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Costmap planning in high dimensional configuration spaces

Romain Iehl 1 Juan Cortés 1 Thierry Simeon 1
1 LAAS-RIS - Équipe Robotique et InteractionS
LAAS - Laboratoire d'analyse et d'architecture des systèmes
Abstract : For many applications, path planning algorithms are expected to compute not only feasible paths, but good-quality solutions with respect to a cost function defined over the configuration space. Although several algorithms have been proposed recently for computing good-quality paths, their practical applicability is mostly limited to low-dimensional problems. This paper extends the applicability of one of such algorithms, T-RRT, to higher-dimensional problems. To this end, we propose to introduce ideas from the ML-RRT algorithm, which can efficiently solve high-dimensional path planning problems by relying on a hierarchical partitioning of the configuration space parameters. Simulation results show the good performance of the new costmap planner, MLT-RRT, for solving problems involving up to several hundreds of degrees of freedom.
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Submitted on : Tuesday, January 15, 2019 - 5:37:41 PM
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  • HAL Id : hal-01982586, version 1


Romain Iehl, Juan Cortés, Thierry Simeon. Costmap planning in high dimensional configuration spaces. IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Jul 2012, Kachsiung, Taiwan. ⟨hal-01982586⟩



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