Guochang Gu

About

Guochang Gu is a pioneering researcher in the fields of cooperative robotics, multi-agent systems, and intelligent path planning. His most influential work, "An implementation of evolutionary computation for path planning of cooperative mobile robots" (2003, 83 citations), demonstrated how genetic algorithms can find globally sub-optimal paths for robot groups, addressing a fundamental challenge in cooperative robotics. Gu has made significant contributions to reinforcement learning for multi-robot systems, notably developing the OptMAX framework that integrates options into the MAXQ architecture for hierarchical multi-agent learning. His work on "Path Planning Based on Improved Binary Particle Swarm Optimization Algorithm" (2008, 30 citations) introduced novel optimization techniques for mobile robot navigation. Throughout his career, Gu has explored diverse applications including autonomous underwater vehicle (AUV) path planning in complex ocean environments and multi-robot formation control for pursuit-evasion scenarios. His research consistently bridges theoretical advances in machine learning—such as prior-knowledge based reinforcement learning and self-adaptive quantization—with practical robotics challenges, establishing him as a key contributor to the evolution of intelligent, cooperative robotic systems.

Research Focus

Key Achievements

Top Papers

1. 1
   An implementation of evolutionary computation for path planning of cooperative mobile robots

   83 citations · 2003
2. 2
   Path Planning Based on Improved Binary Particle Swarm Optimization Algorithm

   30 citations · 2008
3. 3
   Multi-robot Cooperation Based on Hierarchical Reinforcement Learning

   23 citations · 2007
4. 4
   Multi-Agent Hierarchical Reinforcement Learning by Integrating Options into MAXQ

   10 citations · 2006
5. 5
   Behavior control of multi-robot using the prior knowledge based reinforcement learning

   8 citations · 2004
6. 6
   Research on reinforcement learning of the intelligent robot based on self-adaptive quantization

   7 citations · 2002
7. 7
   Research on local path planning of AUV under ocean environment

   4 citations · 2004
8. 8
   A METHOD OF MULTI-ROBOT FORMATION WITH THE LEAST TOTAL COST

   2 citations · 2005

Key Collaborators

Contact & Links