Kurt Malmstrom

About

Kurt Malmstrom is a pioneering researcher in the field of autonomous robotics, with a primary focus on neural network-based control systems and reinforcement learning for mobile robots. His work centers on developing robust, sensor-driven navigation systems that allow robots to learn and adapt to their environments in real time. Malmstrom’s most notable contribution is his 2002 paper, "A simple robust robotic vision system using Kohonen feature mapping," which has garnered 9 citations. In this work, he introduced an innovative method using a one-dimensional Kohonen network to detect the angular position of an infrared beacon from an array of eight sensors mounted on an autonomous vehicle—a simple yet effective solution for robotic vision. He further advanced the field through his research on reinforcement learning, as demonstrated in his 2001 paper on continuous action space learning and his 2002 study on path-finding behavior, where a mobile robot learned to navigate toward goals while avoiding obstacles using neural networks and reinforcement algorithms. Though his citation counts are modest, Malmstrom’s contributions are foundational for students and researchers exploring low-cost, adaptive robotic systems.

Research Focus

Key Achievements

Top Papers

1. 1
   A simple robust robotic vision system using Kohonen feature mapping

   9 citations · 2002
2. 2
   Continuous Action Space Reinforcement Learning on a Real Autonomous Robot

   2 citations · 2001
3. 3
   Reinforcement learning of path-finding behaviour by a mobile robot

   2 citations · 2002

Key Collaborators

Contact & Links