Duo Zhao

About

Dr. Duo Zhao is a leading researcher in robotic path planning and multi-robot cooperative systems, with a primary focus on advancing industrial automation through intelligent optimization algorithms. His major contributions lie in developing novel, computationally efficient solutions for complex manufacturing tasks, particularly dual-robot cooperative arc welding. Dr. Zhao has pioneered the application of cross-entropy optimization and improved genetic algorithms (R-NSGA-II) to solve multi-objective path planning problems, enabling faster, lower-cost, and more effective coordination for large-scale component welding. His most cited work, a 2024 paper on dual-robot cooperative welding path planning using multi-objective cross-entropy optimization, has garnered 23 citations, reflecting its significant impact on the field. Additionally, his 2020 heuristic path planning algorithm for substation inspection robots introduced a practical, topology-based optimization model that balances speed and cost. Dr. Zhao’s recent innovations include an adaptive rapidly-exploring random trees algorithm (CE-RRT) for complex environments, further demonstrating his commitment to pushing the boundaries of robotic autonomy and efficiency in real-world applications.

Research Focus

Key Achievements

Top Papers

1. 1
   A dual-robot cooperative arc welding path planning algorithm based on multi-objective cross-entropy optimization

   23 citations · 2024
2. 2
   A Heuristic Path Planning Algorithm for Inspection Robots

   12 citations · 2020
3. 3
   A Dual-Robot Cooperative Arc Welding Path Planning Algorithm based on Multi-Objective Optimization

   7 citations · 2023
4. 4
   A Dual-Robot Cooperative Welding Path Planning Algorithm Based on Improved Ant Colony Optimization

   6 citations · 2022
5. 5
   An Adaptive Rapidly-Exploring Random Trees Algorithm Based on Cross-Entropy Optimization

   1 citations · 2025

Key Collaborators

Contact & Links