A variable-orientation gait planning method for humanoid robots based on nonlinear model predictive control

Tian Mu; Junyao Gao; Leilei Xie; Mingyue Jin; Tian Mu; Junyao Gao; Leilei Xie; Mingyue Jin

doi:10.3934/jimo.2026122

Journal of Industrial and Management Optimization

2026, Volume 22, Issue 7: 3345-3361. doi: 10.3934/jimo.2026122

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Research article

A variable-orientation gait planning method for humanoid robots based on nonlinear model predictive control

School of Mechatronics Engineering, Beijing Institute of Technology, Beijing, 100081, China

Received: 21 March 2026 Revised: 07 June 2026 Accepted: 15 June 2026 Published: 23 June 2026
93C85, 93B45

Based on nonlinear model predictive control (NMPC), this paper proposes a novel gait generation method for robot turning movement. Unlike traditional approaches that treat the robot's heading as a fixed parameter, this method explicitly incorporates the sequence of heading angles into the NMPC framework, which enables the unified optimization of the center of mass (CoM) trajectory, footstep sequence, and heading angle sequence. This design allows the robot to adapt to relatively high speeds and large turning angles. Finally, the proposed method was validated through simulations of the BHR-FCR humanoid robot model in the CoppeliaSim. The results demonstrate that the robot can stably and smoothly execute turning movements at speeds up to 0.75 m/s in response to velocity commands, which confirms the effectiveness of the generated gait sequences.
- humanoid robot,
- nonlinear model predictive control,
- gait planning,
- turning motion,
- heading angle
Citation: Tian Mu, Junyao Gao, Leilei Xie, Mingyue Jin. A variable-orientation gait planning method for humanoid robots based on nonlinear model predictive control[J]. Journal of Industrial and Management Optimization, 2026, 22(7): 3345-3361. doi: 10.3934/jimo.2026122

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Abstract

Based on nonlinear model predictive control (NMPC), this paper proposes a novel gait generation method for robot turning movement. Unlike traditional approaches that treat the robot's heading as a fixed parameter, this method explicitly incorporates the sequence of heading angles into the NMPC framework, which enables the unified optimization of the center of mass (CoM) trajectory, footstep sequence, and heading angle sequence. This design allows the robot to adapt to relatively high speeds and large turning angles. Finally, the proposed method was validated through simulations of the BHR-FCR humanoid robot model in the CoppeliaSim. The results demonstrate that the robot can stably and smoothly execute turning movements at speeds up to 0.75 m/s in response to velocity commands, which confirms the effectiveness of the generated gait sequences.

References

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