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Title:
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HG-RRT*: Human-Guided Optimal Random Trees for Motion Planning
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Author:
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García Hidalgo, Néstor; Suárez Feijóo, Raúl; Rosell Gratacòs, Jan
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Other authors:
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Universitat Politècnica de Catalunya. Institut d'Organització i Control de Sistemes Industrials; Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial; Universitat Politècnica de Catalunya. SIR - Service and Industrial Robotics |
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Abstract:
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Fumio Harashima Best Paper Award in Emerging Technologies, a la 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA 2015) |
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Abstract:
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The paper deals with the problem of designing an RRT*-based planning algorithm that allows the user to guide the tree growth in a simple and transparent way. The key idea of the proposal is to create a planning algorithm, called HG-RRT*, that minimizes an optimization function over the configuration space where a state cost function is established. This state cost is defined as the combination of several potential fields. Each of
these potential fields will attract the solution path or move it away from certain areas. The planning algorithm will try to minimize the path length, the motion effort and the variations of the cost along the path. The paper presents a description of the proposed approach as well as simulation results from a conceptual and an application example, including a thorough comparison with the TRRT planning algorithm. |
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Abstract:
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Award-winning |
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Subject(s):
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-Àrees temàtiques de la UPC::Informàtica::Robòtica
-Robots -- Motion
-Robots -- Moviment |
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Rights:
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Document type:
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Article - Submitted version
Conference Object |
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Published by:
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Institute of Electrical and Electronics Engineers (IEEE)
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