Probabilistic Safety Constraints for Learned High Relative Degree System Dynamics
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Abstract (arXiv)
This paper focuses on learning a model of system dynamics online while satisfying safety constraints.Our motivation is to avoid offline system identification or hand-specified dynamics models and allowa system to safely and autonomously estimate and adapt its own model during online operation.Given streaming observations of the system state, we use Bayesian learning to obtain a distributionover the system dynamics. In turn, the distribution is used to optimize the system behavior andensure safety with high probability, by specifying a chance constraint over a control barrier function.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Dec 2019.
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Citing papers per year: 2021: 4; 2022: 3; 2023: 0; 2024: 1; 2025: 1.
9 papers.
- 2021Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learningcited by 371
- 2022Sample-efficient Safe Learning for Online Nonlinear Control with Control Barrier Functionscited by 3
- 2022Safe Exploration Method for Reinforcement Learning under Existence of Disturbancecited by 3
- 2022Safe Reinforcement Learning with Probabilistic Control Barrier Functions for Ramp Mergingcited by 1
- 2024Robust Model Based Reinforcement Learning Using L1 Adaptive Controlcited by 1
- 2021Robustifying Reinforcement Learning Policies with L1 Adaptive Controlcited by 0
- 2021Guaranteed Trajectory Tracking under Learned Dynamics with Contraction Metrics and Disturbance Estimationcited by 0
- 2021ProBF: Learning Probabilistic Safety Certificates with Barrier Functionscited by 0
- 2025Safely Learning Controlled Stochastic Dynamicscited by 0
- 2025Safely Learning Controlled Stochastic Dynamics3 Jun 2025
- 2024Robust Model Based Reinforcement Learning Using L1 Adaptive Control21 Mar 2024
- 2022Safe Reinforcement Learning with Probabilistic Control Barrier Functions for Ramp Merging1 Dec 2022
- 2022Safe Exploration Method for Reinforcement Learning under Existence of Disturbance30 Sep 2022
- 2022Sample-efficient Safe Learning for Online Nonlinear Control with Control Barrier Functions29 Jul 2022
- 2021ProBF: Learning Probabilistic Safety Certificates with Barrier Functions22 Dec 2021
- 2021Guaranteed Trajectory Tracking under Learned Dynamics with Contraction Metrics and Disturbance Estimation15 Dec 2021
- 2021Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning13 Aug 2021
- 2021Robustifying Reinforcement Learning Policies with L1 Adaptive Control4 Jun 2021