This paper focuses on the development of a follow behavior for an unmanned ground vehicle (UGV) in collaborative scenarios. The scenario being studied involves a human traveling over a rugged terrain on foot. The UGV follows the human. We present an approach for automatically generating a reactive energy-efficient follow behavior that maps the vehicle’s states into motion goals. We start by partitioning the state space that encodes the relationship between the state of the vehicle and the human’s state, and the environment. For each cell in the partitioned state space, we either directly generate the motion goal for the vehicle to execute or a function that produces the motion goal. The motion goal defines not only the location towards which the vehicle should move but also specifies a zero activity zone around the human within which the vehicle is supposed to slow down and remain stationary to save its energy until it gets outside the margin caused by the movement of the human. Our approach utilizes off-line simulations to assess the performance of the generated behavior. Our simulation results show that the automatically generated follow behavior significantly outperforms a simple conservative tracking rule in terms of distance traveled and violation of proximity constraints. We anticipate that the approach presented in this paper will ultimately enable us to implement energy efficient follow behaviors on physical UGVs.
Towards Energy Efficient Follow Behaviors for Unmanned Ground Vehicles Over Rugged Terrains
