Expert-guided kinodynamic RRT path planner for non-holonomic robots

Sanz, José María, Hernando Gutiérrez, Miguel ORCID: https://orcid.org/0000-0001-9997-0266, Zaragoza Prous, Guillermo and Brunete González, Alberto ORCID: https://orcid.org/0000-0001-9873-232X (2018). Expert-guided kinodynamic RRT path planner for non-holonomic robots. En: "2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018)", 01/10/2018 - 05/10/2018, Madrid, España. pp. 6540-6545. https://doi.org/10.1109/IROS.2018.8593924.

Descripción

Título: Expert-guided kinodynamic RRT path planner for non-holonomic robots
Autor/es:
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018)
Fechas del Evento: 01/10/2018 - 05/10/2018
Lugar del Evento: Madrid, España
Título del Libro: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Fecha: 2018
Materias:
ODS:
Escuela: E.T.S.I. Diseño Industrial (UPM)
Departamento: Ingeniería Eléctrica, Electrónica Automática y Física Aplicada
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

In this paper, an expert-guided kinodynamic RRT algorithm (EGK-RRT) is presented. It aims to consider how a human pilot would navigate a kinodynamic robot. One of the characteristics of this algorithm is the fact that, unlike the original RRT for kinodynamic systems, it generates deterministic control sequences which can be reproduced as long as the sequence of references (sampled states) are known. Here, the performance of the proposed algorithm is tested against the basic RRT, showing that the EGK-RRT greatly improves in terms of execution speed. In addition to this, the influence of using a visibility check and an inertia estimation in order to select the nearest neighbor is also analyzed, demonstrating that a combination of both factors leads to a better overall performance, both in execution speed and in quality of the generated path.

Más información

ID de Registro: 55191
Identificador DC: https://oa.upm.es/55191/
Identificador OAI: oai:oa.upm.es:55191
Identificador DOI: 10.1109/IROS.2018.8593924
URL Oficial: https://ieeexplore.ieee.org/document/8593924
Depositado por: Memoria Investigacion
Depositado el: 23 May 2019 10:11
Ultima Modificación: 03 Jun 2019 07:03