Naifeng He | Robotics | Best Researcher Award

🎓Early Academic Pursuits

He Naifeng began his academic journey with a deep interest in robotics and automation, eventually leading him to pursue a PhD at the School of Automation, Nanjing University of Aeronautics and Astronautics. His early focus revolved around motion control systems for autonomous robots, particularly exploring how robots could navigate complex, dynamic environments. His foundational studies set the stage for his later research in integrating advanced control techniques with artificial intelligence.

As a PhD candidate, He Naifeng specializes in the field of motion control and navigation of wheel-legged mobile robots. His work is recognized for its innovative approach to solving challenges in robot autonomy and mobility. Combining traditional control techniques with reinforcement learning, he has made notable advancements in enhancing the agility and adaptability of mobile robots. His primary professional focus includes optimizing navigation systems, path planning, and obstacle avoidance for these robots.

He Naifeng’s key contributions lie in developing motion control systems that enable wheel-legged robots to operate autonomously in unpredictable environments. His research incorporates deep reinforcement learning to improve the robots’ decision-making capabilities, especially in complex and unmapped areas. Through his approach, the efficiency of path planning and dynamic obstacle avoidance has been significantly improved, paving the way for practical applications such as industrial inspection.

He Naifeng’s research has impacted various sectors, including industrial automation and robotics. By focusing on the development of control algorithms for mobile robots, he has enabled more efficient autonomous navigation in unmapped and unknown environments. His innovations have led to improvements in both the performance and safety of these robots, allowing them to be used in more complex, real-world scenarios.

He Naifeng has made significant contributions to the field of autonomous robotics through his published works in reputable scientific journals. His research has gained recognition, particularly in the areas of autonomous navigation and control algorithms for mobile robots.

He Naifeng’s ongoing work on wheel-legged robots and autonomous navigation systems positions him as an innovator in the field of mobile robotics. His efforts in improving dynamic obstacle avoidance and path optimization have the potential to revolutionize industries where autonomous inspection and mobility are critical. As his research continues to evolve, He Naifeng is poised to make even greater contributions to the advancement of intelligent mobile systems, particularly through the application of reinforcement learning in control systems.

A Supervised Reinforcement Learning Algorithm for Controlling Drone Hovering
Authors: Wu, J., Yang, Z., Zhuo, H., Liao, L., Wang, Z.
Journal: Drones, 2024, 8(3), 69
A Self-Adaptive Double Q-Backstepping Trajectory Tracking Control Approach Based on Reinforcement Learning for Mobile Robots
Authors: He, N., Yang, Z., Fan, X., Sui, Y., Zhang, Q.
Journal: Actuators, 2023, 12(8), 326
A State-Compensated Deep Deterministic Policy Gradient Algorithm for UAV Trajectory Tracking
Authors: Wu, J., Yang, Z., Liao, L., Wang, Z., Wang, C.
Journal: Machines, 2022, 10(7), 496
Adaptive PID Trajectory Tracking Algorithm Using Q-Learning for Mobile Robots
Authors: Fan, X., Sui, J., He, N., Yang, J., Cui, L.
Journal: 2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022, pp. 1112–1117