Multi-Heuristic A*
Sandip Aine, Siddharth Swaminathan, Venkatraman Narayanan, Victor Hwang, Maxim Likhachev
Abstract
Sandip Aine, Siddharth Swaminathan, Venkatraman Narayanan, Victor Hwang, Maxim Likhachev
Abstract
We present a novel heuristic search framework, called Multi-Heuristic A* (MHA*), that simultaneously uses multiple, arbitrarily inadmissible heuristic functions and one consistent heuristic to search for complete and bounded suboptimal solutions. This simplifies the de- sign of heuristics and enables the search to effectively combine the guiding powers of different heuristic func- tions. We support these claims with experimental results on full-body manipulation for PR2 robots.
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We present a novel heuristic search framework, called Multi-Heuristic A* (MHA*), that simultaneously uses multiple, arbitrarily inadmissible heuristic functions and one consistent heuristic to search for complete and bounded suboptimal solutions. This simplifies the de- sign of heuristics and enables the search to effectively combine the guiding powers of different heuristic func- tions. We support these claims with experimental results on full-body manipulation for PR2 robots.
Key concepts: Heuristics, Heuristic, Consistent heuristic, Incremental heuristic search, Computer science, Null-move heuristic, Mathematical optimization, Sign (mathematics)