Sampling-Based Path Planning on Configuration-Space Costmaps

This paper addresses path planning to consider a cost function defined over the configuration space. The proposed planner computes low-cost paths that follow valleys and saddle points of the configuration-space costmap. It combines the exploratory strength of the Rapidly exploring Random Tree (RRT)...

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Veröffentlicht in:	IEEE transactions on robotics Jg. 26; H. 4; S. 635 - 646
Hauptverfasser:	Jaillet, Léonard, Cortés, Juan, Siméon, T
Format:	Journal Article Verlag
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.08.2010 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Applied sciences Artificial Intelligence Biological system modeling Classificació INSPEC Computational biology Computational modeling Computer Science Computer science; control theory; systems Control theory. Systems Cost function Costmap planning Criteria Cybernetics Exact sciences and technology Informàtica Intel·ligència artificial artificial Mathematical models Motion planning Optimization Optimization methods Orbital robotics Path planning path quality Planificació / Intel·ligència artificial Planning / Artificial intelligence Randomized algorithms Robotics robots Saddle points sampling-based motion planning Stochastic models Stochastic processes Stochasticity Testing Trees Valleys Àrees temàtiques de la UPC Quality criterion Path planning Real time Saddle point Robotics path quality Stochastic programming Optimal trajectory sampling-based motion planning Costmap planning Sampling Incomplete information Motion control
ISSN:	1552-3098, 1941-0468
Online-Zugang:	Volltext
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