Papers
14
Total Citations
189
H-Index
7
About
Zhiguo Shi is a leading researcher in swarm robotics, multi-robot systems, and intelligent control, with a focus on enabling autonomous coordination in complex, uncertain environments. His work bridges reinforcement learning, bio-inspired algorithms, and sensor-based target tracking to advance both theoretical foundations and practical applications. Shi’s most cited paper, “A Survey of Swarm Robotics System” (2012, 46 citations), provides a comprehensive overview of the field, establishing a key reference for researchers. He has made significant contributions to adaptive torque estimation for robot joints with harmonic drive transmissions, developing robust Kalman filter-based methods (43 citations) that enhance precision in modular and reconfigurable robots. His research on energy-efficient target tracking with mobile sensors (30 citations) addresses critical constraints in wireless sensor networks, while his innovative use of Boltzmann policy-based Q-learning (23 citations) and pheromone mechanisms in reinforcement learning (9 and 8 citations) has optimized path planning for multi-robot collaboration. Shi’s work on fuzzy neural networks for rapid path planning and vision stability in legged robots further demonstrates his versatility. With over 170 total citations, his research has had a lasting impact on autonomous systems, inspiring advancements in swarm intelligence and adaptive control.
Research Focus
Key Achievements
Top Papers
- 1A Survey of Swarm Robotics System46 citations · 2012
- 2Adaptive torque estimation of robot joint with harmonic drive transmission43 citations · 2017
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- 10Gait and Stability Analysis of a Quadruped Robot3 citations · 2011