In this paper, the kinematics and inverse dynamics of a novel kind of mechanism called a general 3-PRS parallel mechanism is investigated. In the kinematics study, the inverse kinematics solution is derived in closed form, and the forward kinematics problem is resolved by the Newton iterative method seeking for an on-line solution to this issue. The inverse dynamics analysis is approached with two methods: Lagrangian formulations and principle of virtual work. After deriving the dynamic model by a Lagrangian formulation approach, the simulation results of two introduced examples quantitatively and qualitatively verify the accuracy of the derived dynamic equations. By introducing a simplifying hypothesis, a simplified dynamic model is set up using principle of virtual work, also a computer simulation is performed on this reduced model. The simulation results demonstrate that the simplified dynamic model is reasonable under such kind of assumptions through comparison with the precise model derived from the Lagrangian formulation. The inverse dynamics analysis provides a sound basis to develop controllers for controlling over a general 3-PRS parallel robot.

We present a simple biologically inspired strategy for the navigation of a unicycle-like robot towards a target while avoiding collisions with moving obstacles. A mathematically rigorous analysis of the proposed approach is provided. The performance of the algorithm is demonstrated via experiments with a real robot and extensive computer simulations.

After the enthusiasm for creating “intelligent robots” in the early 1980's, progress of robotics research in the past decade has not fulfilled our expectations but revealed various difficulties in understanding motor control by man and implementing intelligent functions in robotic machines. To regain the initiative in the development of intelligent machines, this paper first presents a critical review of the state of the art of robot control and points out the necessity for improving robot servo-loops in order to facilitate skilled and dexterious motions in robotic manipulators and mechanical hands. It is then shown that the introduction of a quasi-natural potential in Lagrange's formulation of robot dynamics gives rise to the design of hyperstable PID servo-loops, which establish global asymptotic stability of set-point control. The hyperstability theoretical framework is then applied to the design of control commands in various control problems, such as hybrid (position/force) control, impedance control, model-based adaptive control, and learning control. In all cases, the passivity concept of residual robot dynamics plays a vital role in conjunction with the concept of feedback connections of two hyperstable nonlinear or linear blocks.

The technologies of autonomous rendezvous and robotic capturing of non-cooperative targets are very crucial for the future on-orbital service. In this paper, we proposed a method to achieve this aim. Three problems were addressed: the target recognition and pose (position and attitude) measurement based on the stereo vision, the guidance, navigation and control (GNC) of the chaser, and the coordinated plan and control of space robot (CP&C). The pose measurement algorithm includes image filtering, edge detection, line extraction, stereo match and pose computing, et al. Based on the measured values, a certain GNC algorithm was designed for the chaser to approach and rendezvous with the target. Then the CP&C algorithm, which is proved to be advantageous over the traditional separated method, was used to plan and track the trajectories of the base pose and the joint angle. At last, a 3D simulation system was developed to evaluate the proposed method. Simulation results verified the corresponding algorithms.

This paper presents an adaptive impedance control scheme for an $n$-link constrained rigid robot manipulator without using the regressor. In addition, inversion of the estimated inertia matrix is also avoided and the new design is free from end-point acceleration measurements. The dynamics of the robot manipulator is assumed that all of the matrices in robot model are unavailable. Since these matrices are time-varying and their variation bounds are not given, traditional adaptive or robust designs do not apply. The function approximation technique is used here to represent uncertainties in some finite linear combinations of the orthogonal basis. The dynamics of the output tracking can thus be proved to be a stable first order filter driven by function approximation errors. Using the Lyapunov stability theory, a set of update laws is derived to give closed loop stability with proper tracking performance. A 2 DOF planar robot with environment constraint is used in the computer simulations to test the efficacy of the proposed scheme.

A haptic interface is a computer-controlled mechanism designed to detect motion of a human operator without impeding that motion, and to feed back forces from a teleoperated robot or virtual environment. Design of such a device is not trivial, because of the many conflicting constraints the designer must face.

