The basic robot control technique is the model based computer-torque control which is known to suffer performance degradation due to model uncertainties. Adding a neural network (NN) controller in the control system is one effective way to compensate for the ill effects of these uncertainties. In this paper a systematic study of NN controller for a robot manipulator under a unified computed-torque control framework is presented. Both feedforward and feedback NN control schemes are studied and compared using a common back-propagation training algorithm. Effects on system performance for different choices of NN input types, hidden neurons, weight update rates, and initial weight values are also investigated. Extensive simulation studies for trajectory tracking are carried out and compared with other established robot control schemes.

In this paper sliding mode motion design is considered for nonlinear plants which are linear with respect to control input. The dynamics of the robotic manipulators is treated with and without those of the actuators. When the dynamics of the actuators is included a design of the sliding modes for the systems with discontinuous control is performed. If actuators' dynamics is negelected the control is assumed to be continuous quantity. By combining the variable structure systems and Lyapunov designs a new algorithm is developed which has all the good properties of the sliding mode systems while avoiding unnecessary discontinuity of the control thus eliminating chattering. Neither the explicit calculation of the equivalent control, nor high gain inside the boundary layer are used. The parameters of the control depend on the plant's gain matrix, and the gradients of the sliding mode manifold. This control method is then applied to develop a unified control strategy for the motion control systems including the path tracking control, the impedance control and the force control of a robotic manipulator. It is shown that all these tasks can be formulated in the same mathematical form in which selected so-called sliding mode functions must track their references. In this way the systems state is forced to remain on the selected manifold in the state space after reaching it. The solution is interpreted in both the Joint space and the Work space for n -degrees of freedom robotic manipulators.

The fundamentals of an approach to solving the control task of robots interaction with a dynamic environment based on the stability of a closed-loop control system are given in this paper. The task is set and solved in its general form. The traditional control concept of compliant robot motion—the hybrid position/force control is discussed. In the paper the proposed control laws ensure simultaneous stabilization of both the desired robot motion and the desired interaction force, as well as their required quality of transient responses. In order to emphasize the fundamental point of this approach in controlling the contact tasks in robotics, the authors have assumed ideal parameters of interacting dynamic systems. The proposed control procedure is demonstrated by one simple example.

In this paper, we present two DCAL-like (Desired Compensation Adaptation Law) controllers for link position tracking of n-link, rigid, revolute robot manipulators. First, we use a simplified stability analysis to illustrate global asymptotic link position-velocity tracking for a DCAL-like controller with nonlinear feedback. The proof is simplified by employing a different structure for the nonlinear feedback than that originally proposed and by making use of the nonlinear damping control design tool. We then use the nonlinear damping tool to show that a DCAL-like controller with linear feedback can guarantee semi-global asymptotic link position-velocity tracking. The proposed nonlinear and linear feedback DCAL-like controllers are experimetally tested and compared using the Integrated Motion Inc. 2-link direct drive robot manipulator.

A learning control algorithm is proposed for hybrid force/position tracking of a manipulator in contact with a hard surface. The algorithm utilizes acceleration errors and force errors for learning the inputs required to perform repetitive tasks. We prove the convergence of both force and position tracking errors theoretically. The speed of convergence of the tracking errors is shown to be improved by proper choice of learning gains. The method is compared with PI and PID learning, and similarities with the free-space case are outlined. The robustness of the new scheme to uncertainties in surface geometry and link parameters is discussed. Results of simulation studies and experimental implementation on 3-link robot manipulators are presented to illustrate the effectiveness of the proposed learning controller.

An approach to time-optimal smooth and collision-free path planning for two industrial robot arms is presented, where path planning and joint trajectory generation are integrated. A suitable objective function, combining the requirements of time optimality and path smoothness, is proposed, which is subject to the continuity of joint trajectories, limits on their rates of change and collision-free constraints. Fast and effective collision detection for the arms is achieved using the Kuhn- Tucker conditions along with the convexity of the distance function and relying on geometrical relationships between cylinders. Nonlinear optimization is used to solve this path planning problem. The feasibility of this method is illustrated both by simulation and by experimental results.

This paper addresses the kinematic workspaces of a walking machine and their graphical representation. The workspaces for walking machines are denned and the methods for investigating various workspaces are presented; the kinematic workspace constraints are established; the displacement is analysed; an algorithm for investigation of kinematic workspaces is presented; and the position and orientation kinematic workspaces are analysed and graphically represented for an example walking machine design.

A potential panel method is proposed to solve simultaneously the path planning and collision avoidance problem for a mobile robot operating in an uncertain obstacle filled environment. The problem is solved in three steps: (1) transform the arbitrary shaped obstacles in the 2-D workspace into simple convex polygons; (2) generate a local minima-free potential field on the workspace; (3) generate a streamline from the starting position towards the goal position in the artificial potential field. The computational complexity of the pertinent algorithms justify the applicability of the approach in real-time. Simulation results are included.

This paper presents theoretical and experimental investigations into modelling a single-link flexible manipulator system. An analytical model of the manipulator, characterised by an infinite number of modes, is developed using the Lagrange's equation and modal expansion method. This is used to develop equivalent time-domain and frequency-domain working models of the system in state-space and transfer function forms respectively. The model parameters are then estimated experimentally using system's measured input/output data. The model thus obtained is validated through experimentation and results including the effect of payload on system characteristics presented and discussed.

We have designed a robotic arm based on a double parallel four bar linkage to act as an assistant in minimally invasive surgical procedures. The remote center of motion (RCM) geometry of the robot arm kinematically constraints the robot motion such that minimal translation of an instrument held by the robot takes place at the entry portal into the patientApos;s body. In addition to the two rotational degrees of freedom comprising the RCM arm, distal translation and rotation are provided to manoeuver the instrument within the patient's body about an axis coincident with the RCM. An XYZ translation stage located proximal to the RCM arm provides positioning capability to establish the RCM location relative to the patients anatomy. An electronics set capable of controlling the system, as well as performing a series of safety checks to verify correct system operation, has also been designed and constructed. The robot is capable of precise positional motion. Repeatability in the ±10 micron range is demonstrated. The complete robotic system consists of the robot hardware and an IBM PC-AT based servo controller connected via a custom shared memory link to a host IBM PS/2. For laparoscopic applications, the PS/2 includes an image capture board to capture and process video camera images. A camera rotation stage has also been designed for this application. We have successfully demonstrated this system as an assistant in a laparoscopic cholecystectomy. Further applications for this system involving active tissue manipulation are under development.

To solve manipulation problems when fast transportation operations are combined with high precision positioning operations, an approach to telerobotic system organization with manipulator variable parameters is presented. It is proposed that the human operator should personally adjust the robot parameters in compliance with the situation requirements. Therefore, an additional channel of parameter control was introduced into the system. The approach results in the organizing of highly effective on-line systems with sufficiently simple control algorithms.

A knowledge of the fabric material and its properties, mechanisms of prehension and an understanding of sensor and manipulator integration are essential for even the most basic of robotic textile handling tasks. This paper considers individually, and as a combination, the aspects of mechanical and electrical hardware, software and logistics necessary in making automated fabric ply separation and positioning possible.