Application of predictive control for manipulator mounted on a satellite

Specific conditions of on-orbit environment are taken into account in the design of all devices intended to be used in space. Despite this fact malfunctions of satellites occur and sometimes lead to shortening of the satellite operational lifetime. It is considered to use unmanned servicing satellite, that could perform repairs of other satellites. Such satellites equipped with a manipulator, could be used to capture and remove from orbit large space debris. The critical part of planned missions is the capture manoeuvre. In this paper a concept of the control system for the manipulator mounted on the satellite is presented. This control system is composed of the trajectory planning module and model predictive controller (the latter is responsible for ensuring precise realization of the planned trajectory). Numerical simulations performed for the simplified planar case with a 2 DoF manipulator show that the results obtained with the predictive control are better than the results obtained with adaptive control method

Robotic Manipulation and Capture in Space: A Survey

Space exploration and exploitation depend on the development of on-orbit robotic capabilities for tasks such as servicing of satellites, removing of orbital debris, or construction and maintenance of orbital assets. Manipulation and capture of objects on-orbit are key enablers for these capabilities. This survey addresses fundamental aspects of manipulation and capture, such as the dynamics of space manipulator systems (SMS), i.e., satellites equipped with manipulators, the contact dynamics between manipulator grippers/payloads and targets, and the methods for identifying properties of SMSs and their targets. Also, it presents recent work of sensing pose and system states, of motion planning for capturing a target, and of feedback control methods for SMS during motion or interaction tasks. Finally, the paper reviews major ground testing testbeds for capture operations, and several notable missions and technologies developed for capture of targets on-orbit

Modeling and Control of a Flexible Space Robot to Capture a Tumbling Debris

RÉSUMÉ La conquête spatiale des 60 dernières années a généré une grande quantité d’objets à la dérive sur les orbites terrestres. Leur nombre grandissant constitue un danger omniprésent pour l’exploitation des satellites, et requiert aujourd’hui une intervention humaine pour réduire les risques de collision. En effet, l’estimation de leur croissance sur un horizon de 200 ans, connue sous le nom de “syndrôme de Kessler”, montre que l’accès à l’Espace sera grandement menacé si aucune mesure n’est prise pour endiguer cette prolifération. Le scientifique J.-C. Liou de la National Aeronautics and Space Administration (NASA) a montré que la tendance actuelle pourrait être stabilisée, voire inversée, si au moins cinq débris massifs étaient désorbités par an, tels que des satellites en fin de vie ou des étages supérieurs de lanceur. Parmi les nombreux concepts proposés pour cette mission, la robotique s’est imposée comme une des solutions les plus prometteuses grâce aux retours d’expérience des 30 dernières années. La Station Spatiale Internationale (ISS) possède déjà plusieurs bras robotiques opérationnels, et de nombreuses missions ont démontré le potentiel d’un tel système embarqué sur un satellite. Pour deux d’entre elles, des étapes fondamentales ont été validées pour le service en orbite,et s’avèrent être similaires aux problématiques de la désorbitation des débris. Cette thèse se concentre sur l’étape de capture d’un débris en rotation par un bras robotique ayant des segments flexibles. Cette phase comprend la planification de trajectoire et le contrôle du robot spatial, afin de saisir le point cible du débris de la façon la plus délicate possible. La validation des technologies nécessaires à un tel projet est quasiment impossible sur Terre, et requiert des moyens démesurés pour effectuer des essais en orbite. Par conséquent, la modélisation et la simulation de systèmes multi-corps flexibles est traitée en détails, et constitue une forte contribution de la thèse. À l’aide de ces modèles, une validation mixte est proposée par des essais expérimentaux, en reproduisant la cinématique en orbite par des manipulateurs industriels contrôlés par une simulation en temps réel. En résumé, cette thèse est construite autour des trois domaines suivants : la modélisation des robots spatiaux, le design de lois de contrôle, et leur validation sur un cas test. Dans un premier temps, la modélisation de robots spatiaux en condition d’apesanteur est développée pour une forme “en étoile”.----------ABSTRACT After 60 years of intensive satellite launches, the number of drifting objects in Earth orbits is reaching a shifting point, where human intervention is becoming necessary to reduce the threat of collision. Indeed, a 200 year forecast, known as the “Kessler syndrome”, states that space access will be greatly compromised if nothing is done to address the proliferation of these debris. Scientist J.-C. Liou from the National Aeronautics and Space Administration (NASA) has shown that the current trend could be reversed if at least five massive objects, such as dead satellites or rocket upper stages, were de-orbited each year. Among the various technical concepts considered for debris removal, robotics has emerged, over the last 30 years, as one of the most promising solutions. The International Space Station (ISS) already possesses fully operational robotic arms, and other missions have explored the potential of a manipulator embedded onto a satellite. During two of the latter, key capabilities have been demonstrated for on-orbit servicing, and prove to be equally useful for the purpose of debris removal. This thesis focuses on the close range capture of a tumbling debris by a robotic arm with light-weight flexible segments. This phase includes the motion planning and the control of a space robot, in order to smoothly catch a target point on the debris. The validation of such technologies is almost impossible on Earth and leads to prohibitive costs when performed on orbit. Therefore, the modeling and simulation of flexible multi-body systems has been investigated thoroughly, and is likewise a strong contribution of the thesis. Based on these models, an experimental validation is proposed by reproducing the on-orbit kinematics on a test bench made up of two industrial manipulators and driven by a real-time dynamic simulation. In a nutshell, the thesis is built around three main parts: the modeling of a space robot, the design of control laws, and their validation on a test case. The first part is dedicated to the flexible modeling of a space robot in conditions of weightlessness. A “star-shaped” multi-body system is considered, meaning that the rigid base carries various flexible appendages and robotic arms, assumed to be open mechanical chains only. The classic Newton-Euler and Lagrangian algorithms are brought together to account for the flexibility and to compute the dynamics in a numerically efficient way. The modeling step starts with the rigid fixed-base manipulators in order to introduce the notations, then, détails the flexible ones, and ends with the moving-base system to represent the space robots

