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Nonprobabilistic anytime algorithm for high-quality trajectories in high-dimensional spaces

Published online by Cambridge University Press:  23 June 2011

Andrés S. Vázquez  and
Antonio Adán
Andrés S. Vázquez*
Affiliation:
Escuela Superior de Informática, Universidad de Castilla-La Mancha, Paseo de la Universidad, 4, 13071, Ciudad Real, Spain E-mail: antonio.adan@uclm.es
Antonio Adán
Affiliation:
Escuela Superior de Informática, Universidad de Castilla-La Mancha, Paseo de la Universidad, 4, 13071, Ciudad Real, Spain E-mail: antonio.adan@uclm.es
*
*Corresponding author. E-mail: andress.vazquez@uclm.es
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Summary

This paper proposes a feasible variation of approximate grid-based path-planning methods, which have been replaced with probabilistic methods nowadays, due mainly to their impracticality in high-dimensional spaces. Our aim is to demonstrate that, with an incremental exploration of the CSpace by means of Interpolated walk primitives and ANY-Time algorithms, we can generate – online – high-quality solutions that can be compared with probabilistic methods and can even improve some aspects, such as the completeness. Computational time, path smoothness, path clearance, and path distance are the qualifiers used to evaluate the path planner. These quality factors are critical in robotics. In fact, in both mobile and industrial robots, the computational time is a primary requirement to work online, the clearance gives security to the movements of the robot, and the smoothness can prolong the life of the mechanical components. Our method has been compared to probabilistic path planners, with the feasibility and benefits of our algorithm being proved in terms of the quality factors aforementioned.

Keywords

Path planningAnytime algorithms

Information

Type
Articles
Information
Robotica , Volume 30 , Issue 2 , March 2012 , pp. 289 - 303
Copyright
Copyright © Cambridge University Press 2011

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