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Motion Planning and Control with Environmental Uncertainties for Humanoid Robot

Year: 2024

Type: article

Abstract: Humanoid robots are typically designed for static environments, but real-world applications demand robust performance under dynamic, uncertain conditions. This paper introduces a perceptive motion planning and control algorithm that enables humanoid robots to navigate and operate effectively in environments with unpredictable kinematic and dynamic disturbances. The proposed algorithm ensures synchronized multi-limb motion while maintaining dynamic balance, utilizing real-time feedback from force, torque, and inertia sensors. Experimental results demonstrate the algorithm's adaptability and robustness in handling complex tasks, including walking on uneven terrain and responding to external disturbances. These findings highlight the potential of perceptive motion planning in enhancing the versatility and resilience of humanoid robots in uncertain environments. The results have potential applications in search-and-rescue missions, healthcare robotics, and industrial automation, where robots operate in unpredictable or dynamic conditions.

Source: Sensors

DOI: 10.3390/s24237652

Authors: Zhiyong Jiang, Yu Wang, Siyu Wang, Sheng Bi, Jiangcheng Chen

Institutions: China Electronics Technology Group Corporation, Shenzhen Academy of Robotics

Language: English

Topic: Robotic Locomotion and Control

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,955

Funder: Basic and Applied Basic Research Foundation of Guangdong Province