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Showing papers on "Motion planning published in 1970"


Journal ArticleDOI
TL;DR: In this paper, the authors developed algorithms for optimal path planning that minimizes the disturbance to the satellite attitude and the satellite microgravity environment caused by satellite mounted robot operation, and solved the inverse kinetics problem with the attitude control system off.
Abstract: One of the most important problems in space based robotics is the disturbance to the satellite attitude and to the satellite microgravity environment caused by satellite mounted robot operation. This paper reports on the development of algorithms for optimal path planning that minimizes these disturbances, and solve the inverse kinetics problem, i.e. with the satellite attitude control system off. Specific optimality criteria are studied, including minimum induced angular velocity of the satellite and minimizing the maximum acceleration of the satellite center of mass. In addition, the space based analog is generated for the common ground based linear interpolation in joint or Cartesian space, i.e. shortest distance paths. Some properties of the various types of optimal paths are developed analytically, and understanding of the typical nature of the optimal paths is obtained in numerical examples. The shortest paths in principal planes, seen in inertial space, are shown to be arcs of circles. The computation required to produce such optimized trajectories is 1 or 2 minutes on a workstation, and methods can be used to substantially decrease this number if necessary. Thus, it can be practical to make use of these optimized path plans in space.

8 citations


Journal ArticleDOI
TL;DR: This tutorial is intended to present what robot motion planning is, what has been achieved through it so far, and what could be reasonably expected from it in the near future.
Abstract: Manipulation and motion are the most common means that we use to act directly on the world. Vision and language serve us as inputs and we communicate with other human beings using speech, but we act on our surroundings by moving and manipulating. If AI is to deal with real life problems, autonomous intelligent systems will have to interact with the world in the way humans do. This tutorial is intended to present what robot motion planning is, what has been achieved through it so far, and what could be reasonably expected from it in the near future. The attention will be focused more on techniques for real-life applications than on theoretical formulations. Emphasis is on robot manipulators rather than on isolated moving objects, distinguising applications in 2D and 3D. The tutorial is organized on a performance basis instead of the usual methodological clasification. Three levels of performance are distinguishedr(a) Geometric theoretical algorithms, (b) approaches that work at a computer simulation level and (c) techniques that have been implemented on actual robots, or which deal with problems for real-life robots. Some of the covered topics are: collision detection, fundamentals of the problem, geometric algorithms, basic motion planning techniques, moving obstacles, multiple robot coordination, nonholonomic motion, planning with uncertainty and future directions. Throughout the tutorial many examples and case studies will serve to illustrate successful applications as well as their underlying theoretical techniques. Transactions on Information and Communications Technologies vol 1, © 1993 WIT Press, www.witpress.com, ISSN 1743-3517

7 citations


Journal ArticleDOI
TL;DR: The path planning of a 5-degrees-of-freedom industrial robot appears to be reasonably fast and a known AI-method utilizing relaxed models is applied to generate admissible heuristics.
Abstract: In this paper, a point-to-point robot path planning problem is studied. It occurs in industry for example in spot welding, riveting, and pick and place tasks. A new A -based method is presented. The algorithm searches the robot's con guration space with many di erent resolutions at the same time. When a path candidate goes far from the obstacles, coarser resolutions corresponding to bigger step sizes is used. When it goes near the obstacle surfaces, ner resolutions corresponding to smaller step sizes is used. The algorithm always nds a path from a starting robot con guration to the goal con guration if one exists, which is a property of the A search in general. This is true given the nest resolution of the search space. These kind of path planning algorithms are called resolution complete in the robotics literature. A is also applied because of the possibility to generate better guiding heuristics. A better admissible heuristic roughly means that A using it expands fewer con guration space nodes, which is known a priori. A known AI-method utilizing relaxed models is applied to generate admissible heuristics. Constructing relaxed models involves removing details from the base level problem to get simpli ed ones. The heuristics are then obtained by solving these simpli ed problems. A simulated robot workcell is provided for demonstrations. The path planning of a 5-degrees-of-freedom industrial robot appears to be reasonably fast.

2 citations


Journal ArticleDOI
TL;DR: A method based on Evolution Strategies is used for the optimization of coordinated motion plans of manipulator robots, which can be easily implemented by programs written in any industrial robot programming language, such as VAL II.
Abstract: A method for obtaining coordinated motion plans of manipulator robots is presented. This planning can be easily implemented by programs written in any industrial robot programming language, such as VAL II. The generated programs minimize the total motion time of the robots along their paths, with some constraints directed at avoiding collision between the robots. A method based on Evolution Strategies is used for the optimization.

2 citations


Journal ArticleDOI
TL;DR: An algorithm which finds a robust path, if it exists, from a source point to a goal point for a non holonomic robot using the Multivalue Coding model is proposed.
Abstract: This paper deals with the problem of mobile path planning. We investigate the case for which the obstacle positions are well known but the mobile location is defined with uncertainties. We propose an algorithm which finds a robust path, if it exists, from a source point to a goal point for a non holonomic robot The proposed method is based on the Multivalue Coding model.

1 citations