Title :
Robot Motion Planning Method Based on Deterministic Sampling
Author :
Hu, Yulan ; Zhang, Qisong
Author_Institution :
Sch. of Inf. Sci. & Eng., Shenyang Ligong Univ., Shenyang, China
Abstract :
With the robotic application of environmental complexity increasing, the traditional motion planning can not overcome the obstacles in the uncertainty space of the model and describe the problem, especially in an unknown environment, subject to environmental restrictions on the amount of information, the traditional sports planning algorithm may not run. Sampling-based motion planning is only through the configuration space of the sampling points to obtain obstacle collision detection information, to avoid running space, modeling, fully applicable to complex and unknown environment.
Keywords :
collision avoidance; multi-robot systems; sampling methods; uncertain systems; environmental complexity; environmental restrictions; obstacle collision detection; robot motion planning; sampling points; uncertainty space; deterministic sampling method; motion planning; unknown environment Introduction;
Conference_Titel :
Intelligent Networks and Intelligent Systems (ICINIS), 2010 3rd International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-8548-2
Electronic_ISBN :
978-0-7695-4249-2
DOI :
10.1109/ICINIS.2010.67