Papers
7
Total Citations
405
H-Index
4
About
Jinge Wang is a pioneering roboticist whose research spans dynamic visual perception, bio-inspired locomotion, and mechanical design for intelligent robots. His most impactful contribution, "Dynamic-SLAM: Semantic monocular visual localization and mapping based on deep learning in dynamic environment" (2019, 344 citations), revolutionized visual SLAM by integrating deep learning to handle moving objects—a critical advancement for autonomous robots operating in real-world, cluttered settings. Wang also made significant strides in legged locomotion with his work on gait planning and stability control for quadruped robots, where he developed a novel CPG-ZMP controller to generate smooth gaits and reduce oscillation. His innovative mechanical designs include a drum worm pair for robot joint reducers, addressing the need for compact, high-torque actuators in modular robots. More recently, Wang has explored underwater perception with a fish-like binocular vision system for robotic fish, inspired by biological eye arrangements to achieve broad-spectrum visual perception. His early work on humanoid robot simulation and soccer robot path planning using arc-cotangent optimization demonstrates a long-standing commitment to bridging theory and application. With over 400 total citations, Wang’s research continues to shape the fields of semantic mapping, bio-inspired robotics, and autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1
- 2Gait Planning and Stability Control of a Quadruped Robot43 citations · 2016
- 3Design and manufacture of the novel drum worm pair6 citations · 2020
- 4Study on Simulation for Humanoid Robot5 citations · 2008
- 5
- 6Soccer Robot Path Planning based on Arc-cotangent Optimization Algorithm2 citations · 2008
- 7