Max Robotics — Global Service Robot Directory + US Certification

About

Erkui Chen’s research lies at the intersection of mobile robotics, intelligent control, and bio-inspired systems, with a focus on enabling autonomous navigation and cooperative behavior in complex environments. His most influential work, “Mobile robot navigation using neural Q-learning” (28 citations), introduced a continuous Q-learning algorithm that has become a widely adopted framework for robotic decision-making due to its simplicity and theoretical rigor. Chen further advanced autonomous perception with a real-time semantic visual SLAM approach (24 citations), integrating points and objects to improve localization accuracy and map richness for service robots. In path planning, he developed an improved genetic algorithm (16 citations) that overcomes limitations of traditional methods for mobile robot navigation. Chen’s contributions extend to biomimetic robotics, where he designed motion control algorithms for a free-swimming robot fish (12 citations), addressing the unique challenges of hydrodynamics and dynamics in underwater locomotion. His work on multi-robot cooperative hunting (7 citations) introduced dynamic prediction of target motion, enhancing encirclement strategies. Collectively, Chen’s research has earned over 90 citations, demonstrating its practical impact on robotic navigation, semantic mapping, and bio-inspired control systems.