Extended reliable robust motion planners
Adina M. Panchea, Alexandre Chapoutot, David Filliat · 2017
A new method to plan guaranteed to be safe paths in an uncertain environment, with an uncertain initial and final configuration space, while avoiding static obstacles is presented. First, two improved versions of the previously proposed BoxRRT algorithm are presented: both with a better integration scheme and one of them with the control input selected according to a desired objective, and not randomly, as in the original formulation. Second, a new motion planner, called towards BoxRRT?, based on optimal Rapidly-exploring Random Trees algorithm and using interval analysis is introduced. Finally, each of the described algorithms are evaluated on a numerical example. Results show that our algorithms make it possible to find shorter reliable paths with less iterations.