J.C.Latombe; Motion Planning with Probabilistic Roadmaps , 3.7, 15:40
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  • J.C.Latombe; Motion Planning with Probabilistic Roadmaps , 3.7, 15:40

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Faculty of Engineering and Natural Sciences

Motion Planning with Probabilistic Roadmaps

Jean-Claude Latombe,
Computer Science Department, Stanford University

For over 15 years, a major research theme in my research group has been the development of random sampling schemes to create efficient motion planners for robots, digital characters, and other moving objects. The main outcome of this research has been the Probabilistic
Roadmap approach (PRM) to motion planning. Originally, this approach was intended to compute collision-free paths of robots with many degrees of freedom at that time, 4 or more. But, over the years, successive improvements (as well as faster computers) made it possible to handle robotic systems with several dozen degrees of freedom operating in complex geometric environments. PRM was also extended to solve planning problems with motion constraints other than collision avoidance, for instance, visibility, equilibrium, contact, and kinodynamic constraints. Concurrently, PRM has also been applied to non-robotics applications, e.g., for animating autonomous digital characters, designing product that can easily be assembled and serviced, testing whether architectural designs satisfy building
codes, providing interactive tools to navigate in huge virtual reality models, planning complex surgical operations, and studying folding and binding molecular motions. In this talk, I will review the PRM approach and various underlying techniques, especially sampling strategies. I will also discuss the probabilistic foundations of the approach and related theoretical results. In particular, I will argue that the main outcome of PRM is what its success tells us about motion planning problems, rather than the approach itself. Finally, I will discuss the recent application of PRM to legged robots navigating on steep irregular terrain more specifically, rock-climbing robots.

Bio: Jean-Claude Latombe is the Kumagai Professor of Computer Science at Stanford University. He received his PhD from the National Polytechnic Institute of Grenoble (INPG) in 1977. He was on the faculty of INPG from 1980 to 1984, then he joined ITMI (Industry and Technology for Machine Intelligence), a company that he had co-founded in 1982. He moved to Stanford in 1987. At Stanford, he served as the Chairman of the Computer Science Department from 1997 till 2001, and on the BioX Leadership Council from 2002 till 2004. His main research interests are in Artificial Intelligence, Robotics, Computational Biology, Computer-Aided Surgery, and Graphic Animation.

July 23, 2009, 15:40, FENS G032