Multi-Heuristic A*
Aine, Sandip (IIIT Delhi) | Swaminathan, Siddharth (Carnegie Mellon University) | Narayanan, Venkatraman (Carnegie Mellon University) | Hwang, Victor (Carnegie Mellon University) | Likhachev, Maxim (Carnegie Mellon University)
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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