Xiaoxin Wang
Papers
1
Total Citations
14
H-Index
1
About
Xiaoxin Wang’s research focuses on the intersection of robotics, control systems, and human-robot interaction, with a particular emphasis on visual servoing and kinematic redundancy. In their most-cited work, "Visual Servoing Control of Baxter Robot Arms with Obstacle Avoidance Using Kinematic Redundancy" (2015), Wang introduced a novel approach that enables robotic arms to dynamically adjust their movements in real time, avoiding obstacles while maintaining precise task execution. This contribution has been cited 14 times, reflecting its relevance to advancing safe and adaptive robotic manipulation. Wang’s work is notable for integrating vision-based feedback with redundancy resolution, a key challenge in autonomous robotics. Their research has practical implications for industrial automation, assistive robotics, and collaborative environments where robots must operate alongside humans. By addressing both control precision and obstacle avoidance, Wang has helped pave the way for more versatile and reliable robotic systems. Their contributions continue to inspire researchers working on real-time adaptive control and human-safe robot design.
Research Focus
Key Achievements
Top Papers
- 1