As part of our research into haptics, we have developed a prototype planar mechanism. It has low apparent mass and damping, high structural stiffness, high force bandwidth, high force dynamic range, and an absence of mechanical singularities within its workspace. We present an analysis of the human-operator and mechanical constraints that apply to any such device, and propose methods for the evaluation of haptic interfaces. Our evaluation criteria are derived from the original task analysis, and are a first step towards a replicable methodology for comparing the performance of different devices.

A new global isotropy index (GII) is proposed to quantify the configuration independent isotropy of a robot's Jacobian or mass matrix. A new discrete global optimization algorithm is also proposed to optimize either the GII or some local measure without placing any conditions on the objective function. The algorithm is used to establish design guidelines and a globally optimal architecture for a planar haptic interface from both a kinematic and dynamic perspective and to choose the optimum geometry for a 6-DOF Stewart Platform. The algorithm demonstrates consistent effort reductons of up to six orders of magnitude over global searching with low sensitivity to initial conditions.

A major technical challenge in controlling modular and reconfigurable robots is associated with the kinematics and dynamic model uncertainties caused by reconfiguration. In parallel, conventional model uncertainties such as uncompensated joint friction still persist. This paper presents a modular distributed control technique for modular and reconfigurable robots that can instantly adapt to robot reconfigurations. Under the proposed control method that is based on joint torque sensing, a modular and reconfigurable robot is stabilized joint by joint, and modules can be added or removed without the need to adjust control parameters of the other modules of the robot. Model uncertainties associated with link and payload masses are compensated using joint torque sensor measurement. The remaining model uncertainties, including uncompensated dynamic coupling and joint friction, are compensated by a decomposition-based robust controller. Simulation results have confirmed the effectiveness of the proposed method.

This paper describes the experimental evaluation of three identification schemes to determine the dynamic parameters of a two degrees of freedom direct-drive robot. These schemes involve a recursive estimator while the regression models are formulated in continuous time. The fact that the total energy of robot manipulators can be represented as a linear relation in the inertial parameters, has motivated the suggestion in the literature of several regression models which are linear in a common dynamic parameter vector. Among them, in this paper we consider the schemes based on the filtered dynamic regression model, the supplied energy regression model and a new one proposed in this paper: the filtered power regression model. The underling recursive parameter estimator used in the experimental evaluation is the standard least-squares.

This paper demonstrates how numerical optimization techniques can efficiently be used to create self-stable running motions for a human-like robot model. Exploitation of self-stability is considered to be a crucial factor for biological running and might be the key for success to make bipedal and humanoid robots run in the future. We investigate a two-dimensional simulation model of running with nine bodies (trunk, thighs, shanks, feet, and arms) powered by external moments at all internal joints. Using efficient optimal control techniques and stability optimization, we were able to determine model parameters and actuator inputs that lead to fully open-loop stable running motions.

This paper addresses an optimal study of workspace for spherical parallel mechanism for laparoscopic surgery. The spherical parallel manipulator has been selected because of its characteristics. Two designs have been studied for maximizing their workspaces; a haptic device, as part of training system, and a laparoscope holding mechanism. The laparoscope holding mechanism has to satisfy additional constraints by minimizing the occupied space above the patient. The objective is to solve design problem to offer the maximal workspace for such mechanisms. The design of a haptic interface and the laparoscope holding mechanism based on the optimal parameters are presented. This paper presents a Genetic Algorithm (GA) approach for selecting optimal design parameters for maximizing workspace of spherical parallel mechanism.

A Wall-Climbing Robot (WCR) with magnetic tracks is presented in this paper. The robot is designed for labeling the scale of oil tank.5 The Wall-Climbing Robot (WCR) uses a permanent magnet sucker as its sucking mode, and a track as its moving mode. We designed an elastic brace mechanism, a load-scatter mechanism and parallelogram mechanism to improve the robot's adaptability on the steel wall surface. The control system utilizes two-level computer control systems, achieving control of the robot's moving track and processing data collected by the robot.

