Kenneth Tze Kin Teo
Papers
5
Total Citations
61
H-Index
4
About
Kenneth Tze Kin Teo is a leading researcher in robotics and artificial intelligence, with a primary focus on autonomous navigation, multi-robot coordination, and deep reinforcement learning. His most influential work, "Deep Reinforcement Learning with Robust Deep Deterministic Policy Gradient" (2020, 39 citations), addresses critical stability issues in continuous control algorithms, advancing their application in autonomous driving and robotics. Teo has also made significant contributions to mobile robotics, including the development of wireless device-controlled navigation systems (2012) and comprehensive reviews of four-wheeled mobile robots (2022). His research on swarm robotics, particularly "Enhancement of Ant Colony Optimization in Multi-Robot Source Seeking Coordination" (2019, 6 citations), introduces dynamic approaches to optimize power usage and coordination in multi-robot systems. Additionally, Teo has explored 3D solid robot animation design using ADAMS (2021), demonstrating his versatility across hardware and simulation platforms. With a career spanning over a decade, his work has garnered increasing attention, reflecting the growing relevance of his contributions to autonomous systems and intelligent control.
Research Focus
Key Achievements
Top Papers
- 1Deep Reinforcement Learning with Robust Deep Deterministic Policy Gradient39 citations · 2020
- 2
- 3Four Wheeled Mobile Robots: A Review6 citations · 2022
- 4
- 53D solid robot animation design based on ADAMS3 citations · 2021