L. Munday
Papers
2
Total Citations
11
H-Index
2
About
L. Munday is a researcher in mobile robotics and neural network control systems, with a focus on enabling autonomous navigation through bio-inspired learning algorithms. Their work centers on two key areas: vision-based localization and reinforcement learning for path-finding. In their most-cited paper, "A simple robust robotic vision system using Kohonen feature mapping" (2002, 9 citations), Munday introduced an innovative method for detecting the angular position of an infrared beacon using a one-dimensional Kohonen self-organizing map. This approach allowed an experimental autonomous vehicle to robustly determine beacon direction from eight analog infrared detector signals arranged in a semi-circle. In a complementary study, "Reinforcement learning of path-finding behaviour by a mobile robot" (2002, 2 citations), Munday demonstrated how a simple mobile robot could learn to navigate toward a goal while avoiding obstacles. By employing a neural network that maps infrared sensor inputs to motor actions, and adjusting connection weights through reinforcement learning, the robot autonomously developed effective navigation strategies. Though modest in citation counts, Munday's contributions represent early, practical applications of neural network learning—both unsupervised and reinforcement-based—to real-world robotic control, laying groundwork for adaptive autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1A simple robust robotic vision system using Kohonen feature mapping9 citations · 2002
- 2Reinforcement learning of path-finding behaviour by a mobile robot2 citations · 2002