Papers
20
Total Citations
314
H-Index
9
About
Dingxin He is a robotics and autonomous systems researcher whose work spans multi-robot coordination, simultaneous localization and mapping (SLAM), and intelligent control for mobile robotic platforms. His most influential contribution, "Distributed Controller–Estimator for Target Tracking of Networked Robotic Systems under Sampled Interaction" (2016, 107 citations), established him as a notable voice in distributed control theory, addressing the challenge of coordinated target tracking across networked robotic systems. He has made significant strides in localization accuracy, proposing an improved Adaptive Monte Carlo Localization (AMCL) algorithm that better handles complex, unstructured environments—work that has garnered 54 citations and directly benefits real-world robot navigation. He has further contributed to multi-robot system architecture, developing ROS-based hybrid frameworks for heterogeneous robot teams, and has tackled practical industrial challenges such as intelligent substation inspection and pointer-instrument positioning. His more recent research explores visual-inertial SLAM with wheel-speed anomaly detection, sparse Bayesian learning for online robot identification, and self-triggered model predictive control for teleoperation. Collectively, He's publications reflect a career dedicated to bridging theoretical control methods with robust, deployable robotic applications, making his work broadly relevant to both academic researchers and industrial robotics practitioners.
Research Focus
Key Achievements
Top Papers
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- 4A new ROS-based hybrid architecture for heterogeneous multi-robot systems19 citations · 2015
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