Dake Zheng

Shenzhen Institutes of Advanced Technology, Shenzhen Academy of Robotics

Papers

Total Citations

H-Index

About

Dake Zheng is a robotics researcher whose work focuses on enabling real-time, intelligent obstacle avoidance for robotic manipulators. His primary research areas include redundant manipulator control, dynamical systems (DS)-based motion planning, and whole-body collision avoidance in complex environments. Zheng's major contributions lie in developing computationally efficient algorithms that allow high-degree-of-freedom robots, such as 7-DOF arms, to navigate dynamic and cluttered spaces without pre-computed paths. He pioneered a method for real-time whole-body obstacle avoidance, addressing the heavy computational costs that previously hindered practical implementation. Additionally, his work on dynamical systems provides a framework for avoiding three-dimensional concave obstacles by decomposing them into intersecting convex ellipsoids, and for integrating workspace constraints directly into the modulation of robot motion. While his most-cited papers (totaling 8 citations) represent early-career impact, his innovative approach to merging real-time performance with complex geometric reasoning marks a significant step toward safer, more autonomous robots in human-shared environments.