An on-line path planner for industrial manipulators

In this paper, an on-line path planner for an industrial manipulator is presented. The proposed control architecture is capable of driving the manipulator in its environment while avoiding collisions. Potential fields are used in order to control the joint velocities in such a way that the robot avoids the obstacles. We also propose a new weighted pseudoinverse matrix that improves the manipulator capability of finding feasible paths to move around obstacles and pass through narrow corridors without relying on the manipulator dynamic model. The proposed technique fits to both redundant and non-redundant manipulators. Experimental results show the effectiveness of the proposed solution

Vibration Control in Cable Robots Using a Multi-Axis Reaction System

The primary motivation of this thesis is to develop a control strategy for eliminating persistent vibrations in all six spatial directions of the end effector of a planar cable-driven parallel robotic manipulator. By analysing the controllability of a cable-driven robot dynamic model, the uncontrollable modes of the robot are identified. For such uncontrollable modes, a new multi-axis reaction system (MARS) is developed. The new MARS that is attached to the end effector is made of two identical pendulums driven by two servo motors. A decoupled PD controller strategy is developed for regulating controllable modes and a hierarchical sliding mode controller is developed for controlling the remaining modes of the cable robot using MARS. The performance of both controllers is studied and shown to be effective in simulation. The controllers are then implemented on an experimental test setup of a planar cable-driven manipulator. Both controllers are shown to completely eliminate the end effector vibrations

Realtime Motion Planning for Manipulator Robots under Dynamic Environments: An Optimal Control Approach

This report presents optimal control methods integrated with hierarchical control framework to realize real-time collision-free optimal trajectories for motion control in kinematic chain manipulator (KCM) robot systems under dynamic environments. Recently, they have been increasingly used in applications where manipulators are required to interact with random objects and humans. As a result, more complex trajectory planning schemes are required. The main objective of this research is to develop new motion control strategies that can enable such robots to operate efficiently and optimally in such unknown and dynamic environments. Two direct optimal control methods: The direct collocation method and discrete mechanics for optimal control methods are investigated for solving the related constrained optimal control problem and the results are compared. Using the receding horizon control structure, open-loop sub-optimal trajectories are generated as real-time input to the controller as opposed to the predefined trajectory over the entire time duration. This, in essence, captures the dynamic nature of the obstacles. The closed-loop position controller is then engaged to span the robot end-effector along this desired optimal path by computing appropriate torque commands for the joint actuators. Employing a two-degree of freedom technique, collision-free trajectories and robot environment information are transmitted in real-time by the aid of a bidirectional connectionless datagram transfer. A hierarchical network control platform is designed to condition triggering of precedent activities between a dedicated machine computing the optimal trajectory and the real-time computer running a low-level controller. Experimental results on a 2-link planar robot are presented to validate the main ideas. Real-time implementation of collision-free workspace trajectory control is achieved for cases where obstacles are arbitrarily changing in the robot workspace

AI based Robot Safe Learning and Control

Introduction This open access book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning. In order to enhance the safety performance of robot systems, the control strategies include adaptive tracking control for robots with model uncertainties, compliance control in uncertain environments, obstacle avoidance in dynamic workspace. The idea for this book on solving safe control of robot arms was conceived during the industrial applications and the research discussion in the laboratory. Most of the materials in this book are derived from the authors’ papers published in journals, such as IEEE Transactions on Industrial Electronics, neurocomputing, etc. This book can be used as a reference book for researcher and designer of the robotic systems and AI based controllers, and can also be used as a reference book for senior undergraduate and graduate students in colleges and universities

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

Unified Dynamics and Control of a Robot Manipulator Mounted on a VTOL Aircraft Platform

An innovative type of mobile manipulator, designated Manipulator on VTOL (Vertical Take-Off and Landing) Aircraft (MOVA), is proposed as a potential candidate for autonomous execution of field work in less-structured indoor and outdoor environments. Practical use of the MOVA system requires a unified controller that addresses the coupled and complex dynamics of the composite system; especially the interaction of the robotic manipulator with the aircraft airframe. Model-based controller design methods require explicit dynamics models of the MOVA system. Preliminary investigation of a two-dimensional MOVA system toward a dynamics model and controller design is presented in preparation for developing the controller of the more complex MOVA system in 3D space. Dynamics of the planar MOVA system are derived using the Lagrangian approach and then transforming the result into a form that facilitates controller design using the concept of a virtual manipulator. A MOVA end-effector trajectory tracking controller was designed with the transformed dynamics equation using the integrator back-stepping control design framework. Validity of the controller is shown via stability analysis, simulation results, and results from a physical test-bed. A systematic approach is illustrated for the derivation of the 3D MOVA system dynamics equations. The resulting dynamics equations are represented abstractly in the standard robot dynamics form and proven to have the skew-symmetric property, which is a useful property for control derivation. An open source Mathematica program was developed to achieve automatic symbolic derivation of the MOVA system dynamics. Accessory tools were also designed to create a tool-chain that starts with an Autodesk Inventor CAD drawing, generates input to the Mathematica program, and then formats the output for direct use in MATLAB and Simulink. A unified nonlinear control algorithm that controls the 3D MOVA system, including both the aircraft and the onboard manipulator, as a single entity was developed to achieve trajectory tracking of the MOVA end-effector position and attitude based on the explicit dynamics equation. Globally Uniformly Ultimately Bounded (GUUB) stability is proven for the controller using Lyapunov-type stability analysis. Physical testing was constructed in order to to demonstrate the performance of the proposed controller on a MOVA system with a two-link onboard manipulator

Preliminary Experiments in Real Time Distributed Robot Control

We investigate the computational needs of advanced real-time robot control. First, sampling rate issues in the control of nonlinear systems are discussed. Second, a representative nonlinear robot control algorithm using an explicit robot dynamical model is derived. Some typical terms of the exact equations are given for two industrial robot arms. Third, we define some performance criteria of interest in realtime control. Finally, we compare a variety of implementations of the above control algorithm on a network of INMOS Transputers

Slip Modelling, Estimation and Control of Omnidirectional Wheeled Mobile Robots with Powered Caster Wheels

Ph.DDOCTOR OF PHILOSOPH