Aiming at the problem that the mobile robot operating in complex outdoor environment reduced work completion rate due to energy limitation because of consume excessive energy when moving along the shortest paths on uneven terrains which often consisted of rapid elevation changes, an improved heuristic search algorithm called ECA* algorithm was proposed, which can optimize energy loss of the path when resources were limited. Firstly, the distance traveled and the energy lost by the robot were calculated by the establishment of robot distanceenergy loss model, which can also evaluate the future path and the energy consumption trend. Then, the distanceenergy loss model was brought into the heuristic cost function based on the traditional A* algorithm and the extended subnode was searched for the optimal path. In each iteration process, the path at the disadvantage was eliminated by comparison to ensure the efficiency of the algorithm. Finally, the energy loss of different paths searched by the improved algorithm as well as the traditional A* algorithm was compared though the design of simulation experiment. The improved algorithm can reduce the energy consumption by 14.87% through the simulated calculation which verified the effectiveness of the improved algorithm.