Shape reconstruction using a mobile robot for demining and UXO classification

Abstract

Metal detectors are widely used to detect and localize land mines, as well as metallic clutter that causes many false alarms. These false alarms are handled by manual inspection with a prodder or using extra features like size and depth as well as fusion with other sensors like ground penetrating radar or chemical sensors. Directly shape itself has never been used, mainly due to infeasibility of the results of the few existing studies, which require controlled environments and dense sampling of the target objects. In this paper, we propose a new method for shape reconstruction that works with sparse data, and show its feasibility using field data collected by a mobile robot equipped with a commercial pulse induction metal detector carried by a custom 2DoF arm. This paper also describes the method employed to sweep natural terrains with the mobile manipulator and provides results of imaging a set of different metallic objects.