underactuated prosthetic hand control system is presented in this paper. The prosthetic hand control part is based on an EMG motion pattern classifier which combines VLR (variable learning rate) based neural network with wavelet transform and sample entropy. This motion pattern classifier can successfully identify flexion and extension of the thumb, the index finger and the middle finger, by measuring the surface EMG signals through three electrodes mounted on the flexor digitorum profundus, flexor pollicis longus and extensor digitorum. Furthermore, via continuously controlling single finger's motion, the prosthetic hand can achieve more prehensile postures such as power grasp, fingertip grasp, etc. The experimental results show that the classifier has a great potential application to the control of bionic man-machine systems because of its high recognition capability

A closed loop self-calibration method for Delta mechanism and 3-RRR mechanism used in a double parallel haptic device was presented. This approach blocks successively one joint of each parallel mechanism using a simple lockup device and reforms the 3-DOF mechanism to be a 2-DOF one. The parameter errors of the mechanism are identified according to the differences between the sensor output of the redundant chain and nominal model output. Both the condition number and singular value of the error propagation Jacobian are synthesized as a new selection principle of calibration set such that the calibrating process is insensitive to the noise and the calibration precision is increased efficiently. Experiments show that the ratio of maximal error before and after calibrating is 9.6, namely, the setting accuracy of the two mechanisms are increased about 10 times and the error of re-position is less than 0.1 mm and 0.1deg

This paper presents a surface Electromyography (EMG) motion pattern classifier which combines Levenberg-Marquardt (LM) based neural network with parametric Autoregressive (AR) model. This motion pattern classifier can successfully identify three types of motion of thumb, index finger and middle finger, by measuring the surface EMG through two electrodes mounted on the flexor digitorum profundus and flexor pollicis longus. Furthermore, via continuously controlling single finger’s motion, the five-fingered underactuated prosthetic hand can achieve more prehensile postures such as power grasp, centralized grip, fingertip grasp, cylindrical grasp, etc. The experimental results show that the classifier has a great potential application to the control of bionic man-machine systems because of its fast learning speed, high recognition capability and strong robustness.

This paper presents a novel two-layer fuzzy-navigator that incorporates sensing, control and planning to guide real-time self-reaction of a mobile robot in FMC/FMS. It can identify and solve the local minima problem during the robot's movement, which mimic the way that a human might understand his trapped state by recollecting some of similar experiences he had experienced before. The first-layer-controller does the regular navigation, while the remembrance is provided by the second-layer local-minima-solver, which can also analyze the information of sensor readings, impart an understanding of the robot's local environment and correlate the same with human heuristic experiences of a similar environment. The robot's local environment is identified in terms of fuzzy-rule, sensor- information and landmark-weight-vector. When the robot reaches a dangerous landmark-weigh-value during movement, it understands its entanglement in a loop and takes suitable actions to pull the robot out of its trap. The simulation results prove the validity of the proposed method.

The paper presents hardware and software architectures of the HIT/DLR Hand. The hand has four identical fingers and an extra degree of freedom (d.o.f) for the palm. In each finger, there is a re-configurable Field Programmable Gate Array (FPGA) for data acquisition, Brushless DC (BLDC) motor control and communication with the palm's FPGA by Point-to-Point Serial Communication (PPSeCo). The kernel of the hardware system is a PCI-based high speed floating-point Digital Signal Processor (DSP) for data processing, and an FPGA for high speed (up to 25 Mbps) real-time serial communication with the palm's FPGA. In order to achieve high modularity and reliability of the hand, a fully mechatronic integration and analog signals in-situ digitalization philosophy are implemented to minimize the dimension, number of the cables (5 cables including power supply) and protect data communication from outside disturbances. Furthermore, according to the hardware architecture of the hand, a hierarchical software architecture has been established to perform all data processing and control of the hand. The software structure provides basic Application Programming Interface (API) functions and skills to access all hardware resources for data acquisition, computation and teleoperation.

Time delay over the Internet deteriorates the performance of multi-operator-multi-robot teleoperation system (MOMR). At present, several methods aiming at the problems of the Internet-based multi-telerobot collaboration only depend on the master side. In this paper, a coordinated controller was presented based on the idea of shared control that combined the intelligence of the master side with the slave side. It is composed of three modules, task coordination, motion planning and communication, which can not only increase the efficiency and safety of the system but also relieve the burden and the requirements to the operators. The controller also can cope with the collision between two telerobots in the common environment arising from the time delay. A simulation experiment via an Ethernet local area network (LAN) subject to simulated time delay was carried out to protect the medical staff from highly dangerous virus such as SARS, bird flu etc. And the validity of the coordinated controller was evaluated in the system.

