4 citations · 6 across the 4 of their papers we have counts for
8 papers
Characterising the Robustness of Reinforcement Learning for Continuous Control using Disturbance Injection
Catherine R. Glossop, Jacopo Panerati, Amrit Krishnan +2
In this study, we leverage the deliberate and systematic fault-injection capabilities of an open-source benchmark suite to perform a series of experiments on state-of-the-art deep…
Learning-based Bias Correction for Time Difference of Arrival Ultra-wideband Localization of Resource-constrained Mobile Robots
Wenda Zhao, Jacopo Panerati, Angela P. Schoellig
Accurate indoor localization is a crucial enabling technology for many robotics applications, from warehouse management to monitoring tasks. Ultra-wideband (UWB) time difference of…
Learning to Fly -- a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Control
Jacopo Panerati, Hehui Zheng, SiQi Zhou +3
Robotic simulators are crucial for academic research and education as well as the development of safety-critical applications. Reinforcement learning environments -- simple simulat…
Learning-based Bias Correction for Ultra-wideband Localization of Resource-constrained Mobile Robots
Wenda Zhao, Abhishek Goudar, Jacopo Panerati +1
Accurate indoor localization is a crucial enabling technology for many robotics applications, from warehouse management to monitoring tasks. Ultra-wideband (UWB) ranging is a promi…
Multi-Vehicle Mixed-Reality Reinforcement Learning for Autonomous Multi-Lane Driving
Rupert Mitchell, Jenny Fletcher, Jacopo Panerati +1
Autonomous driving promises to transform road transport. Multi-vehicle and multi-lane scenarios, however, present unique challenges due to constrained navigation and unpredictable…
Decentralized Connectivity Control in Quadcopters: a Field Study of Communication Performance
Jacopo Panerati, Benjamin Ramtoula, David St-Onge +5
Redundancy and parallelism make decentralized multi-robot systems appealing solutions for the exploration of extreme environments. However, effective cooperation often requires tea…