Jianlong Li

Papers

Total Citations

H-Index

About

Jianlong Li is a researcher working at the intersection of brain-computer interfaces (BCIs), human-robot interaction, and autonomous navigation systems. His work focuses on developing innovative hybrid intelligent systems that bridge human cognitive control with advanced robotic capabilities, enabling more intuitive and efficient human-machine collaboration. Li's most notable contribution is his development of a human-robot hybrid intelligent system that integrates motor-imagery-based brain teleoperation with deep learning-driven simultaneous localization and mapping (SLAM). Published in 2019, this work — which has garnered 53 citations — demonstrates how electroencephalographic (EEG) signals generated through motor imagery can be harnessed to teleoperate mobile robots navigating entirely unknown environments, with deep learning enhancing the robot's active perception and spatial awareness. His earlier 2018 work laid foundational groundwork for this direction, exploring brain-robot interface (BRI) systems combined with SLAM to achieve reliable navigation and control. By merging neuroscience-inspired control paradigms with cutting-edge machine learning techniques, Li's research holds significant promise for assistive robotics, rehabilitation technologies, and next-generation autonomous systems. His contributions offer meaningful pathways toward empowering individuals with motor impairments and advancing the broader field of intelligent human-robot collaboration.