Control strategy for cooperating disparate manipulators

To manipulate large payloads typical of space construction, the concept of a small arm mounted on the end of a large arm is introduced. The main purposes of such a configuration are to increase the structural stiffness of the robot by bracing against or locking to a stationary frame, and to maintain a firm position constraint between the robot's base and workpieces by grasping them. Possible topologies for a combination of disparate large and small arms are discussed, and kinematics, dynamics, controls, and coordination of the two arms, especially when they brace at the tip of the small arm, are developed. The feasibility and improvement in performance are verified, not only with analytical work and simulation results but also with experiments on the existing arrangement Robotic Arm Large and Flexible and Small Articulated Manipulator

Autonomous Mechanical Assembly on the Space Shuttle: An Overview

The space shuttle will be equipped with a pair of 50 ft. manipulators used to handle payloads and to perform mechanical assembly operations. Although current plans call for these manipulators to be operated by a human teleoperator. The possibility of using results from robotics and machine intelligence to automate this shuttle assembly system was investigated. The major components of an autonomous mechanical assembly system are examined, along with the technology base upon which they depend. The state of the art in advanced automation is also assessed

Force-directed control with a strong hydraulic manipulator

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.Includes bibliographical references (leaves 68-73).by Peter Carl Lefren Jaffe.M.Eng

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

Study of extravehicular protection and operations

Extravehicular protection and operation

Control of free-flying space robot manipulator systems

New control techniques for self contained, autonomous free flying space robots were developed and tested experimentally. Free flying robots are envisioned as a key element of any successful long term presence in space. These robots must be capable of performing the assembly, maintenance, and inspection, and repair tasks that currently require human extravehicular activity (EVA). A set of research projects were developed and carried out using lab models of satellite robots and a flexible manipulator. The second generation space robot models use air cushion vehicle (ACV) technology to simulate in 2-D the drag free, zero g conditions of space. The current work is divided into 5 major projects: Global Navigation and Control of a Free Floating Robot, Cooperative Manipulation from a Free Flying Robot, Multiple Robot Cooperation, Thrusterless Robotic Locomotion, and Dynamic Payload Manipulation. These projects are examined in detail

Real-Time Hybrid Visual Servoing of a Redundant Manipulator via Deep Reinforcement Learning

Fixtureless assembly may be necessary in some manufacturing tasks and environ-ments due to various constraints but poses challenges for automation due to non-deterministic characteristics not favoured by traditional approaches to industrial au-tomation. Visual servoing methods of robotic control could be effective for sensitive manipulation tasks where the desired end-effector pose can be ascertained via visual cues. Visual data is complex and computationally expensive to process but deep reinforcement learning has shown promise for robotic control in vision-based manipu-lation tasks. However, these methods are rarely used in industry due to the resources and expertise required to develop application-specific systems and prohibitive train-ing costs. Training reinforcement learning models in simulated environments offers a number of benefits for the development of robust robotic control algorithms by reducing training time and costs, and providing repeatable benchmarks for which algorithms can be tested, developed and eventually deployed on real robotic control environments. In this work, we present a new simulated reinforcement learning envi-ronment for developing accurate robotic manipulation control systems in fixtureless environments. Our environment incorporates a contemporary collaborative industrial robot, the KUKA LBR iiwa, with the goal of positioning its end effector in a generic fixtureless environment based on a visual cue. Observational inputs are comprised of the robotic joint positions and velocities, as well as two cameras, whose positioning reflect hybrid visual servoing with one camera attached to the robotic end-effector, and another observing the workspace respectively. We propose a state-of-the-art deep reinforcement learning approach to solving the task environment and make prelimi-nary assessments of the efficacy of this approach to hybrid visual servoing methods for the defined problem environment. We also conduct a series of experiments ex-ploring the hyperparameter space in the proposed reinforcement learning method. Although we could not prove the efficacy of a deep reinforcement approach to solving the task environment with our initial results, we remain confident that such an ap-proach could be feasible to solving this industrial manufacturing challenge and that our contributions in this work in terms of the novel software provide a good basis for the exploration of reinforcement learning approaches to hybrid visual servoing in accurate manufacturing contexts

