Papers
59
Total Citations
9,764
H-Index
26
About
Ian Reid is a pioneering researcher whose work spans computer vision, robotics, and simultaneous localization and mapping (SLAM). He is perhaps best known for co-developing MonoSLAM, the first real-time monocular visual SLAM system, which demonstrated that a single camera could recover 3D trajectories in unknown environments — a landmark contribution that has accumulated nearly 4,000 citations and fundamentally shaped modern robotic navigation. His co-authored survey on the past, present, and future of SLAM (3,158 citations) stands as a definitive reference for the field, charting three decades of progress toward robust, large-scale perception. Beyond classical SLAM, Reid has made significant contributions to semantic and object-oriented mapping, bridging geometric understanding with high-level scene interpretation. His deep learning work includes AffordanceNet for object affordance detection and Deep-6DPose for 6D object pose estimation, reflecting his drive to enable richer robot-world interaction. Practical achievement is equally evident in his team's victory at the Amazon Robotics Challenge with the Cartman manipulator. Across trajectory forecasting, active SLAM, and semantic robotics surveys, Reid's research consistently advances both theory and real-world deployment, cementing his status as a central figure in modern robot perception.
Research Focus
Key Achievements
Top Papers
- 1MonoSLAM: Real-Time Single Camera SLAM3,909 citations · 2007
- 2Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age3,158 citations · 2016
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- 5Meaningful maps – Object-oriented semantic mapping225 citations · 2017
- 6Real-Time SLAM Relocalisation224 citations · 2007
- 7On the comparison of uncertainty criteria for active SLAM143 citations · 2012
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- 9Deep-6DPose: Recovering 6D Object Pose from a Single RGB Image129 citations · 2018
- 10Semantics for Robotic Mapping, Perception and Interaction: A Survey100 citations · 2020