Max Robotics — Global Service Robot Directory + US Certification

About

Ligang Cai is a leading researcher in human–robot collaboration (HRC), industrial robotics, and intelligent perception systems. His work focuses on enabling robots to accurately perceive human actions and intentions, a critical challenge for safe and efficient collaborative environments. Cai’s most impactful contribution is the development of a deep learning framework, combined with the Dempster–Shafer evidence theory, for standing-posture recognition using pressure-floor sensors. This approach, detailed in his highly cited 2020 paper (34 citations), allows robots to predict human workers’ intended actions during HRC tasks, significantly enhancing interaction safety and responsiveness. He has also advanced the prediction of transmission accuracy in harmonic drives, a key component for robotic joint performance, and pioneered color recognition and dynamic decision-making models for industrial robots using embedded systems like Raspberry Pi. Cai’s work bridges the gap between sensor data and real-time robotic adaptation, with his research on posture recognition and intelligent sensing floors laying the groundwork for more intuitive human–robot teams. His contributions are shaping the future of collaborative robotics in manufacturing and service applications.