Heuristics for Multi-Vehicle Routing Problem Considering Human-Robot Interactions

Autonomous mobile robots (AMRs) are being used extensively in civilian and military applications for such as underground mining, nuclear plant operations, planetary exploration, intelligence, surveillance reconnaissance (ISR) missions manned-unmanned teaming. We consider a multi-objective, multiple-vehicle routing problem which teams of manned ground vehicles (MGVs) AMRs deployed respectively leader-follower framework to execute with differing requirements MGVs while considering human-robot interactions (HRI). HRI studies highlight the costs managing team follower by leader MGV. This paper aims compute feasible visit sequences, replenishments, compositions number MGV-AMR that met routing, replenishment, deployment at minimum. The is first modeled mixed-integer linear program (MILP) can be solved optimality off-the-shelf commercial solvers small-sized instances. For larger instances, variable neighborhood search algorithm offered near optimal solutions address challenges arise when solving combinatorial multi-objective optimization problem. Finally, computational experiments corroborate effectiveness proposed algorithms presented.