NASA Center for Intelligent Robotic Systems for Space Exploration

NASA's program for the civilian exploration of space is a challenge to scientists and engineers to help maintain and further develop the United States' position of leadership in a focused sphere of space activity. Such an ambitious plan requires the contribution and further development of many scientific and technological fields. One research area essential for the success of these space exploration programs is Intelligent Robotic Systems. These systems represent a class of autonomous and semi-autonomous machines that can perform human-like functions with or without human interaction. They are fundamental for activities too hazardous for humans or too distant or complex for remote telemanipulation. To meet this challenge, Rensselaer Polytechnic Institute (RPI) has established an Engineering Research Center for Intelligent Robotic Systems for Space Exploration (CIRSSE). The Center was created with a five year $5.5 million grant from NASA submitted by a team of the Robotics and Automation Laboratories. The Robotics and Automation Laboratories of RPI are the result of the merger of the Robotics and Automation Laboratory of the Department of Electrical, Computer, and Systems Engineering (ECSE) and the Research Laboratory for Kinematics and Robotic Mechanisms of the Department of Mechanical Engineering, Aeronautical Engineering, and Mechanics (ME,AE,&M), in 1987. This report is an examination of the activities that are centered at CIRSSE

Design and Implementation of a Robot Force and Motion Server

A robot manipulator is a force and motion server for a robot. The robot, interpreting sensor information in terms of a world model and a task plan, issues instructions to the manipulator to carry out tasks. The control of a manipulator first involves motion trajectory generation needed when the manipulator is instructed to move to desired positions. The procedure of generating the trajectory must be flexible and efficient. When the manipulator comes into contact with the environment such as during assembly, it must be able to comply with the geometric constraints presented by the contact in order to perform tasks successfully. The control strategies for motion and compliance are executed in real time by the control computer, which must be powerful enough to carry out the necessary computations. This thesis first presents an efficient method for manipulator motion planning. Two fundamental modes of motion, Cartesian and joint, are considered and transition between motion segments is uniformly treated to obtain an efficient and simple system. A modified hybrid control method for manipulator compliance is then proposed and implemented. The method overcomes the problems existing in previous approaches such as stiffness control and hybrid control. Finally, a controller architecture is studied to distribute computations into a number of processors to satisfy the computational requirement in a cost-effective manner. The implementation using Intel\u27s single board computers is also discussed. Finally, to demonstrate the system, the motion trajectory. and the modified forced/motion control scheme are implemented on the controller and a PUMA 260 manipulator controlled from a multi-user VAX/Unix system through an Ethernet interface

DETC2005-84349 HYBRID TARGET TRACKING MANIPULATION THEORIES FOR COMBINED FORCE AND POSITION CONTROL IN OPEN AND CLOSED LOOP MANIPULATORS

ABSTRACT This paper presents a new manipulation theory for controlling compliant motions of a robotic manipulator. In previous closed loop control methods, both direct kinematics and inverse kinematics of a manipulator must be resolved to convert feedback force and position data from Cartesian space to joint space. However, in many cases, the solution of direct kinematics in a parallel manipulator or the solution of inverse kinematics in a serial manipulator is not easily available. In this study, the force and position data are packed into one set of "motion feedback," by replacing the force errors with virtual motion quantities, or one set of "force feedback," by replacing motion errors with virtual force quantities. The joint torques are adjusted based on this combined feed back package. Since only Jacobian of direct kinematics or Jacobian of inverse kinematics is used in the control scheme, the computational complexity is reduced significantly. The applications of this theory are demonstrated in simulation experiments with both serial and parallel manipulators. KEYWORDS Target tracking, open loop, closed loop, manipulation, hybrid control INTRODUCTION In many applications such as deburring, grinding, scribing and contour following, a manipulator is required to follow a predefined position trajectory in the tangent direction of a surface while maintaining a contact force in the normal direction. These tasks need appropriate control of motion and force. In the beginning, a typical force control strategy was used to command an actuator torque. This strategy combined feedback of force with feedback of position (and velocity) and corrected the error through a common controlle

