31 citations · 55 across the 12 of their papers we have counts for
4 papers · 1 filter
safe-control-gym: a Unified Benchmark Suite for Safe Learning-based Control and Reinforcement Learning in Robotics
Zhaocong Yuan, Adam W. Hall, Siqi Zhou +4
In recent years, both reinforcement learning and learning-based control -- as well as the study of their safety, which is crucial for deployment in real-world robots -- have gained…
Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning
Lukas Brunke, Melissa Greeff, Adam W. Hall +4
The last half-decade has seen a steep rise in the number of contributions on safe learning methods for real-world robotic deployments from both the control and reinforcement learni…
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…