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Randomized path planning with preferences in highly complex dynamic environments

Published online by Cambridge University Press:  22 May 2013

Khaled Belghith ,
Froduald Kabanza  and
Leo Hartman
Khaled Belghith*
Affiliation:
University Of Sherbrooke, 2500, boul. de l'Université Sherbrooke, Québec J1K 2R1, Canada
Froduald Kabanza
Affiliation:
University Of Sherbrooke, 2500, boul. de l'Université Sherbrooke, Québec J1K 2R1, Canada
Leo Hartman
Affiliation:
Canadian Space Agency, John H. Chapman Space Centre, 6767 Route de l'Aéroport Saint-Hubert, Québec J3Y 8Y9, Canada
*
*Corresponding author. E-mail: [email protected]
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Summary

In this paper we consider the problem of planning paths for articulated bodies operating in workplaces containing obstacles and regions with preferences expressed as degrees of desirability. Degrees of desirability could specify danger zones and desire zones. A planned path should not collide with the obstacles and should maximize the degrees of desirability. Region desirability can also convey search-control strategies guiding the exploration of the search space. To handle desirability specifications, we introduce the notion of flexible probabilistic roadmap (flexible PRM) as an extension of the traditional PRM. Each edge in a flexible PRM is assigned a desirability degree. We show that flexible PRM planning can be achieved very efficiently with a simple sampling strategy of the configuration space defined as a trade-off between a traditional sampling oriented toward coverage of the configuration space and a heuristic optimization of the path desirability degree. For path planning problems in dynamic environments, where obstacles and region desirability can change in real time, we use dynamic and anytime search exploration strategies. The dynamic strategy allows the planner to replan efficiently by exploiting results from previous planning phases. The anytime strategy starts with a quickly computed path with a potentially low desirability degree which is then incrementally improved depending on the available planning time.

Keywords

RoboticsPath planningReplanningAnytime planningDynamic planning
Type
Articles
Information
Robotica , Volume 31 , Issue 8 , December 2013 , pp. 1195 - 1208
Copyright
Copyright © Cambridge University Press 2013 

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