A comparison of homotopic path planning algorithms for robotic applications

This paper addresses the path planning problem for robotic applications using homotopy classes. These classes provide a topological description of how paths avoid obstacles, which is an added value to the path planning problem. Homotopy classes are generated and sorted according to a lower bound heu...

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Detalles Bibliográficos
Autores: Hernàndez Bes, Emili, Carreras Pérez, Marc, Ridao Rodríguez, Pere
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/11331
Acceso en línea:http://hdl.handle.net/10256/11331
Access Level:acceso embargado
Palabra clave:Robots -- Moviment
Robots -- Motion
Homotopia, Teoria d'
Homotopy theory
Vehicles submergibles
Submersibles
Descripción
Sumario:This paper addresses the path planning problem for robotic applications using homotopy classes. These classes provide a topological description of how paths avoid obstacles, which is an added value to the path planning problem. Homotopy classes are generated and sorted according to a lower bound heuristic estimator using a method we developed. Then, the classes are used to constrain and guide path planning algorithms. Three different path planners are presented and compared: a graph-search algorithm called Homotopic A∗ (HA∗), a probabilistic sample-based algorithm called Homotopic RRT (HRRT), and a bug-based algorithm called Homotopic Bug (HBug). Our method has been tested in simulation and in an underwater bathymetric map to compute the trajectory of an Autonomous Underwater Vehicle (AUV). A comparison with well-known path planning algorithms has also been included. Results show that our homotopic path planners improve the quality of the solutions of their respective non-homotopic versions with similar computation time while keeping the topological constraints