Path Planning for a Heterogeneous Aerial-Ground Robot System with Neighbourhood Constraints

For the path planning problem of a class of heterogeneous aerial-ground robot systems with neighborhood constraints, a convex optimization based on mixed integer programming is proposed. The heterogeneous robot system consists of an unmanned aerial vehicle (UAV) and an autonomous ground mobile vehicle. A sequence of targets, whose positions are known as prior knowledge, are expected to be accessed in a given order. Owing to its limited duration in the air, the unmanned aerial vehicle should return to the ground vehicle timely and land on the deck for its energy-saving and recharge. The maximum speeds of the both vehicles, the minimum time for charging and the maximum duration time in the air for the aerial robot, and the neighborhood of each target is carefully considered in the model. An objective optimization model is developed by minimizing the time cost spent on all the targets, and the path planning problem of the heterogeneous aerial-ground robot system is formulated as a mixed integer convex optimization problem. Considering the time consumption on takeoff or landing of the aerial robot, the influence of the UAV agility on path solutions is analyzed based on the proposed convex optimization model. Finally, the simulation results show the feasibility and efficiency of the proposed method.