Nonlinear Control Techniques for Robot Manipulators

This Masters thesis describes the design and implementation of control strategies for the following topics of research: i) Whole Arm Grasping Control for Redundant Robot Manipulators, ii) Neural Network Grasping Controller for Continuum Robots and, iii) Coordination Control for Haptic and Teleoperator Systems. An approach to whole arm grasping of objects using redundant robot manipulators is presented. A kinematic control which facilitates the encoding of both the end-effector position, as well as body self-motion positioning information as a desired trajectory signal for the manipulator joints is developed. An approach is presented to whole arm grasping control for continuum robots. The grasping controller is developed in two stages; high level path planning for the grasping objective, and a low level joint controller using a neural network feedforward component to compensate for dynamic uncertainties. Lastly, two controllers are developed for nonlinear haptic and teleoperator systems for coordination of the master and slave systems

Passive tool dynamics rendering for nonlinear bilateral teleoperated manipulators

Abstract--In the companion paper [1], a control law ren-ders a 2n-degree of freedom (DOF) nonlinear teleoperator (consisting of n-DOF master and slave robots) as a n-DOF common passive mechanical tool which has the usual robotic dynamics. In this paper ~ we develop a control methodology to endow the resulting n-DOF common passive mechanical tool with useful passive tool dynamics which incorporates inertia scaling, guidance / avoidance system while preserv-ing energetic passivity of the closed-loop system. A ficti-tious energy storage is used to scale the apparent inertia of the teleoperator. The passive velocity field control [2] for a velocity field tracking and artificial potential function are utilized for guidance / avoidance system. Thus, with the control law proposed in [1] ~ the control law renders the 2n-DOF teleoperator as a n-DOF common passive mechanical tool which has programmable apparent inertia and moves under the effects of velocity / potential field tailored to task objectives and obstacles in the workspace. I

Smart Exercise Adaptive Control of a Three Degree of Freedom Upper-limb Manipulator Robot

An adaptive velocity field controller for robotic manipulators is proposed in this thesis. The control objective is to cause the user to exercise in a manner that optimizes a criterion related to the user’s mechanical power. The control structure allows for passive user-manipulator physical interaction while the adaptive algorithm identifies the user’s biomechanical characteristics as a linear Hill based force-velocity curve defined at each pose of a repetitive exercise motion i.e. a Hill surface. The study of such a surface allows for the characterization of maximal effort exercise tasks and subsequently the control of exercises that is unique to each user. This allows for the intelligent characterization of a user’s abilities such that repetitive exercises defined by velocity fields can be safely performed. Such a study involving a 3DOF manipulator operating in full 3D has not been conducted in literature to the best of author’s knowledge. The proposed control structure is verified through experimentation on a unimanual setup of the BURT rehabilitation manipulator system involving a single user. The manipulator system includes friction, actuator/sensor noise, and unmodelled dynamics