Ding-Gong Sung
Papers
1
Total Citations
7
H-Index
1
About
Ding-Gong Sung is a robotics researcher whose work focuses on developing autonomous locomotion strategies for transformable robots, particularly those combining legged and wheeled mobility. His key contributions center on enabling robots to perceive and adapt to complex terrains through real-time environmental sensing. In his most cited work, Sung introduced a behavior decision strategy for the leg-wheel transformable robot TurboQuad-V, leveraging RGBD data to classify terrain and select optimal gaits. By integrating dynamic simulation results with onboard perception, his system allows the robot to autonomously switch between walking and rolling modes, navigate obstacles, and maintain stability in unstructured environments. This research has garnered 7 citations and demonstrates a practical approach to bridging perception and control in hybrid robotic systems. Sung’s work is notable for its emphasis on real-time decision-making, offering a foundation for future autonomous robots operating in disaster response, exploration, or industrial inspection. His contributions highlight the importance of combining simulation-driven gait analysis with sensor-based adaptation, advancing the field of mobile robotics toward more versatile and resilient platforms.
Research Focus
Key Achievements
Top Papers
- 1