Papers

2

Total Citations

25

H-Index

2

About

Hippolyte Watrelot is a robotics researcher advancing the frontiers of autonomous manipulation and logistics through data-driven methods and multi-robot coordination. His primary research areas include robotic grasping, sim-to-real transfer, and heterogeneous robot teams for real-world service applications. Watrelot’s most cited work, "Domain Randomization for Sim2real Transfer of Automatically Generated Grasping Datasets" (2024, 20 citations), tackles a critical challenge in data-driven grasping: the sparse reward problem that hinders learning. By introducing domain randomization techniques for automatically generated datasets, he enables more robust transfer of grasping policies from simulation to reality without constraining the learning process. This contribution is pivotal for scalable, cost-effective robotic manipulation. In parallel, his involvement in the euROBIN First-Year Robotics Hackathon (2024, 5 citations) demonstrates his ability to integrate heterogeneous robot teams—spanning logistics, outdoor, and domestic morphologies—for end-to-end door-to-door parcel delivery. This work showcases a practical vision of fully autonomous logistics from supply point to user’s home. Watrelot’s research bridges fundamental algorithmic innovation with tangible, multi-robot systems, making him a promising voice in the future of service robotics and autonomous grasping.

Research Focus

Key Achievements

2
H-Index
2
Papers
25
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
Domain Randomization for Sim2real Transfer of Automatically Generated Grasping Datasets
20 citations · 2024
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 67
🏛 Institutions: Sorbonne Université, Centre National de la Recherche Scientifique

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago