Changsuk Oh

Papers

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About

Dr. Changsuk Oh is a leading robotics researcher whose work focuses on the frontiers of multirobot perception, cooperative manipulation, and real-time environmental sensing. His most impactful contribution, the 2021 paper on "Multirobot Collaborative Monocular SLAM Utilizing Rendezvous" (43 citations), addresses the critical challenge of map fusion in multirobot simultaneous localization and mapping (SLAM), enabling teams of robots to systematically construct and merge local maps for coordinated exploration. Building on this, his 2022 work on "Learning and Generalizing Cooperative Manipulation Skills Using Parametric Dynamic Movement Primitives" (21 citations) introduces PDMPs to rapidly generalize complex motion trajectories for mobile manipulators, allowing robots to learn from multiple demonstrations and adapt to new tasks with minimal retraining. Most recently, his 2025 paper on "Real-Time Moving Object Detection for 3-D LiDAR Using Occlusion Accumulation in Range Image" (3 citations) pioneers a GPU-free, deep-learning-free approach that achieves real-time performance by leveraging occlusion patterns, making it ideal for resource-constrained platforms. Dr. Oh’s research consistently pushes toward practical, scalable autonomy—from collaborative mapping to adaptive manipulation and efficient perception—making him a rising voice in modern robotics.