S.K. Tso

Visual programming for capturing of human manipulation skill

The paper describes a visual programming approach to transferring the operators manipulation skill directly to the robot. The objective is to let the robot learn by observing the human expert moving in his/her own work space. High-speed and high-precision acquisition of the location information is expedited by a marker-based visual system mounted on a conic tool surface, assisted by transputer calculation. Possible violation of the robot physical constraint is checked online with the provision of computer graphic facilities in the system which are also used for subsequent automatic path refinement.

Variable structure model reference adaptive control of robot manipulators

An adaptive control scheme combining the variable structure and model reference methods is presented. With the variable structure technique, all known parameters of the robot system are fully used while the unknown parameters are adaptively adjusted. The overall control system maintains the basic structure of the computer torque controller, but incorporates adaptive components in the system. The method removes the requirement for persistent excitation, essential to traditional adaptive schemes for satisfactory operation. The control algorithm ensures the robustness of the controlled system with respect to disturbance, since the tracking error always converges to zero theoretically, rather than to an ill-defined residual set as in other adaptive schemes. Using this method, the transient response can be prescribed in advance. Thus, all the outstanding issues in adaptive control are directly treated. Simulation analysis for a two-degree-of-freedom robot is conducted to compare the method with the classical model reference method and computed torque method.<<ETX>>

A fast motion planner based on configuration space

This paper describes a fast motion planning method which can be applied to online collision avoidance. It is based on C-obstacle determination, but the way in which the surface contours are established reduces significantly the determination time. Collision checking is based on exploring possible virtual intersection between the two convex polyhedra which define the robot link and the obstacle. Virtual intersection is deduced by examining the signs of distances between a facet of a robot polyhedron and the vertices of the obstacle polyhedron, and that between a facet of the obstacle polyhedron and the vertices of the robot polyhedron. A subsidiary feature of this planner is that it can determine the direction for the robot to retract from an approaching obstacle, according to the types of virtual intersection detected.

Implementing model-based variable-structure controllers for robot manipulators with actuator modelling

A model-based control scheme for robot manipulators employing a variable structure control law has been found to perform well, provided that the design parameters are carefully chosen. A refinement of the system model of this original scheme in which the actuator dynamics is taken into consideration is studied. Practical experiments are carried out on a commercial revolute-joint robot manipulator.

Robust control of robot manipulators using hybrid H/sup /spl infin///adaptive controller

A robust hybrid control method for robot manipulators is proposed which integrates an H/sup /spl infin// controller and an adaptive controller. The H/sup /spl infin// controller is used to minimize the effect of parameter uncertainties of the robot model on the tracking performance, while the adaptive controller continuously adjusts the model parameters to reduce the model error. Simulations show that disturbances generated from the model error will be quickly compensated and so small tracking errors can be achieved.<<ETX>>

A discrete learning algorithm for robot motion control with both position and velocity sensing

With a view to improving the quality of learning and simplifying the iterative learning controller implementation, a new discrete strategy for robot motion control is proposed. A systematic means is devised to merge the position and velocity data in consecutive cycles for effective learning control. The convergence property is also established.<<ETX>>

Model-Based Variable-Structure Adaptive Control of Robot Manipulators

Abstract Model-based control enables the nonlinear, coupled and time-varying dynamics of multi-joint robot manipulator to be largely compensated. There are, however, inevitable uncertainties in the model and various adaptive control measures have been proposed to retain the inherent advantage of the model-based control. This paper deals with a recently developed scheme which singles out the uncertain parameters in the model and applies a switching control law acting on the parameter estimates understood to vary within given bounds. The particular features of the new method are examined by means of an experimental study.

Adaptive Variable Structure Control of Robot Trajectories

By making use of all known parameters in the robot manipulator model and introducing variable structure control laws to adjust the remaining unknown parameters, a novel model reference adaptive control system is developed for robot trajectory control. The tracking errors of the joint variables will converge to zero without persistent excitation. The transient response can be prescribed in advance. Performance is basically not affected by input disturbances.