Computing pareto optimal coordinations on roadmaps

Abstract We consider 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.

@article{GhrOKaLav05,
  author = {Robert Ghrist and Jason M. O'Kane and Steven M. LaValle},
  journal = {International Journal of Robotics Research},
  month = {November},
  number = {11},
  pages = {997-1010},
  title = {Computing pareto optimal coordinations on roadmaps},
  volume = {24},
  year = {2005}
}