Papers
4
Total Citations
60
H-Index
3
About
Dengfeng Sun is a leading researcher in multi-robot systems, autonomous navigation, and human-robot interaction, with a focus on enabling intelligent coordination in dynamic and unknown environments. His foundational work on pursuit-evasion games and collision avoidance, published in 2005 (39 citations), established a roadmap-based framework for mobile robots to navigate shared spaces safely and efficiently—a contribution that remains influential in robotics and autonomous vehicle research. More recently, Sun introduced the DoSS (Distributed on-line Source Seeking) algorithm, which leverages a novel dummy confidence upper bound (D-UCB) concept to enable multi-robot teams to dynamically locate sources in unknown environments without centralized control. This work, published in 2021 (12 citations), addresses critical challenges in environmental monitoring and disaster response. Sun has also pioneered hybrid gaze-brain-computer interface (BCI) control systems for multi-robot operations, allowing operators to command robotic teams while their hands are occupied—a breakthrough for dual-tasking scenarios in defense and industrial applications. His development of Gazebo-based simulation environments for unmanned aerial systems further supports accessible testing and validation of autonomous algorithms. Through these diverse contributions, Sun continues to advance the frontiers of decentralized robotics and intuitive human-machine collaboration.
Research Focus
Key Achievements
Top Papers
- 1Roadmap Based Pursuit-Evasion and Collision Avoidance39 citations · 2005
- 2Multi-Robot Dynamical Source Seeking in Unknown Environments12 citations · 2021
- 3
- 4Gazebo-Based Simulation Environment Integration for UAS2 citations · 2021