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Titlebook: Algorithmic Foundations of Robotics VI; Michael Erdmann,Mark Overmars,Frank der Stappen Book 2005 Springer-Verlag Berlin Heidelberg 2005 D

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Locating and Capturing an Evader in a Polygonal Environment,rsuer. Second, using the randomized algorithm together with the solution of a known lion and man problem [12] as subroutines, we present a strategy for two pursuers (one of which is at least as fast as the evader) to quickly capture an evader in a simply-connected polygonal environment.
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Book 2005iplinary field of robotics. ..This volume consists of selected contributions to the sixth Workshop on the Algorithmic Foundations of Robotics. This is a highly competitive meeting of experts in the field of algorithmic issues related to robotics and automation. .
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1610-7438 stractions of computational processes that control or reason about motion and perception in the physical world. Because actions in the physical world are subject to physical laws and geometric constraints, the design and analysis of robot algorithms raise a unique combination of questions in control
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Glencora Sharfman MD,Ursula K. Braun MD, MPHing obstacle avoidance and essentially global convergence. The composition law is associative, and successive compositions fold into a single, computational simple expression, enabling the practical construction of NFs on the Cartesian product of several manifolds.
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The Structures of Society and Depressionsible. However, for . obstacles (those defined by pairwise interactions), we prove a finite bound on the number of optimal coordinations. For such systems, we present an exact algorithm for reducing a coordination scheme to its Pareto optimal representative.
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Multi-Step Motion Planning for Free-Climbing Robots,based technique. However, experimental results point toward a better approach, incorporating the ability to detect when one-step motions are infeasible (i.e., to prove disconnection). Current work on a general method for doing this, based on recent advances in computational real algebra, is also presented.
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Sampling-Based Motion Planning under Kinematic Loop-Closure Constraints,eral subsets with complex and a priori unknown topology. Sampling-based motion planning algorithms cannot be directly applied to such closed-chain systems. This paper describes our recent work [7] on the extension of sampling-based planners to treat this kind of mechanisms.
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