SYMORO+: A SYSTEM FOR THE SYMBOLIC MODELLING OF ROBOTS

International audienceThis paper presents the software package SYMORO+ for the automatic symbolic modelling of robots. This package permits to generate the direct geometric model, the inverse geometric model, the direct kinematic model, the inverse kinematic model, the dynamic model, and the inertial parameters identification models. The structure of the robots can be serial, tree structure or containing closed loops. The package runs on Sun stations and PC computers, it has been developed under MATHEMATICA and C language. In this paper we give an overview of the algorithms used in the different models, the computational cost of the dynamic models of the PUMA robot are given

Inertial-space disturbance rejection for robotic manipulators

The disturbance rejection control problem for a 6-DOF (degree of freedom) PUMA manipulator mounted on a 3-DOF platform is investigated. A control algorithm is designed to track the desired position and attitude of the end-effector in inertial space, subject to unknown disturbances in the platform axes. Conditions for the stability of the closed-loop system are derived. The performance of the controller is compared for step, sinusoidal, and random disturbances in the platform rotational axis and in the neighborhood of kinematic singularities

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

Evaluation of automated decisionmaking methodologies and development of an integrated robotic system simulation

A generic computer simulation for manipulator systems (ROBSIM) was implemented and the specific technologies necessary to increase the role of automation in various missions were developed. The specific items developed are: (1) capability for definition of a manipulator system consisting of multiple arms, load objects, and an environment; (2) capability for kinematic analysis, requirements analysis, and response simulation of manipulator motion; (3) postprocessing options such as graphic replay of simulated motion and manipulator parameter plotting; (4) investigation and simulation of various control methods including manual force/torque and active compliances control; (5) evaluation and implementation of three obstacle avoidance methods; (6) video simulation and edge detection; and (7) software simulation validation

Applications of parallel computing in robotics problems

"December 2013.""A Thesis presented to the Faculty of the Graduate School University of Missouri In Partial Fulfillment Of the Requirements for the Degree Master of Science."Thesis advisor: Dr. Guilherme N. DeSouza.Many typical robotics problems involve search in high-dimensional spaces, where real-time execution is hard to be achieved. This thesis presents two case studies of parallel computation in such robotics problems. More specifically, two problems of motion planning-the Inverse Kinematics of robotic manipulators and Path Planning for mobile robots-are investigated and the contributions of parallel algorithms are highlighted. For the Inverse Kinematics problem, a novel and fast solution is proposed for general serial manipulators. This new approach relies on the computation of multiple (parallel) numerical estimations of the inverse Jacobian while it selects the current best path to the desire con- figuration of the end-effector. Unlike other iterative methods, our method converges very quickly, achieving sub-millimeter accuracy in 20.48ms in average. We demonstrate such high accuracy and the real-time performance of our method by testing it with six different robots, at both non-singular and singular configurations, including a 7-DoF redundant robot. The algorithm is implemented in C/C++ using a configurable number of POSIX threads, and it can be easily expanded to use many-core GPUs. For the Path Planning problem, a solution to the problem of smooth path planning for mobile robots in dynamic and unknown environments is presented. A novel concept of Time-Warped Grids is introduced to predict the pose of obstacles on a grid-based map and avoid collisions. The algorithm is implemented using C/C++ and the CUDA programming environment, and combines stochastic estimation (Kalman filter), Harmonic Potential Fields and a Rubber Band model, and it translates naturally into the parallel paradigm of GPU programing. The proposed method was tested using several simulation scenarios for the Pioneer P3- DX robot, which demonstrated the robustness of the algorithm by finding the optimum path in terms of smoothness, distance, and collision-free either in static or dynamic environments, even with a very large number of obstacles.Includes bibliographical references (pages 70-78)