Receding Horizon Control Using Graph Search for Multi-Agent Trajectory Planning

It is hard to find the global optimum of general nonlinear and nonconvex optimization problems in a reasonable time. This article presents method transfer receding horizon control approach, where nonlinear, are considered, into graph-search problems. Specifically, systems with symmetries considered system dynamics finite-state automaton. In contrast traditional approaches search continues until goal vertex found, approach presented this allows solve them real We prove that solutions recursively feasible by restricting graph end accepting states underlying The applied trajectory planning for multiple networked autonomous vehicles. evaluate its effectiveness simulation experiments Cyber-Physical Mobility Lab, an open-source platform show real-time capable collision avoidance on off-the-shelf hardware code MATLAB two