Optimized Motion Control for Energy-Efficient Bipedal Walking Robots

This study explores a novel control optimization framework for bipedal robotic locomotion, focusing on energy efficiency and stability. Using a control co-design (CCD) approach, the system simultaneously optimizes mechanical parameters and control strategies to enhance gait efficiency. Within the simulation scope considered, the proposed method reduces torque demands and cycle time and yields stable walking over the simulated cycles for the reported initial conditions. Simulation results demonstrate a reduction in control effort over ten walking cycles while maintaining dynamic balance in the simulated cases, highlighting the potential of integrated design strategies in robotic walking systems.

Authors

Publication Details

Journal
International Journal of Intelligent Systems and Data Science
Published
2026-10-31
DOI
https://doi.org/10.67231/zrqvwj89
Primary Topic
Robotic Locomotion and Control
Type
article
Field-Weighted Citation Impact
0.00
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article

Optimized Motion Control for Energy-Efficient Bipedal Walking Robots

Harish Kasireddy
International Journal of Intelligent Systems and Data Science
Robotic Locomotion and Control
article

Optimized Motion Control for Energy-Efficient Bipedal Walking Robots

Harish Kasireddy
article en

Abstract

This study explores a novel control optimization framework for bipedal robotic locomotion, focusing on energy efficiency and stability. Using a control co-design (CCD) approach, the system simultaneously optimizes mechanical parameters and control strategies to enhance gait efficiency. Within the simulation scope considered, the proposed method reduces torque demands and cycle time and yields stable walking over the simulated cycles for the reported initial conditions. Simulation results demonstrate a reduction in control effort over ten walking cycles while maintaining dynamic balance in the simulated cases, highlighting the potential of integrated design strategies in robotic walking systems.

International Journal of Intelligent Systems and Data ScienceVol. 1(6)
Openalex Percentile: Top 24%
Robotic Locomotion and Control
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