Pneumatic motion control systems for modular robots

This thesis describes a research study in the design, implementation, evaluation and commercialisation of pneumatic motion control systems for modular robots. The research programme was conducted as part of a collaborative study, sponsored by the Science and Engineering Research Council, between Loughborough University and Martonair (UK) Limited. Microprocessor based motion control strategies have been used to produce low cost pneumatic servo-drives which can be used for 'point-to-point' positioning of payloads. Software based realtime control strategies have evolved which accomplish servo-controlled positioning while compensating for drive system non-linearities and time delays. The application of novel compensation techniques has resulted in a significant improvement in both the static and dynamic performance of the drive. A theoretical foundation is presented based on a linearised model of a pneumatic actuator, servo-valve, and load system. The thesis describes the design and evolution of microprocessor based hardware and software for motion control of pneumatic drives. A British Standards based test-facility has allowed control strategies to be evaluated with reference to standard performance criteria. It is demonstrated in this research study that the dynamic and static performance characteristics of a pneumatic motion control system can be dramatically improved by applying appropriate software based realtime control strategies. This makes the application of computer controlled pneumatic servos in manufacturing very attractive with cost performance ratios which match or better alternative drive technologies. The research study has led to commercial products (marketed by Martonair Ltd), in which realtime control algorithms implementing these control strategy designs are executed within a microprocessor based motion controller

Proceedings of the NASA Conference on Space Telerobotics, volume 3

The theme of the Conference was man-machine collaboration in space. The Conference provided a forum for researchers and engineers to exchange ideas on the research and development required for application of telerobotics technology to the space systems planned for the 1990s and beyond. The Conference: (1) provided a view of current NASA telerobotic research and development; (2) stimulated technical exchange on man-machine systems, manipulator control, machine sensing, machine intelligence, concurrent computation, and system architectures; and (3) identified important unsolved problems of current interest which can be dealt with by future research

Toward Vision-based Control of Heavy-Duty and Long-Reach Robotic Manipulators

Heavy-duty mobile machines are an important part of the industry, and they are used for various work tasks in mining, construction, forestry, and agriculture. Many of these machines have heavy-duty, long-reach (HDLR) manipulators attached to them, which are used for work tasks such as drilling, lifting, and grabbing. A robotic manipulator, by definition, is a device used for manipulating materials without direct physical contact by a human operator. HDLR manipulators differ from manipulators of conventional industrial robots in the sense that they are subject to much larger kinematic and non-kinematic errors, which hinder the overall accuracy and repeatability of the robot’s tool center point (TCP). Kinematic errors result from modeling inaccuracies, while non-kinematic errors include structural flexibility and bending, thermal effects, backlash, and sensor resolution. Furthermore, conventional six degrees of freedom (DOF) industrial robots are more general-purpose systems, whereas HDLR manipulators are mostly designed for special (or single) purposes. HDLR manipulators are typically built as lightweight as possible while being able to handle significant load masses. Consequently, they have long reaches and high payload-to-own-weight ratios, which contribute to the increased errors compared to conventional industrial robots. For example, a joint angle measurement error of 0.5◦ associated with a 5-m-long rigid link results in an error of approximately 4.4 cm at the end of the link, with further errors resulting from flexibility and other non-kinematic aspects. The target TCP positioning accuracy for HDLR manipulators is in the sub-centimeter range, which is very difficult to achieve in practical systems. These challenges have somewhat delayed the automation of HDLR manipulators, while conventional industrial robots have long been commercially available. This is also attributed to the fact that machines with HDLR manipulators have much lower production volumes, and the work tasks are more non-repetitive in nature compared to conventional industrial robots in factories. Sensors are a key requirement in order to achieve automated operations and eventually full autonomy. For example, humans mostly rely on their visual perception in work tasks, while the collected information is processed in the brain. Much like humans, autonomous machines also require both sensing and intelligent processing of the collected sensor data. This dissertation investigates new visual sensing solutions for HDLR manipulators, which are striving toward increased automation levels in various work tasks. The focus is on visual perception and generic 6 DOF TCP pose estimation of HDLR manipulators in unknown (or unstructured) environments. Methods for increasing the robustness and reliability of visual perception systems are examined by exploiting sensor redundancy and data fusion. Vision-aided control using targetless, motion-based local calibration between an HDLR manipulator and a visual sensor is also proposed to improve the absolute positioning accuracy of the TCP despite the kinematic and non-kinematic errors present in the system. It is experimentally shown that a sub-centimeter TCP positioning accuracy was reliably achieved in the tested cases using a developed trajectory-matching-based method. Overall, this compendium thesis includes four publications and one unpublished manuscript related to these topics. Two main research problems, inspired by the industry, are considered and investigated in the presented publications. The outcome of this thesis provides insight into possible applications and benefits of advanced visual perception systems for HDLR manipulators in dynamic, unstructured environments. The main contribution is related to achieving sub-centimeter TCP positioning accuracy for an HDLR manipulator using a low-cost camera. The numerous challenges and complexities related to HDLR manipulators and visual sensing are also highlighted and discussed