Weichuang Li

Papers

Total Citations

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About

Weichuang Li is a roboticist whose research centers on perception-driven manipulation, particularly the challenge of grasping occluded objects in cluttered environments. His most-cited work, "Affordance-Driven Next-Best-View Planning for Robotic Grasping" (2023), introduces ACE-NBV, a policy that actively selects viewpoints to reveal hidden object affordances, enabling robots to iteratively observe and execute feasible grasps. This contribution addresses a critical bottleneck in autonomous manipulation—how to handle visual occlusion without exhaustive exploration. By framing the problem as an affordance-guided search, Li’s approach reduces computational overhead while improving grasp success rates in dense clutter. Though early in his career, his work has already garnered attention (6 citations), reflecting its relevance to the growing field of active perception. Li’s research bridges computer vision and robotics, offering practical solutions for warehouse automation, assistive robotics, and household tasks. His focus on affordance-driven planning marks him as a promising voice in next-generation robotic manipulation, where intelligent observation is as vital as dexterous execution.