Chen Che

University of Michigan–Ann Arbor

Papers

2

Total Citations

12

H-Index

2

About

Chen Che’s research lies at the intersection of safe motion planning, real-time control, and robust manipulation for articulated robots. His major contributions focus on developing algorithms that enable manipulators to operate reliably under uncertainty—accounting for unknown object masses, inertias, and environmental unpredictability. In his 2024 work, “Safe Planning for Articulated Robots Using Reachability-based Obstacle Avoidance With Spheres,” Che introduced a novel reachability framework that represents robot geometry with spheres, allowing for efficient collision avoidance without sacrificing safety. Building on this, his 2025 paper, “Can Not Touch This,” proposes an optimization-based approach for real-time, safe motion planning that simultaneously handles collision avoidance, joint limits, and dynamic uncertainties—a critical step toward deploying robots in unstructured, human-centric environments. Though early in his career, Che’s work has already garnered over a dozen citations, reflecting its immediate relevance to the robotics community. His achievements include pioneering methods that bridge the gap between theoretical safety guarantees and practical, real-time implementation, positioning him as an emerging leader in autonomous manipulation and safe robotics.

Research Focus

Key Achievements

2
H-Index
2
Papers
12
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Safe Planning for Articulated Robots Using Reachability-based Obstacle Avoidance With Spheres
6 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: University of Michigan–Ann Arbor

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago