Junke Li

Southwest University, Suqian University, Sichuan University

Papers

Total Citations

H-Index

About

Junke Li is a robotics researcher whose work spans gesture-based human-robot interaction, legged locomotion, and autonomous navigation in challenging environments. Li’s most cited paper, “Hand gesture recognition system using depth data” (2012, 24 citations), introduced a novel method for recognizing predefined gestures from Kinect depth images to control mobile robots, laying groundwork for intuitive, vision-based interfaces. Expanding into mechanical design, Li’s “Design of a hexapod robot” (2012, 7 citations) presented a modular, wheel-leg hybrid platform capable of autonomously adapting to varied terrain and surmounting obstacles—a key contribution to field robotics. More recently, Li has tackled indoor localization with “Mobile Robot Localization in Geometrically Similar Environment Combining Wi-Fi with Laser SLAM” (2023, 2 citations), fusing wireless signals with laser mapping to overcome GPS-denied scenarios. Li has also explored aquatic robotics through “Target Tracking with Energy Efficiency Using Robotic Fish-based Sensor Networks” (2016, 2 citations), demonstrating energy-efficient tracking in underwater sensor networks. With a cumulative citation impact of over 35, Li’s work bridges perception, mechanical design, and multi-modal localization, advancing robots from the lab floor to real-world terrains—both on land and underwater.