Max Robotics — Global Service Robot Directory + US Certification

About

Zichen He is an emerging robotics researcher whose work sits at the intersection of autonomous mobile robotics, reinforcement learning, and multi-agent systems. His research focuses on advancing motion planning methodologies for mobile robots, particularly through the application of deep reinforcement learning to overcome the limitations of classical hierarchical planners in complex, dynamic environments. He is perhaps best known for his comprehensive review of mobile robot motion planning — a work that has amassed over 113 citations and has become a key reference for researchers navigating the transition from traditional planning workflows to learning-based architectures. Beyond survey contributions, He has made meaningful algorithmic advances, including the development of a multiagent Soft Actor-Critic hybrid motion planner (47 citations) that enables smooth, end-to-end multirobot coordination without explicit communication. His more recent work on socially aware cooperative planning in pedestrian environments further demonstrates his commitment to real-world deployment challenges. Across his portfolio, He has also tackled multi-robot formation control using reinforcement learning, reflecting a consistent focus on scalable, cooperative autonomy. With a growing citation record and increasingly sophisticated contributions, Zichen He represents a promising voice in next-generation autonomous robotics research.