Zhixiong Wang

About

Zhixiong Wang is a leading researcher in intelligent robotics and autonomous navigation, with a focus on solving complex path planning and obstacle avoidance challenges. His work centers on developing advanced algorithms for mobile robots and dual-arm robotic systems operating in dynamic, unpredictable environments. Wang’s most impactful contribution is his 2022 paper on a mobile robot path planning algorithm that integrates an improved A* algorithm with the Dynamic Window Approach, which has garnered 105 citations for its ability to reduce path turning points, eliminate redundant nodes, and optimize runtime. He further advanced the field with a 2024 hybrid method combining improved A* and CSA-APF algorithms, addressing dynamic obstacle avoidance and local optima issues. Wang has also made notable strides in dual-arm robotics, proposing a multi-obstacle avoidance algorithm that handles zero-space and terminal obstacles while ensuring self-collision avoidance. His work on simultaneous localization and mapping (SLAM) for unmanned vehicles in dynamic environments, incorporating YOLOv7, demonstrates his commitment to real-world applicability. With a growing citation record and innovative solutions, Wang is shaping the future of autonomous systems.

Research Focus

Key Achievements

Top Papers

1. 1
   A Mobile Robot Path Planning Algorithm Based on Improved A* Algorithm and Dynamic Window Approach

   105 citations · 2022
2. 2
   A Hybrid Path Planning Method Based on Improved A* and CSA-APF Algorithms

   20 citations · 2024
3. 3
   The Algorithm of Multiple Obstacle Avoidance Tasks for Dual-Arm Robots

   9 citations · 2023
4. 4
   Simultaneous Localization and Mapping of Unmanned Vehicles under Dynamic Environments with YOLOv7

   5 citations · 2022

Key Collaborators

Contact & Links