Lars Olsson
Papers
3
Total Citations
102
H-Index
3
About
Lars Olsson is a pioneering researcher in developmental robotics and autonomous sensorimotor learning. His work focuses on how robots can build internal models of their own bodies and environments from scratch, without any pre-programmed knowledge about their sensors or actuators. In his most influential paper (86 citations), Olsson introduced a groundbreaking system based on information theory that enables a real robot to discover its own sensory and motor apparatus through interaction, learning entirely from raw sensorimotor data. This work challenges traditional approaches that rely on predefined representations. He also developed methods for robots to adaptively detect motion flow by analyzing temporal-informational correlations between sensors and actuators, and conducted innovative experiments inspired by biological studies on visual development, exploring how environments with oriented contours shape a robot’s visual processing. Olsson’s contributions are foundational for creating truly autonomous systems capable of open-ended learning, bridging robotics, cognitive science, and developmental psychology. His research continues to inspire new approaches to artificial intelligence that emphasize self-organization and embodied cognition.
Research Focus
Key Achievements
Top Papers
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