Coverage path planning (CPP) is a critical task in various fields of mobile robots, including agricultural autonomous vehicles, lawnmowers, demining robots, planetary exploration rovers, milling operations, and many other applications. This paper studies Benson’s method (BM) a preference-based multi-objective optimization (PBMO) CPP of a mobile robot in a rectilinear simulation environment with uneven terrain. The primary objective of the paper is to minimize the energy consumption of the mobile due to: (1) the distance traveled by the robot, (2) the total elevation (ascend and descend) made by the robot, and (3) the total number of turns to complete the task of CPP in uneven terrain. Two simulation environments are selected to validate the proposed method (BM) and compare it with the weighted sum method (WSM). The proposed method overpowered the WSM in total energy consumption by 3.66% and 5.75% in the first and second environments, respectively.