In view of the shortcomings of cable-driven and chain transmission mechanism with motor rotation direction changing frequently and large load, a novel electric-drive robot leg based on planar five-bar mechanism with dual freedoms was proposed to reduce the inertia of robot leg and enhance load capacity. Considering the close relationship between the dynamic performance of robot and the dimension parameters of planar fivebar mechanism, the kinematic and dynamic analyses of this mechanism was made, and the functional relationship between peak torque, peak angular velocity of joint motors, energy consumption in a gait period and dimension parameters were setup to get the optimal dimension parameters. In this way, a multiobjective optimization model of the dimension parameters was got. By determining the weight of the objectives based on analytic hierarchy process (AHP) method, the multi-objective optimization problem was transformed into single objective optimization problem. Then the genetic algorithm was applied to obtain the optimal solution. Finally, the virtual prototypes of robot leg before and after optimization were built via ADAMS to conduct the walking simulation test, and the comparison between simulation results and computation results was made. The motors were selected subsequently according to the optimization results, which made the robot weight decreased by 7.8%, which was beneficial to the improvement of load capacity and battery life. These results verified the correctness and validity of the proposed algorithm which can also be applicable to the selection of brushless DC motor.