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About

Jeeho Ahn is a roboticist whose research focuses on the intersection of manipulation, planning, and autonomy in cluttered and confined environments. His primary contributions lie in developing algorithms for multi-robot coordination and object retrieval, particularly when overhand grasps are infeasible. In his most cited work, "Coordination of two robotic manipulators for object retrieval in clutter" (2022, 13 citations), Ahn addresses the challenge of retrieving a target object occluded by movable obstacles using two robotic arms, strategically planning which objects to relocate and where to place them to clear a path. This builds on his earlier integrated approach (2021, 13 citations) for determining relocation targets and goal positions within clutter, enabling a single manipulator to systematically clear obstacles. Ahn also explores neuro-symbolic task planning for mobile robot navigation, introducing a fully automatic data collection method (2021, 2 citations) that reduces the labor-intensive process of gathering training images. His work has direct applications in warehouse automation, assistive robotics, and disaster response, where robots must operate in tight, disordered spaces. With over 28 citations across his key papers, Ahn is establishing himself as a rising expert in robotic manipulation and task planning.