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

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

Algorithms are a basic portion of robot structures. robotic algorithms method inputs from sensors that offer noisy and partial info, 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 restricted precision. The layout and research of robotic algorithms elevate a special 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 thought, and theoretical computing device science.

The Workshop on Algorithmic Foundations of Robotics (WAFR) is a single-track assembly of prime researchers within the eld of robotic algorithms. considering its inception in 1994, WAFR has been held any other 12 months, and has supplied one of many most appropriate venues for the ebook of a few of the eld's most vital and lasting contributions.

This books includes the court cases 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 extensive variety of issues, from primary theoretical concerns in robotic movement making plans, keep an eye on, and conception, to novel applications.

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

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Sacks [14] computes the free space of two curved parts, in 2D or 3D, each of which rotates around or translates along a fixed axis. Complete path planning has been implemented robustly via exact computation (Sec. 6) for translating polygons [19], translating polyhedra [5], and polygons with translation along an axis and rotation [16]. There is extensive research on sample-based planning with narrow passages. The approach closest to ours is a hybrid algorithm [21] that approximates the free space with an octree comprised of free, blocked, and mixed cells, builds a graph of free configurations for each mixed cell, and links the graphs into a global approximation of free space.

A vertex, v, is a point, pv , and an outward normal, nv . An edge, e, is an open line segment or circular arc with tail vertex t = te and head vertex h = he such that nt × nh ≥ 0 (Fig. 4). A linear edge has normal ne = nt (= nh ), normal interval [ne , ne ], and curvature se = 0. A circular edge has normal interval (nt , nh ), angular extent at most π , center me , signed radius re , and curvature se = 1/re . It is convex if re > 0 and is concave otherwise. The part interior lies to the left when a linear or convex edge is traversed from t to h, or when a concave edge is traversed from h to t.

Circular edges enable one to model curved parts to a given accuracy with many fewer edges and permit one to work with level sets and rotational sweeps without approximation. Sacks [13] presents a precursor to our algorithm that computes type 3 criticalities (Sec. 3) approximately, is not output sensitive, and is not robust. Stappen et al [18] develop efficient path planning algorithms for a translating robot with mild input restrictions. Sacks [14] computes the free space of two curved parts, in 2D or 3D, each of which rotates around or translates along a fixed axis.

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