This paper presents the current work progress of HIT/DLR Dexterous Hand. Based on the technology of DLR Hand II, HIT and DLR are jointly developing a smaller and easier manufactured robot hand. The prototype of one finger has been successfully built. The finger has three DOF and four joints, the last two joints are mechanically coupled by a rigid linkage. All the actuators are commercial brushless DC motors with integrated analog Hall sensors. DSP based control system is implemented in PCI bus architecture and the serial communication between the hand and DSP needs only 6 lines(4 lines power supply and 2 lines communication interface). The fingertip force can reach 10N.

This paper presents a novel passive robot system with 6 DOF force/torque sensor for measuring spacesuit joint damping parameters. Based on its special mechanical structure, a 3 DOF model of flexible IVA (intra vehicular activity) spacesuit joint has been built. Experimental results prove the effectiveness of the measuring principle. Potential application of the measuring system is discussed.

In this paper, we present a novel algorithm for computing three-finger force-closure grasps of 2D and 3D objects. In the case of a robot hand with three hard fingers and point contact with friction, new necessary and sufficient conditions for 2D and 3D equilibrium and force-closure grasps have been deduced, and a corresponding algorithm for computing force-closure grasps has been developed. Based on geometrical analysis, the algorithm is simple and only needs a few algebraic calculations. Finally, the algorithm has been implemented and its effectivity has been demonstrated by two examples.

This paper presents a new intelligent path planning method for motions of the mobile manipulator in flexible manufacturing cell. It simulates the way of human actions to control the mobile manipulator according to a master-slave hierarchical control strategy. The method can find path using the genetic fuzzy controller (GFC) while in moving, and switch to the collision-free path planner based on the critical collision joint angle (CCJA) and DA* algorithms when in requirement of performing the tasks such as load or unload. In this paper, the GFC is developed to automatically generate the fuzzy if-then rules from samples. In addition, a new modeling approach for manipulator is presented. It is called the c-space modeling based on CCJA. Using this technique, the computation time and memory space are greatly reduced. Moreover, a modified DA* algorithm with dynamic step-changeable and goal-visible-test is also used to accelerate the search process. Simulation results of the mobile manipulator performing object transporting task show the method presented is feasible.

Presents an intelligent control method for real-time self-reaction of a mobile robot in an unknown environment, it is called a genetic fuzzy neural network. It is used to control a mobile robot according to sensing different information, which includes the different direction distances between the obstacles and robot sensed by ultrasonic sensors, the target orientation sensed by a simple optical range-finder and the robot's direction of movement. In the paper, the distances d/sub r/, d/sub c/, and d/sub l/ between the robot and the obstacles with respect to the right, front and left sensors, as well as the angle t/sub r/, between the target orientation and the robot's direction of movement are taken as the inputs of the intelligent controller. The output of the intelligent controller is the steering angle s/sub a/. A genetic fuzzy neural network is presented to describe the fuzzy reasoning relationship between the inputs and the output of the system. It has a few advantages, such as higher learning speed and easier ensuring convergence. Simulation results of mobile robot collision avoidance in an unknown environment show the method presented is feasible.

This paper presents the implementation of online learning neural network controller in the pneumatic robot position servo control. The advantages of this design include: the ability to compensate for nonlinearities, and it is insensitive to system parameter time-varying. The traditional PID controller is replaced by neural network controller trained online to learn the inverse model of the pneumatic manipulator by backpropagation of the performance error. The simulation studies and experimental results on the PID controller, online learning neural network controller and off-line training neural network controller, are presented and discussed.

Assembly is one of the key areas for achieving productivity improvements in industry. Robotic assembly has become a highly important aspect of robot industrial applications. The authors present an active/passive assembly system, which has the virtues of both active and passive assembly methods. Differing from the active/passive systems of the past, it combines the active and passive functions in one. Hence the system is fully controllable and can conduct assembly operation along any direction. The system is a macro/micro manipulation system. It employs a PUMA 562 robot as macro manipulator and a specially designed active/passive micromanipulator as the micro one which is mounted on the end of PUMA 562 robot. The whole system is controlled by an IBM-PC computer through C language and macro-instructions. An experiment shows that the system is effective.>