Max Robotics — Global Service Robot Directory + US Certification

About

Jingxuan Cao is a rising leader in the field of legged robotics, with a focused expertise in quadruped robot locomotion, terrain adaptation, and autonomous control. His work bridges the gap between robust mechanical design and intelligent decision-making, enabling robots to traverse challenging, unstructured environments. Cao’s most impactful contribution, "Whole‐body motion planning and control of a quadruped robot for challenging terrain" (30 citations), presents a novel control framework that plans center-of-gravity trajectories for rough terrain navigation, directly addressing a critical bottleneck in field robotics. He has further advanced the field through innovative work on adaptive diagonal gaits for efficient dynamic locomotion and a stable skill improvement method using privileged information and curriculum guidance. Notably, Cao introduced an online terrain classification framework based on acoustic signals, a creative approach that allows robots to "hear" their environment for real-time adaptation. His research also integrates visual-lidar fusion for terrain recognition and leverages deep reinforcement learning with parallel training for sim-to-real transfer. With a rapidly growing body of work published in 2022-2023, Cao is establishing himself as a key innovator in creating more capable, perceptive, and autonomous legged systems for real-world deployment.