Kris Hauser (auth.), Emilio Frazzoli, Tomas Lozano-Perez,'s Algorithmic Foundations of Robotics X: Proceedings of the PDF

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 basic part of robot platforms. robotic algorithms approach inputs from sensors that supply noisy and partial information, construct geometric and actual types of the area, plan high-and low-level activities at various time horizons, and execute those activities on actuators with constrained precision. The layout and research of robotic algorithms elevate a distinct mixture of questions from many elds, together with keep watch over idea, computational geometry and topology, geometrical and actual modeling, reasoning less than uncertainty, probabilistic algorithms, online game idea, and theoretical desktop science.

The Workshop on Algorithmic Foundations of Robotics (WAFR) is a single-track assembly of top researchers within the eld of robotic algorithms. considering its inception in 1994, WAFR has been held some other yr, and has supplied one of many most excellent venues for the e-book of a few of the eld's most crucial and lasting contributions.

This books includes the complaints of the 10th WAFR, hung on June 13{15 2012 on the Massachusetts Institute of expertise. The 37 papers integrated during this booklet disguise a huge variety of subject matters, from primary theoretical matters in robotic movement making plans, keep watch over, and conception, to novel applications.

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

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G. 03 and the best action to execute is to manipulate obstacle O3 to gain access to free space F6. Low level policies visualized as a vector field. Static obstacles visualized in gray. to be between 7 and 24, each obstacle in turn having random position, shape (rectangular or ellipsoid) and size (minimum 15x15 cells, maximum 65x65 cells occupation). Motion models P(δ x, δ y|all , c) were represented using Gaussians with their mean and standard deviation randomly varying for different categories.

Mishra, B. ) Algorithmic Foundation of Robotics VII. STAR, vol. 47, pp. 269–284. Springer, Heidelberg (2008) Hierarchical Decision Theoretic Planning for Navigation Among Movable Obstacles Martin Levihn, Jonathan Scholz, and Mike Stilman Abstract. In this paper we present the first decision theoretic planner for the problem of Navigation Among Movable Obstacles (NAMO). While efficient planners for NAMO exist, they are challenging to implement in practice due to the inherent uncertainty in both perception and control of real robots.

Artificial Intelligence 81(1-2), 81–109 (1996) The Minimum Constraint Removal Problem with Three Robotics Applications 17 13. : Complexity of the mover’s problem and generalizations. In: 20th Annual IEEE Symposium on Foundations of Computer Science, San Juan, Puerto Rico, pp. 421–427 (1979) 14. : Navigation among movable obstacles: Real-time reasoning in complex environments. International Journal of Humanoid Robotics 2(4) (December 2005) 15. : Approximation Algorithms. Springer (2001) 16. : A simple path non-existence algorithm using cobstacle query.

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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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