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Computing Pareto Optimal Coordinations on Roadmaps

Department of Mathematics, University of Illinois, Urbana, IL 61801, USA, ghrist{at}math.uiuc.edu

Jason M. O'Kane

Department of Computer Science, University of Illinois, Urbana, IL 61801, USA, jokane{at}cs.uiuc.edu

Steven M. LaValle

Department of Computer Science, University of Illinois, Urbana, IL 61801, USA, lavalle{at}cs.uiuc.edu

We consider the coordination of multiple robots in a common environment, each robot having its own (distinct) roadmap. Our primary contribution is a classification of and exact algorithm for computing vector-valued (or Pareto) optima for collision-free coordination. We indicate the utility of new geometric techniques from CAT(0) geometry and give an argument that curvature bounds are the key distinguishing feature between systems for which the classification is finite and for those in which it is not.

Key Words: motion planning • optimality • coordination spaces • roadmaps • multiple robots

The International Journal of Robotics Research, Vol. 24, No. 11, 997-1010 (2005)
DOI: 10.1177/0278364905059057


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