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 operating heavy machinery in such unstable conditions. To speedup access to inner areas, obstacles can be surmounted with the assistance of carefully maneuvered power shovel arm, instead of removing them. In this work, 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 chosen as the best candidate for surmounting a given step-like obstacle. Dynamic simulation results show the effectiveness of the proposed method.