Chansu Suh

Seoul National University, Korea Institute of Robot and Convergence, École Polytechnique Fédérale de Lausanne

Papers

Total Citations

148

H-Index

About

Chansu Suh is a roboticist whose work bridges the gap between theoretical motion planning and practical soft robotics. His primary research areas include constrained motion planning on curved manifolds, soft pneumatic actuators, and proximity-based safe manipulation. Suh’s most significant contribution is the development of the Tangent Bundle Rapidly Exploring Random Tree (TB-RRT) algorithm, which revolutionized motion planning for robots operating on complex, curved configuration spaces. By constructing random trees on tangent bundle approximations rather than the manifold itself, his approach elegantly handles holonomic constraints and has garnered 95 citations. Earlier, his Tangent Space RRT (TS-RRT) laid the groundwork for this concept with 32 citations. Suh also pioneered the Soft Pneumatic Actuator skin (SPA-skin), an ultra-thin (<1 mm) sensor-embedded actuator designed to provide proprioceptive sensing for soft robots, demonstrating his versatility in hardware design. His work on proximity sensing and reactive control further advances safe human-robot interaction. With a total of nearly 150 citations across his top papers, Suh’s research is essential reading for students and researchers interested in both algorithmic foundations and innovative actuator design in robotics.