Tong Guo
Papers
6
Total Citations
88
H-Index
5
About
Tong Guo is a leading researcher in bio-inspired robotics, with a primary focus on the locomotion and control of legged walking robots. His work is distinguished by its integration of biological principles with advanced engineering to solve fundamental challenges in robot mobility. A major contribution is his development of a backward control system based on a σ-Hopf oscillator, which allows for the decoupling of key parameters to generate smooth, adaptive gaits in bio-inspired legged robots (28 citations). To address the practical issue of trajectory inaccuracies caused by rolling feet, Guo proposed a novel trajectory correction methodology using Least Squares Support Vector Machines (LS-SVM) and the concept of ideal footholds (16 citations). His research also extends to sensory integration, where he developed a simple yet robust obstacle detection algorithm fusing depth and infrared data to improve recognition rates in outdoor environments (15 citations). Notably, Guo has drawn inspiration from ant behavior to devise turning and deviation correction strategies for hexapod robots, and has optimized galloping trajectories for transport robots to minimize energy consumption. With a cumulative impact of nearly 100 citations across his most prominent works, Tong Guo’s research is pivotal for advancing the autonomy and efficiency of legged robots in unstructured, real-world settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6