Implications of Motion Planning: Optimality and k-survivability

We study motion planning problems, finding trajectories that connect two configurations of a system, from two different perspectives: optimality and survivability. For the problem of finding optimal trajectories, we provide a model in which the existence of optimal trajectories is guaranteed, and design an algorithm to find approximately optimal trajectories for a kinematic planar robot within this model. We also design an algorithm to build data structures to represent the configuration space, supporting optimal trajectory queries for any given pair of configurations in an obstructed environment. We are also interested in planning paths for expendable robots moving in a threat environment. Since robots are expendable, our goal is to ensure a certain number of robots reaching the goal. We consider a new motion planning problem, maximum k-survivability: given two points in a stochastic threat environment, find n paths connecting two given points while maximizing the probability that at least k paths reach the goal. Intuitively, a good solution should be diverse to avoid several paths being blocked simultaneously, and paths should be short so that robots can quickly pass through dangerous areas. Finding sets of paths with maximum k-survivability is NP-hard. We design two algorithms: an algorithm that is guaranteed to find an optimal list of paths, and a set of heuristic methods that finds paths with high k-survivability

NASA Automated Rendezvous and Capture Review. A compilation of the abstracts

This document presents a compilation of abstracts of papers solicited for presentation at the NASA Automated Rendezvous and Capture Review held in Williamsburg, VA on November 19-21, 1991. Due to limitations on time and other considerations, not all abstracts could be presented during the review. The organizing committee determined however, that all abstracts merited availability to all participants and represented data and information reflecting state-of-the-art of this technology which should be captured in one document for future use and reference. The organizing committee appreciates the interest shown in the review and the response by the authors in submitting these abstracts

Advanced Mobile Robotics: Volume 3

Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications

Heterogeneous Self-Reconfiguring Robotics: Ph.D. Thesis Proposal

Self-reconfiguring robots are modular systems that can change shape, or reconfigure, to match structure to task. They comprise many small, discrete, often identical modules that connect together and that are minimally actuated. Global shape transformation is achieved by composing local motions. Systems with a single module type, known as homogeneous systems, gain fault tolerance, robustness and low production cost from module interchangeability. However, we are interested in heterogeneous systems, which include multiple types of modules such as those with sensors, batteries or wheels. We believe that heterogeneous systems offer the same benefits as homogeneous systems with the added ability to match not only structure to task, but also capability to task. Although significant results have been achieved in understanding homogeneous systems, research in heterogeneous systems is challenging as key algorithmic issues remain unexplored. We propose in this thesis to investigate questions in four main areas: 1) how to classify heterogeneous systems, 2) how to develop efficient heterogeneous reconfiguration algorithms with desired characteristics, 3) how to characterize the complexity of key algorithmic problems, and 4) how to apply these heterogeneous algorithms to perform useful new tasks in simulation and in the physical world. Our goal is to develop an algorithmic basis for heterogeneous systems. This has theoretical significance in that it addresses a major open problem in the field, and practical significance in providing self-reconfiguring robots with increased capabilities