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

An intelligent, free-flying robot

The ground based demonstration of the extensive extravehicular activity (EVA) Retriever, a voice-supervised, intelligent, free flying robot, is designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the Space Station. The major objective of the EVA Retriever Project is to design, develop, and evaluate an integrated robotic hardware and on-board software system which autonomously: (1) performs system activation and check-out; (2) searches for and acquires the target; (3) plans and executes a rendezvous while continuously tracking the target; (4) avoids stationary and moving obstacles; (5) reaches for and grapples the target; (6) returns to transfer the object; and (7) returns to base

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 344)

This bibliography lists 125 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during January, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Embodied neuromorphic intelligence

The design of robots that interact autonomously with the environment and exhibit complex behaviours is an open challenge that can benefit from understanding what makes living beings fit to act in the world. Neuromorphic engineering studies neural computational principles to develop technologies that can provide a computing substrate for building compact and low-power processing systems. We discuss why endowing robots with neuromorphic technologies – from perception to motor control – represents a promising approach for the creation of robots which can seamlessly integrate in society. We present initial attempts in this direction, highlight open challenges, and propose actions required to overcome current limitations

An artificial neural network for redundant robot inverse kinematics computation

A redundant manipulator can be defined as a manipulator that has more degrees of freedom than necessary to determine the position and orientation of the end effector. Such a manipulator has dexterity, flexibility, and the ability to maneuver in presence of obstacles. One important and necessary step in utilizing a redundant robot is to relate the joint coordinates of the manipulator with the position and orientation of the end-effector. This specification is termed as the direct kinematics problem and can be written as x = f(q) where x is a vector representing the position and orientation of the end-effector, q is the Joint vector, and f is a continuous non-linear function defined by the design of the manipulator. The inverse kinematics problem can be stated as: Given a position and orientation of the end-effector, determine the joint vector that specifies this position a q = f -1(x). and orientation. That is, For non-trivial designs, f -1 cannot be expressed analytically. This paper presents a solution to the inverse kinematics problem for a redundant robot based on multilayer feed-forward artificial neural network

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

Parallel algorithm and architecture for the control of kinematically redundant manipulators, A

Includes bibliographical references (pages 413-414).Kinematically redundant manipulators are inherently capable of more dexterous manipulation due to their additional degrees of freedom. To achieve this dexterity, however, one must be able to efficiently calculate the most desirable configuration from the infinite number of possible configurations that satisfy the end-effector constraint. It has been previously shown that the singular value decomposition (SVD) plays a crucial role in doing such calculations. In this work, a parallel algorithm for calculating the SVD is incorporated into a computational scheme for solving the equations of motion for kinematically redundant systems. This algorithm, which generalizes the damped least squares formulation to include solutions that utilize null-space projections and task prioritization as well as augmented or extended Jacobians, is then implemented on a simple linear array of processing elements. By taking advantage of the error bounds on the perturbation of the SVD, it is shown that an array of only four AT&T DSP chips can result in control cycle times of less than 3 ms for a seven degree-of-freedom manipulator

Overview of microoptics: Past, present, and future

Through advances in semiconductor miniaturization technology, microrelief patterns, with characteristic dimensions as small as the wavelength of light, can now be mass reproduced to form high-quality and low-cost optical components. In a unique example of technology transfer, from electronics to optics, this capability is allowing optics designers to create innovative optical components that promise to solve key problems in optical sensors, optical communication channels, and optical processors

HyperForest: A high performance multi-processor architecture for real-time intelligent systems

Intelligent Systems are characterized by the intensive use of computer power. The computer revolution of the last few years is what has made possible the development of the first generation of Intelligent Systems. Software for second generation Intelligent Systems will be more complex and will require more powerful computing engines in order to meet real-time constraints imposed by new robots, sensors, and applications. A multiprocessor architecture was developed that merges the advantages of message-passing and shared-memory structures: expendability and real-time compliance. The HyperForest architecture will provide an expandable real-time computing platform for computationally intensive Intelligent Systems and open the doors for the application of these systems to more complex tasks in environmental restoration and cleanup projects, flexible manufacturing systems, and DOE`s own production and disassembly activities

Efficient Parallel Algorithms and VLSI Architectures for Manipulator Jacobian Computation

Real-time computations of manipulator Jacobian are examined for executing on uniprocessor computers, parallel computers, and VLSI pipelines. The characteristics of the Jacobian equations are found to be in the form of the first-order linear recurrence. The time lower bound of computing the first-order linear recurrence, and hence the Jacobian, is of order O(N) on uniprocessor computers, and of order O(log2N) on parallel SIMD computers, where TV is the number of degrees-of-freedom of the manipulator. The Generalized-^ method, which achieves the time lower bound on uniprocessor computers, is derived to compute the Jacobian at any desired reference coordinate frame A; from the base coordinate frame to the end-effector coordinate frame. We find that if the reference coordinate frame k is in the range [3 , N—4], then the computational effort is the minimum. To reduce the computational complexity from the order of O (N) to O (log2N), we derive the parallel forward and backward recursive doubling algorithm to compute the Jacobian on parallel computers. Again, any reference coordinate frame k can be used, and the minimum computation occurs at k = (N—1)/2. To further reduce the Jacobian computation complexity, we design two VLSI systolic pipelined architectures. A linear VLSI pipe, which uses the least number of modular processors, takes 3N floating-point operations to compute the Jacobian, and a parallel VLSI pipe takes 3 floating-point operations. We also show that if the reference coordinate frame is selected at k — (N—1)/2, then the parallel pipe will require the least number of modular processors, and the communication paths are much shorter