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Hi, my name is Sihui Li. I’m a Ph.D. candidate in computer science at Colorado School of Mines. I work with Dr. Dantam in the DyALab. I’m graduating this Spring, and will join Washington State University Tri-Cities as a tenure-track assistant professor in Fall 2024.
Email Address: li@mines.edu
Location: Brown Hall 340
My current research focuses on robot motion planning and task planning. I believe that one key to any robotics application is the algorithm running behind and driving all the hardware. Because of this, one of my goals is to develop robust, generally applicable, and theoretically complete algorithms for robots. In one area of my research, I look at motion planning infeasibility proofs that demonstrate the non-existence of configuration space paths. This also leads to a narrow passage motion planning algorithm. Applying these algorithms in context-sensitive scenarios shows the advantages on HRI robotic systems.
Sihui Li, Neil Dantam, “Scaling Infeasibility Proofs via Concurrent, Codimension-one, Locally-updated Coxeter Triangulation”, IEEE Robotics and Automation Letters (RA-L) (Accepted), 2023.
Sihui Li, Neil Dantam, “A sampling and learning framework to prove motion planning infeasibility”, The International Journal of Robotics Research (IJRR), 2023. Download
Sihui Li, Raagini Rameshwar, Ann Marie Votta, Cagdas Onal. “Intuitive Control of a Robotic Arm and Hand System with Pneumatic Haptic Feedback”, IEEE Robotics and Automation Letters (RA-L), 2019.
Sihui Li, Sriram Siva, Terran Mott, Tom Williams, Hao Zhang, and Neil Dantam, “Failure Explanation in Privacy-Sensitive Contexts: An Integrated Systems Approach”, International Symposium on Robot and Human Interactive Communication (RO-MAN), 2023.
Sihui Li, Neil Dantam, “Sample-Driven Connectivity Learning for Motion Planning”, International Conference on Robotics and Automation (ICRA), 2023. Acceptance Rate 43%. Download
Sihui Li, Neil Dantam, “Exponential Convergence of Infeasibility Proofs For Kinematic Motion Planning”, Algorithmic Foundations of Robotics (WAFR), 2022. Acceptance Rate 56%. Download
Ryan Blake Jackson, Sihui Li, Santosh Balajee Banisetty, Sriram Siva, Hao Zhang, Neil Dantam, and Tom Williams. “An Integrated Approach to Context-Sensitive Moral Cognition in Robot Cognitive Architectures”, IROS 2021, in finalists for Best Paper Award on Cognitive Robotics. Acceptance Rate 45%. Download
Sihui Li, Neil T. Dantam.”Learning Proofs of Motion Planning Infeasibility”, RSS 2021. Acceptance Rate 27%. Download
Sihui Li, Neil T. Dantam, “Towards General Infeasibility Proofs in Motion Planning”, IROS 2020. Acceptance Rate 47%. Download
Sihui Li, Neil Dantam, “Infeasibility Proofs in Task and Motion Planning”, IROS Workshop on Task and Motion Planning: from Theory to Practice, 2023.
Sihui Li, Neil Dantam, “Learning Explicit Infeasibility from Implicit Configuration Space Connectivity”, RSS Workshop on Implicit Representations for Robotic Manipulation, 2022.
Sihui Li, Haowei Zhao, et al.“Learning Motion Primitives and Task Plan in Teleoperated Robot Motion through Multi-modal Interface”, RSS Workshop on Fundamental Issues in Symbiotic Human-Robot Interaction, 2018.
Please see these two project pages Motion Planning Infeasibility Proof and Context-Sensitive Planning.