Qihang Li

University at Buffalo, State University of New York

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About

Qihang Li is a rising researcher in robotics and autonomous systems, with a primary focus on kinematics-aware planning and imperative learning for trajectory generation. His most notable contribution is the development of iKap (Kinematics-Aware Planning with Imperative Learning), a pioneering framework that bridges vision-based perception and motion planning by enabling robots to generate collision-free pose sequences that are both interpretable and reliably executable in dynamic environments. This work addresses a critical bottleneck in traditional modular systems—the gap between high-level scene understanding and low-level kinematic feasibility—by integrating learning-based adaptability with geometric constraints. Although early in its impact trajectory, iKap has already garnered 2 citations since its 2025 publication, signaling growing interest from the robotics community. Li’s research is particularly significant for advancing vision-to-planning pipelines, which promise to make autonomous systems more efficient and responsive in real-world settings such as manufacturing, service robotics, and autonomous navigation. His work exemplifies a modern, learning-informed approach to classical motion planning challenges, positioning him as a promising contributor to the next generation of intelligent robotic systems.