Papers
17
Total Citations
1,015
H-Index
12
About
Jacopo Panerati is a robotics researcher whose work spans safe learning-based control, swarm robotics, and autonomous systems. He is perhaps best known for his foundational contributions to the intersection of machine learning and robot safety — his 2022 review "Safe Learning in Robotics" has accumulated an remarkable 654 citations, establishing itself as a definitive reference for researchers navigating the rapidly evolving landscape of safe reinforcement learning and learning-based control for real-world deployment. Complementing this, his development of **Safe-Control-Gym**, a unified benchmarking suite for safe learning in robotics, has helped standardize evaluation practices across the community. Beyond safety, Panerati has made significant contributions to swarm robotics, tackling challenges such as robust area coverage, connectivity maintenance, and resilient multi-robot topologies — work with notable implications for planetary exploration using autonomous robot teams. His research on UWB-based indoor localization and privacy-preserving flocking further demonstrates his range across practical and theoretical robotics challenges. His open-source simulation environments, including a PyBullet-based quadcopter gym, reflect a commitment to accessible, reproducible research infrastructure. Collectively, his portfolio positions him as a versatile and influential voice shaping the future of trustworthy autonomous robotics.
Research Focus
Key Achievements
Top Papers
- 1
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- 3Robust Area Coverage with Connectivity Maintenance48 citations · 2019
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- 6Robust connectivity maintenance for fallible robots30 citations · 2018
- 7An Adversarial Approach to Private Flocking in Mobile Robot Teams28 citations · 2020
- 8
- 9Self-optimization of resilient topologies for fallible multi-robots17 citations · 2019
- 10