Open Access

REVIEW

Gait Planning, and Motion Control Methods for Quadruped Robots: Achieving High Environmental Adaptability: A Review

Sheng Dong^*, Feihu Fan, Yinuo Chen, Shangpeng Guo, Jiayu Liu

School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi’an, 710016, China

* Corresponding Author: Sheng Dong. Email:

(This article belongs to the Special Issue: Environment Modeling for Applications of Mobile Robots)

Computer Modeling in Engineering & Sciences 2025, 143(1), 1-50. https://doi.org/10.32604/cmes.2025.062113

Received 10 December 2024; Accepted 17 February 2025; Issue published 11 April 2025

Abstract

Legged robots have always been a focal point of research for scholars domestically and internationally. Compared to other types of robots, quadruped robots exhibit superior balance and stability, enabling them to adapt effectively to diverse environments and traverse rugged terrains. This makes them well-suited for applications such as search and rescue, exploration, and transportation, with strong environmental adaptability, high flexibility, and broad application prospects. This paper discusses the current state of research on quadruped robots in terms of development status, gait trajectory planning methods, motion control strategies, reinforcement learning applications, and control algorithm integration. It highlights advancements in modeling, optimization, control, and data-driven approaches. The study identifies the adoption of efficient gait planning algorithms, the integration of reinforcement learning-based control technologies, and data-driven methods as key directions for the development of quadruped robots. The aim is to provide theoretical references for researchers in the field of quadruped robotics.

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