Papers
8
Total Citations
110
H-Index
6
About
Yulong Ding is a leading researcher in multi-robot systems, focusing on cooperative motion planning, coverage control, and autonomous choreography. His work addresses fundamental challenges in coordinating multiple robots for complex tasks, from area coverage and dynamic aggregation to pursuit-evasion scenarios. Ding’s most cited paper (31 citations) introduces a distributed algorithm for cooperative multi-area coverage, enabling robots to jointly cover multiple regions while moving—a framework applicable to demining, garbage clearance, and area scanning. His 2023 paper (23 citations) proposes a distributed encirclement strategy using buffered Voronoi cells, allowing multiple pursuers to capture an evader safely in cluttered environments. Notably, Ding also bridges robotics and cognitive science: his 2019 work (12 citations) creates a computable model of visual aesthetics for evaluating robotic dance poses, while his 2018 paper (11 citations) develops a method for humanoid robots to autonomously generate choreography inspired by human dance creation. With over 100 total citations, Ding’s contributions advance both practical multi-robot coordination and the intersection of robotics with human-like creativity and perception.
Research Focus
Key Achievements
Top Papers
- 1Distributed multi-robot motion planning for cooperative multi-area coverage31 citations · 2017
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- 5Robotic Choreography Inspired by the Method of Human Dance Creation11 citations · 2018
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- 8Continuous Path Planning for Multi-Robot in Intelligent Warehouse2 citations · 2024