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[資源]
[F]Robot Motion Planning and Control.Springer.1998
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Robot Motion Planning and Control 免責(zé)聲明 本資源來(lái)自于互聯(lián)網(wǎng)，僅供網(wǎng)絡(luò)測(cè)試之用，請(qǐng)務(wù)必在下載后24小時(shí)內(nèi)刪除！所有資源不涉及任何商業(yè)用途。發(fā)帖人不承擔(dān)由下載使用者引發(fā)的一切法律責(zé)任及連帶責(zé)任！ 著作權(quán)歸原作者或出版社所有。未經(jīng)發(fā)貼人許可，嚴(yán)禁任何人以任何形式轉(zhuǎn)貼本文，違者必究！ 如果本帖侵犯您的著作權(quán)，請(qǐng)與發(fā)貼人聯(lián)系，收到通知后我們將立即刪除此帖！ Authors(Editors): J.-P. Laumond Publisher: Springer Pub Date: 1998 Pages: 354 ISBN: 9783540762195 Foreword How can a robot decide what motions to perform in order to achieve tasks in the physical world ? The existing industrial robot programming systems still have very limited motion planning capabilities. Moreover the field of robotics is growing: space exploration, undersea work, intervention in hazardous environments, servicing robotics ... Motion planning appears as one of the components for the necessary autonomy of the robots in such real contexts. It is also a fundamental issue in robot simulation software to help work cell designers to determine collision free paths for robots performing specific tasks. Robot Motion Planning and Control requires interdisciplinarity The research in robot motion planning can be traced back to the late 60's, during the early stages of the development of computer-controlled robots. Nevertheless, most of the effort is more recent and has been conducted during the 80's (Robot Motion Planning, J.C. Latombe's book constitutes the reference in the domain). The position (configuration) of a robot is normally described by a number of variables. For mobile robots these typically are the position and orientation of the robot (i.e. 3 variables in the plane). For articulated robots (robot arms) these variables are the positions of the different joints of the robot arm. A motion for a robot can, hence, be considered as a path in the configuration space. Such a path should remain in the subspace of configurations in which there is no collision between the robot and the obstacles, the so-called free space. The motion planning problem asks for determining such a path through the free space in an efficient way. Motion planning can be split into two classes. When all degrees of freedom can be changed independently (like in a fully actuated arm) we talk about hotonomic motion planning. In this case, the existence of a collision-free path is characterized by the existence of a connected component in the free configuration space. In this context, motion planning consists in building the free configuration space, and in finding a path in its connected components. Within the 80's, Roboticians addressed the problem by devising a variety of heuristics and approximate methods. Such methods decompose the configuration space into simple cells lying inside, partially inside or outside the free space. A collision-free path is then searched by exploring the adjacency graph of free cells. In the early 80's, pioneering works showed how to describe the free configuration space by algebraic equalities and inequalities with integer coefficients (i.e. as being a semi-algebraic set). Due to the properties of the semi-algebraic sets induced by the Tarski-Seidenberg Theorem, the connectivity of the free configuration space can be described in a combinatorial way. From there, the road towards methods based on Real Algebraic Geometry was open. At the same time, Computational Geometry has been concerned with combinatorial bounds and complexity issues. It provided various exact and efficient methods for specific robot systems, taking into account practical constraints (like environment changes). More recently, with the 90's, a new instance of the motion planning problem has been considered: planning motions in the presence of kinematic constraints (and always amidst obstacles). When the degrees of freedom of a robot system are not independent (like e.g. a car that cannot rotate around its axis without also changing its position) we talk about nonholonomic motion planning. In this case, any path in the free configuration space does not necessarily correspond to a feasible one. Nonholonomic motion planning turns out to be much more difficult than holonomic motion planning. This is a fundamental issue for most types of mobile robots. This issue attracted the interest of an increasing number of research groups. The first results have pointed out the necessity of introducing a Differential Geometric Control Theory framework in nonholonomic motion planning. On the other hand, at the motion execution level, nonholonomy raises another difficulty: the existence of stabilizing smooth feedback is no more guaranteed for nonholonomic systems. Tracking of a given reference trajectory computed at the planning level and reaching a goal with accuracy require nonstandard feedback techniques. Four main disciplines are then involved in motion planning and control. However they have been developed along quite different directions with only little interaction. The coherence and the originality that make motion planning and control a so exciting research area come from its interdisciplinarity. It is necessary to take advantage from a common knowledge of the different theoretical issues in order to extend the state of the art in the domain. 本資源鏈接友情奉送，共3個(gè)可選網(wǎng)絡(luò)硬盤鏈接，19.5 MB，免積分資源不提供保質(zhì)。 -------------------------------------------------------------------------------------------------------- |
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