Task-space sensory feedback control of robot manipulators (Q2253779)

The book presents recent advances in robot control theory on task-space sensory feedback control of robot manipulators. By using sensory feedback information, the robot control systems are robust to various uncertainties in modeling and calibration errors of the sensors. Several sensory task-space control methods that do not require exact knowledge of either kinematics or dynamics of robots, are presented. Some useful methods such as approximate Jacobian control, adaptive Jacobian control, region control and multiple task-space regional feedback are included. The contents of the book is organized as follows. Chapter 1 serves a brief introductory purpose. Its presentation assumes already some familiarity of the readers with robot kinematics and dynamics. Chapter 2 introduces the fundamental concepts for design and analysis of task-space sensory feedback control with uncertainty. The joint-space method for control of robots is first reviewed, and several task-space sensory feedback control schemes for setpoint control or point-to-point control of a robot manipulator are introduced. Such control schemes were inspired by human visually guided reaching movements, which do not require an accurate knowledge of kinematics and dynamics of the arm. Chapter 3 introduces several basic concepts and design techniques to adaptive Jacobian control of robot manipulators using sensory task-space feedback. The approach allows to design adaptive controllers with concurrent adaptation to both kinematic and dynamic uncertainties. Several sensory task-space adaptive controllers are introduced for tracking the control of a robot in the presence of uncertain transformations from sensory space to joint space. The design concept is also an useful modular tool for studying robot or nonlinear systems containing multiple uncertainties. Update laws for various uncertain parameters such as actuator model and depth information can be added and updated concurrently while preserving the structure and properties of the original adaptive control systems and ensuring the stability of the overall system. In most human reaching movements, the desired targets are regions with arbitrary shapes rather than points. Chapter 4 introduces a control concept called region control. In region control, the desired objective can be specified as a region instead of a point or trajectory. Since the desired region can be specified to be arbitrary small, the region control method is also a generalization of the set point control problem and trajectory tracking control problem. The desired region can be also specified as a performance bound to ensure transient and steady-state response of the system. Since a region is specified of a point or a trajectory, less control effort is required, saving energy in the reaching task. Region control can also be used as a secondary objective to set constraints on the motion control task so that a robot operates in a finite region within the sensing zone and singularities are avoided. In Chapter 5 a regional feedback method is designed for task-space robot control. Based on the concept of regional feedback, a global task-space controller is developed for a robotic manipulator, which enables the end effector to start from any initial position outside the sensing zone and in the vicinity of singularities, and reach for a desired trajectory. The global task-space controller also allows the robot to enter vision-occluded areas of singular regions during the course of movement. In Chapter 6, sensory task-space control problems of robot systems with uncertain actuator dynamics are studied. Two main types of actuator dynamics, electrically driven actuator systems and joint flexibility, are considered. In addition, force control problems with constraint uncertainty and multi-fingered robot control with uncertain contact points are treated. Finally, in an Appendix, a brief description of Lyapunov's stability method, related with considered above problems, is given.