This paper presents a general method to identify the geometric parameters of robots. An algorithm is given to calculate the identifiable geometric parameters. The robot location and the tool location parameters are taken into account. The algorithm is generalized to tree structure robots. The problem of selecting the optimum robot configurations to be used during the identification is discussed and a solution is proposed.

Wearable devices are fast evolving to address mobility and autonomy needs of elderly people who would benefit from physical assistance. Recent developments in soft robotics provide important opportunities to develop soft exoskeletons (also called exosuits) to enable both physical assistance and improved usability and acceptance for users. The XoSoft EU project has developed a modular soft lower limb exoskeleton to assist people with low mobility impairments. In this paper, we present the design of a soft modular lower limb exoskeleton to improve person’s mobility, contributing to independence and enhancing quality of life. The novelty of this work is the integration of quasi-passive elements in a soft exoskeleton. The exoskeleton provides mechanical assistance for subjects with low mobility impairments reducing energy requirements between 10% and 20%. Investigation of different control strategies based on gait segmentation and actuation elements is presented. A first hip–knee unilateral prototype is described, developed, and its performance assessed on a post-stroke patient for straight walking. The study presents an analysis of the human–exoskeleton energy patterns by way of the task-based biological power generation. The resultant assistance, in terms of power, was 10.9% ± 2.2% for hip actuation and 9.3% ± 3.5% for knee actuation. The control strategy improved the gait and postural patterns by increasing joint angles and foot clearance at specific phases of the walking cycle.

Several static and dynamic stability criteria have been defined in the course of walking robot history. Nevertheless, different applications may require different stability criteria and, to the authors' best knowledge, there is no qualitative classification of such stability measurements. Using the wrong stability criterion to control a robot gait may prevent the task from succeeding. Furthermore, if the optimum criterion is found, the robot gait can also be optimized. In this paper, the stability criteria that have been applied to walking robots with at least four legs are examined in terms of their stability margins in different static and dynamic situations. As a result, a qualitative classification of stability criteria for walking machines is proposed so that the proper criterion can be chosen for every desired application.

During the last two decades a large amount of effort and attention has been paid to the problem of designing and controlling dextrous robotics hands. The possible application background ranges from telerobotics to upper limb prosthetics, while actual industrial developments are mainly limited to specific grippers and tools. Classical problems related to dextrous hand design are kinematics of multifingered hands, development of proper actuation technologies and redundant tendinous systems for transmission. As far as hand control is concerned, grasp preshaping, planning and synthesis are of major concern, while sensor guided hand operation is still a matter of research. The present work reviews the above mentioned hand design and control issues trying to throw some light on the Babel-like confusion encountered when looking at present literature on dextrous hand design and specially control. Most actuation and transmission technologies, as well as control approaches, are studied and classified.

Several descriptions of redundancy are presented in the literature, often from widely different perspectives. Therefore, a discussion of these various definitions and the salient points would be appropriate. In particular, any definition and redundancy needs to cover the following issues; the difference between multiple solutions and an infinite number of solutions; degenerate solutions to inverse kinematics; task redundancy; and the distinction between non-redundant, redundant and highly redundant manipulators.

The design of prosthetic hands is constrained by a series of strict conditions. Despite this, many different design strategies have been explored. One particular form is the Southampton Hand system. This is a hierarchically controlled, electrically driven hand, with multiple axes, in an anthropomorphic form. This paper details the range of mechanical solutions adopted to address the conditions. It also compares them with other solutions.

This work presents, first, a complete dynamic model of a unicycle-like mobile robot that takes part in a multi-robot formation. A linear parameterization of this model is performed in order to identify the model parameters. Then, the robot model is input-output feedback linearized. On a second stage, for the multi-robot system, a model is obtained by arranging into a single equation all the feedback linearized robot models. This multi-robot model is expressed in terms of formation states by applying a coordinate transformation. The inverse dynamics technique is then applied to design a formation control. The controller can be applied both to positioning and to tracking desired robot formations. The formation control can be centralized or decentralized and scalable to any number of robots. A strategy for rigid formation obstacle avoidance is also proposed. Experimental results validate the control system design.