Junjun Liu

Huazhong University of Science and Technology, Zhengzhou University of Science and Technology, Beijing University of Technology

Papers

Total Citations

H-Index

About

Junjun Liu is a robotics researcher whose work spans compliant locomotion, computer vision, and path planning. His primary research areas include bio-inspired robotics, legged locomotion on deformable terrains, and intelligent perception systems. Liu’s major contribution is a novel compliance planning method for hydraulically actuated quadruped robots that accounts for ground stiffness—a critical advancement for robots operating on soft surfaces like sand or mud, improving both adaptability and energy efficiency. This work, published in 2021, has garnered 5 citations and addresses a gap in generalized compliant locomotion. In computer vision, Liu proposed a shadow detection method using convolutional block attention modules and unsupervised learning, achieving 3 citations for its novel approach to natural scene processing. He has also contributed to path planning with an aggressive heuristic search algorithm for sub-optimal solutions, cited 2 times, relevant to robotics and AI systems. Liu’s interdisciplinary work demonstrates a commitment to solving real-world robotic challenges, from perception to locomotion, making him a promising voice in the field of intelligent robotics.