Energy-Efficient Bipedal Gait Pattern Generation via CoM Acceleration Optimization

Abstract

Energy consumption for bipedal walking plays a central role for a humanoid robot with limited battery capacity. Studies have revealed that exploiting the allowable Zero Moment Point region (AZR) and Center of Mass (CoM) height variation (CoMHV) are strategies capable of improving energy performance. In general, energetic cost is evaluated by integrating the electric power of multi joints. However, this Joint-Power-based Index requires computing joint torques and velocities in advance, which usually requires time-consuming iterative procedures, especially for multi-joints robots. In this work, we propose a CoM-Acceleration-based Optimal Index (CAOI) to synthesize an energetically efficient CoM trajectory. The proposed method is based on the Linear Inverted Pendulum Model, whose energetic cost can be easily measured by the input energy required for driving the point mass to track a reference trajectory. We characterize the CoM motion for a single walking cycle and define its energetic cost as Unit Energy Consumption. Based on the CAOI, an analytic solution for CoM trajectory generation is provided. Hardware experiments demonstrated the computational efficiency of the proposed approach and the energetic benefits of exploiting AZR and CoMHV strategies.

Humanoid Robot Cooperative Motion Control Based on Optimal Parameterization

“…Liu et al ( 2021 ) used a direct collocation method that converts the trajectory optimization problem into a nonlinear programming problem which can reduce energy consumption and improve the stability in the multi-phase gait motion process, but usually the local optimal solution is found. Ding et al ( 2018 ) took the acceleration of the center of mass as the evaluation criteria of energy consumption to verify the energy-saving performance in the stable zone of the ZMP. However, for multi-joint robots, this method usually takes more time-consuming iteration to calculate joint torques and velocities in advance.…”

Energy-Efficient Bipedal Walking: From Single-Mass Model to Three-Mass Model

“…To overcome the above drawbacks, in previous work, that is, ref. [41], a CoM accelerationbased optimal index (CAOI) was derived. By using this cost function, an unconstrained optimization approach was proposed for CoM trajectory generation, with the capability of tracking different forms of ZMP trajectories.…”

“…Then, through deriving the equivalent ZMP motion of 3MIPM, the unconstrained optimization method introduced in ref. [41] is extended for generating the energy-efficient CoM trajectory, while the two-stage optimization method 42 is employed to make use of the AZR. Finally, by modifying the step parameters inputs, higher energy economy is obtained.…”

Energy Efficiency of Force-Sensor-Controlled Humanoid-Robot Walking on Indoor Surfaces

“…In this previously reported work, the energy-consumption determination has been done based on a simulation platform [3], while real-time energy measurements are not reported. An energy-efficient bipedalwalking-pattern generation, using center of mass (CoM) height variation (CoMHV), is reported in [4]. The authors propose a CoM-acceleration-based optimal index (CAOI) model, using the linear inverted pendulum model (LIPM) to find out an efficient walking trajectory with minimumenergy utilization.…”

“…The authors propose a CoM-acceleration-based optimal index (CAOI) model, using the linear inverted pendulum model (LIPM) to find out an efficient walking trajectory with minimumenergy utilization. For this purpose, the authors of [4] have considered an energy-consumption model to determine oneunit-walking-cycle steps. A further method for simulationbased bio-inspired energy-efficient walking-pattern generation is reported in [5], where neutral-oscillators are used to generate gait patterns with improved energy efficiency (40.5%) in comparison to conventional walkingpattern generation for biped robots.…”