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Titel:

Balancing Exploration and Exploitation in Sampling-Based Motion Planning

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Rickert, Markus; Sieverling, Arne; Brock, Oliver
Abstract:
We present the exploring/exploiting tree (EET) algorithm for motion planning. The EET planner deliberately trades probabilistic completeness for computational efficiency. This tradeoff enables the EET planner to outperform state-of-the-art sampling-based planners by up to three orders of magnitude. We show that these considerable speedups apply for a variety of challenging real-world motion planning problems. The performance improvements are achieved by leveraging work space information to conti...     »
Zeitschriftentitel:
IEEE Transactions on Robotics
Jahr:
2014
Band / Volume:
30
Monat:
Dec
Heft / Issue:
6
Seitenangaben Beitrag:
1305--1317
Volltext / DOI:
doi:10.1109/TRO.2014.2340191
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