Tao Tan

Papers

Total Citations

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About

Tao Tan is a pioneering researcher in intelligent robotics, with a primary focus on motion planning and control for robotic arm systems. His most influential work, "Motion Planning In Phase Space For Intelligent Robot Arm Control" (2005, 29 citations), introduces novel planning and control schemes that leverage phase space representation—mapping velocity against position—to enhance sensing-based robot arm intelligence. This foundational contribution integrates motion planning directly with real-time sensory feedback, enabling more adaptive and precise robotic manipulation. Tan's approach addresses a critical challenge in robotics: bridging the gap between high-level planning and low-level control in dynamic environments. By developing these phase space methodologies, he has provided a framework that allows robot arms to navigate complex tasks with greater autonomy and efficiency. His work is particularly notable for its compatibility with sensing-based systems, making it highly relevant for modern applications in manufacturing, automation, and assistive robotics. While his citation count reflects a focused but impactful contribution, Tan's research continues to influence subsequent developments in intelligent robot control, offering students and researchers a compelling example of how theoretical insights can drive practical advancements in robotic intelligence.