Large debris created after natural disasters restrict access to inner parts of affected regions and slows down disaster relief operations. Power shovels are often used to clear wreckage but the process can take a lot of time. Moreover, it is dangerous to involve human workers in such conditions due to loose debris collapsing and causing severe damage. To speedup access to inner areas, instead of removing obstacles, they can be surmounted with the assistance of a carefully maneuvered power shovel arm. In this paper, an autonomous obstacle surmounting technique for an unmanned power shovel is proposed. Out of different sequences, the one that optimizes the total energy consumption is selected as the best candidate for surmounting a given obstacle by dynamic simulations. The experiments conducted using a miniaturized power shovel show the effectiveness of the proposed method.
['Peshala G. Jayasekara', 'Hitoshi Arisumi']
Obstacle surmounting by arm maneuver for unmanned power shovel