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Sampling-based algorithms for optimal motion planning using process algebra specifications
2014
2014 IEEE International Conference on Robotics and Automation (ICRA)
This paper investigates motion-planning using formal language specifications for dynamical systems with differential constraints. In particular, we focus on process algebra as a language to specify complex task specifications motivated by autonomous electric vehicles operating in a mobility-on-demand scenario. We use ideas from sampling-based motion-planning algorithms to incrementally construct a finite abstraction of the dynamical system as a Kripke structure. Given a task specification
doi:10.1109/icra.2014.6907642
dblp:conf/icra/VarricchioCF14
fatcat:4hljd7u4cfh6rcdp4cmpggmsiu