Yongqiang Qi

China University of Mining and Technology

Papers

Total Citations

H-Index

About

Yongqiang Qi is a robotics researcher whose work focuses on intelligent motion planning and control for autonomous systems operating in challenging environments. His key research areas include space robotics, snake-like locomotion, and autonomous rescue robotics. Qi’s most notable contribution is the development of a path-integral-based reinforcement learning algorithm for goal-directed locomotion of snake-shaped robots in complex 3D environments, published in 2021. This model-free online Q-learning approach enables snake robots to optimize decision-making through repeated exploration-learning cycles, advancing the field of bio-inspired robotics. His 2017 work on space robot active collision avoidance under thruster failure addresses critical safety concerns in orbital operations, while his 2020 study on fast path planning for on-water rescue robots using the constant thrust artificial fluid method demonstrates practical applications in emergency response. Though his citation counts are currently modest—with his top papers garnering 5 and 2 citations respectively—Qi’s research represents important foundational work at the intersection of reinforcement learning, path planning, and autonomous systems. His contributions to snake robot locomotion and rescue robotics highlight his commitment to developing intelligent, adaptive solutions for real-world robotic challenges.