Control Framework for Hand-Arm Coordination

Co-ordination of multiple manipulators requires cooperation at several levels in the control hierarchy. A distributed processing environment with no hardware dependencies except at the motor servo level, would provide a flexible architecture for coordination. A system on these lines is being built to control an articulated hand and an arm. The four levels of control envisaged include a task decomposition level, a planning level, a scheduling level and a server level. The hand will carry both force and tactile sensors, feedback from these are used to provide adaptive control in grasping tasks. The processing of the sensory information is performed by independent processes, with analyzed information being sent to the relevant layer of the system. The manipulators are also controlled by individual processes. All process can open communications with an active process sending commands or data, or receiving them. We describe the scope of the system and the current setup plus future lines of development

RISC-based architectures for multiple robot systems

Several approaches to multiple robot system control are discussed. In order to simplify the study a multilayered model is proposed: a control layer which directly acts on the dynamics of the manipulators, a coordination/communication layer which makes all the manipulators work together and a programming layer which interfaces with the user. For the first layer two architectural alternatives are studied: a centralized single processor system and a distributed multiprocessor with static task assignment. For the second case an implementation based on the 1960 family of RISC processors is introduced. For the second layer three possibilities are considered: serial interface, parallel bus and local area network. The latter is carefully studied and a low cost alternative to the standard deterministic network MAP is introduced. This cell network is based on the CSMA/DCR protocol implemented on the i82596 coprocessor. Two alternatives are discussed for the programming layer: a parallel programming language based on a scene approach and a C extended language used to program elementary tasks in a robot independent way coupled with an intelligent scheduler used to assign these tasks to the robot arms at run time

A review of parallel processing approaches to robot kinematics and Jacobian

Due to continuously increasing demands in the area of advanced robot control, it became necessary to speed up the computation. One way to reduce the computation time is to distribute the computation onto several processing units. In this survey we present different approaches to parallel computation of robot kinematics and Jacobian. Thereby, we discuss both the forward and the reverse problem. We introduce a classification scheme and classify the references by this scheme

Robotics handbook. Version 1: For the interested party and professional

This publication covers several categories of information about robotics. The first section provides a brief overview of the field of Robotics. The next section provides a reasonably detailed look at the NASA Robotics program. The third section features a listing of companies and organization engaging in robotics or robotic-related activities; followed by a listing of associations involved in the field; followed by a listing of publications and periodicals which cover elements of robotics or related fields. The final section is an abbreviated abstract of referred journal material and other reference material relevant to the technology and science of robotics, including such allied fields as vision perception; three-space axis orientation and measurement systems and associated inertial reference technology and algorithms; and physical and mechanical science and technology related to robotics

Aspects of an open architecture robot controller and its integration with a stereo vision sensor.

The work presented in this thesis attempts to improve the performance of industrial robot systems in a flexible manufacturing environment by addressing a number of issues related to external sensory feedback and sensor integration, robot kinematic positioning accuracy, and robot dynamic control performance. To provide a powerful control algorithm environment and the support for external sensor integration, a transputer based open architecture robot controller is developed. It features high computational power, user accessibility at various robot control levels and external sensor integration capability. Additionally, an on-line trajectory adaptation scheme is devised and implemented in the open architecture robot controller, enabling a real-time trajectory alteration of robot motion to be achieved in response to external sensory feedback. An in depth discussion is presented on integrating a stereo vision sensor with the robot controller to perform external sensor guided robot operations. Key issues for such a vision based robot system are precise synchronisation between the vision system and the robot controller, and correct target position prediction to counteract the inherent time delay in image processing. These were successfully addressed in a demonstrator system based on a Puma robot. Efforts have also been made to improve the Puma robot kinematic and dynamic performance. A simple, effective, on-line algorithm is developed for solving the inverse kinematics problem of a calibrated industrial robot to improve robot positioning accuracy. On the dynamic control aspect, a robust adaptive robot tracking control algorithm is derived that has an improved performance compared to a conventional PID controller as well as exhibiting relatively modest computational complexity. Experiments have been carried out to validate the open architecture robot controller and demonstrate the performance of the inverse kinematics algorithm, the adaptive servo control algorithm, and the on-line trajectory generation. By integrating the open architecture robot controller with a stereo vision sensor system, robot visual guidance has been achieved with experimental results showing that the integrated system is capable of detecting, tracking and intercepting random objects moving in 3D trajectory at a velocity up to 40mm/s

A constructivist model of robot perception and performance

We present a new architecture for robot control rooted in notions from Brooks ' subsumption architecture and extended to include an internal representation which matures as it experiences the world. Our architecture is based on the Copycat program of Mitchell and Hofstadter, a model of fluid representation whose details we discuss. We show how our architecture develops a representation of its environment through a continuing interaction with it. The architecture is founded on a dynamical systems interpretation of representation and demonstrates the importance of the use of "embodiment". It reflects a constructivist epistemology, with the robot designed to utilize its environment in its exploration

Reinforcement Learning for Platform-Independent Visual Robot Control

www.his.sunderland.ac.uk Abstract—This paper proposes a new architecture for robot control. A test scenario is outlined to test the proposed system and enable a comparison with an existing system, which is able to fulfil the scenario and thus be used as a benchmark. The scenario is a navigation task, to allow a robot to approach a specified landmark. The proposed architecture will make use of two control units, one to allow a pan/tilt camera to track the landmark as the robot moves, and a second to control the robots drive motors. These units will be trained via reinforcement learning, and provide the potential for platformindependent robot control. I I