Receding Horizon Control in unknown environments: Experimental results

摘要

This paper presents a novel approach to navigation in an a priori unknown, GPS-denied environment. The aim is to combine dynamic path planning with the ability to learn about the environment. The vehicle is tasked with autonomous travel from an uncertain initial position to an uncertain target, without prior mapping information. The environment is modelled using linear segments that represent boundaries between the estimated traversable and non-traversable regions. The approach integrates Receding Horizon Control (RHC) and Simultaneous Localisation and Mapping (SLAM). The control problem is formulated as a mixed integer linear program (MILP) and explicitly includes the obstacles and vehicle dynamics. We present the results of our experiments using Pioneer robots, as well as, simulation results which clearly demonstrated the impact of each component of the system.