Name
Abstract | ||
|---|---|---|
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 allow a 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 distribution over the system dynamics. In turn, the distribution is used to optimize the system behavior and ensure safety with high probability, by specifying a chance constraint over a control barrier function. |
Year | Venue | DocType |
|---|---|---|
2020 | L4DC | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammad J. Khojasteh | 1 | 9 | 5.00 |
| Vikas Dhiman | 2 | 5 | 2.81 |
| Massimo Franceschetti | 3 | 2200 | 167.33 |
| Nikolay Atanasov | 4 | 162 | 24.84 |