Anders Moe

Linköping University, University of British Columbia

Papers

Total Citations

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About

Anders Moe is a researcher whose work lies at the intersection of autonomous robotics and multi-agent systems, with a particular focus on enabling robots to perceive and interact with their environments without human intervention. His major contributions include pioneering methods for autonomous object discovery, where robots learn to recognize objects by physically exploring and manipulating their surroundings—a paradigm shift from pre-programmed recognition. In his most cited work, "Autonomous Learning of Object Appearances using Colour Contour Frames" (2006, 11 citations), Moe introduced a robust technique using colour contour frames to replace simple colour histograms, significantly improving a robot's ability to discriminate and learn object appearances through active probing. He further advanced the field of aerial robotics with "Single and Multi-UAV Relative Position Estimation Based on Natural Landmarks" (2008, 5 citations), addressing the critical challenge of UAV localization without GPS by leveraging natural environmental features. Though his citation counts reflect a focused, niche impact, Moe’s work is foundational for researchers in developmental robotics and autonomous exploration, demonstrating how robots can bootstrap their own understanding of the world through embodied interaction.