Zhengguo Zhu — accepted AI-conference papers

2025

An Online Terrain Classification Framework for Legged Robots Based on Fusion of Proprioceptive and Exteroceptive Sensors

Weikai Ding, Jingui Meng, Zhengguo Zhu, Teng Chen, Guoteng Zhang

IROS 2025

Terrain classification is crucial for assessing terrain traversability and supporting locomotion control of legged robots. By integrating multi-source sensor information, including exteroceptive sensors and proprioceptive sensors, legged robots can acquire terrain geometric features and surface cove

Cited by 0 Source ↗Scholar ↗

2023

Proprioceptive-Based Whole-Body Disturbance Rejection Control for Dynamic Motions in Legged Robots

Zhengguo Zhu, Guoteng Zhang, Zhongkai Sun, Teng Chen, Xuewen Rong, Anhuan Xie +1

RA-L 2023

This letter presents a control framework for legged robots that enables self-perception and resistance to external disturbances. First, a novel proprioceptive-based disturbance estimator is proposed. Compared with other disturbance estimators, this estimator possesses notable advantages in terms of

Cited by 17 Source ↗Scholar ↗