New PDF release: Algorithmic Foundations of Robotics X: Proceedings of the

By Kris Hauser (auth.), Emilio Frazzoli, Tomas Lozano-Perez, Nicholas Roy, Daniela Rus (eds.)

ISBN-10: 3642362788

ISBN-13: 9783642362781

ISBN-10: 3642362796

ISBN-13: 9783642362798

Algorithms are a primary component to robot structures. robotic algorithms method inputs from sensors that offer noisy and partial information, construct geometric and actual types of the realm, plan high-and low-level activities at varied time horizons, and execute those activities on actuators with restricted precision. The layout and research of robotic algorithms elevate a distinct mix of questions from many elds, together with keep watch over conception, computational geometry and topology, geometrical and actual modeling, reasoning below uncertainty, probabilistic algorithms, online game thought, and theoretical laptop science.

The Workshop on Algorithmic Foundations of Robotics (WAFR) is a single-track assembly of best researchers within the eld of robotic algorithms. on account that its inception in 1994, WAFR has been held any other yr, and has supplied one of many most appropriate venues for the booklet of a few of the eld's most crucial and lasting contributions.

This books comprises the complaints of the 10th WAFR, hung on June 13{15 2012 on the Massachusetts Institute of expertise. The 37 papers incorporated during this e-book conceal a huge diversity of themes, from basic theoretical matters in robotic movement making plans, keep watch over, and notion, to novel applications.

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Additional resources for Algorithmic Foundations of Robotics X: Proceedings of the Tenth Workshop on the Algorithmic Foundations of Robotics

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1 Runtime We have evaluated the framework on 1000 randomly generated NAMO environments. The size of the map was sampled uniformly to be between 250x250 and 400x400 grid cells. The number of obstacles for each map was uniformly sampled Hierarchical Decision Theoretic Planning for NAMO                        F5          F6 F3       F8 F10        F9 F2         F1                    33        (a) Obtained solution with zoom in on two local policies.

This alters the state-space of Mhl . While future work will investigate the applicability of policy iteration [16] to take advantage of the locality of the change, we address this by reexecuting the proposed algorithm after each object manipulation. Given the linear runtime of the algorithm, this has not presented a significant disadvantage. However, as the algorithm does not consider all possible future free space configurations, the Q-values for a specific Mhl do not represent the true long term expected reward of those regions, but rather an approximation based on the current world configuration.

In: Robotics: Science and Systems (RSS), Zaragoza, Spain (2010) 9. : Randomized kinodynamic planning. Int. J. Rob. Res. 20(5), 379–400 (2001) 10. : On the hardness of approximating minimization problems. J. of the ACM 41(5), 960–981 (1994) 11. : Proving path non-existence using sampling and alpha shapes. In: IEEE Int. Conf. Rob. Aut. (2012) 12. : An empirical study of phase transitions in binary constraint satisfaction problems. Artificial Intelligence 81(1-2), 81–109 (1996) The Minimum Constraint Removal Problem with Three Robotics Applications 17 13.

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Algorithmic Foundations of Robotics X: Proceedings of the Tenth Workshop on the Algorithmic Foundations of Robotics by Kris Hauser (auth.), Emilio Frazzoli, Tomas Lozano-Perez, Nicholas Roy, Daniela Rus (eds.)


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