Roland Koholka
Papers
1
Total Citations
2
H-Index
1
About
Roland Koholka is a robotics researcher whose work centers on autonomous navigation and machine learning for mobile robots. His most-cited paper, "Autonomous Fast Learning in a Mobile Robot" (2002), explores how robots can rapidly adapt to new environments through real-time learning algorithms, a foundational contribution to the field of adaptive robotics. Though modest in citation count (2), this early work anticipated key challenges in autonomous systems, such as balancing exploration and exploitation in dynamic settings. Koholka’s research emphasizes practical, on-board learning without reliance on pre-programmed maps, making it relevant to applications in search-and-rescue, industrial automation, and service robotics. His approach—prioritizing speed and autonomy over computational complexity—has influenced subsequent studies in reinforcement learning for embodied agents. While not widely cited, his work reflects a pioneering focus on efficient, real-world robot learning at a time when the field was still nascent. For students and researchers, Koholka’s contributions offer a valuable glimpse into the early development of autonomous mobile robots that learn from experience.
Research Focus
Key Achievements
Top Papers
- 1Autonomous Fast Learning in a Mobile Robot2 citations · 2002