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IBUKI TATSUYA
Department Undergraduate School , School of Science and Technology Position Associate Professor |
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| Language | English |
| Publication Date | 2022/09 |
| Type | Academic Journal |
| Peer Review | Peer reviewed |
| Title | Gaussian Control Barrier Functions: Non-Parametric Paradigm to Safety |
| Contribution Type | Co-authored (other than first author) |
| Journal | IEEE Access |
| Journal Type | Another Country |
| Publisher | The Institute of Electrical and Electronics Engineers (IEEE) |
| Volume, Issue, Page | 10,pp.99823-99836 |
| Total page number | 14 |
| International coauthorship | International coauthorship |
| Author and coauthor | Mouhyemen Khan, Tatsuya Ibuki, Abhijit Chatterjee |
| Details | We propose a non-parametric approach for online synthesis of CBFs using Gaussian Processes (GPs). A dynamical system is defined to be safe if a subset of its states remains within the prescribed set, also called the safe set. CBFs achieve safety by designing a candidate function a priori. However, designing such a function can be challenging. Consider designing a CBF in a disaster recovery scenario where safe and navigable regions need to be determined. The decision boundary for safety here is unknown and cannot be designed a priori. Moreover, CBFs employ a parametric design approach and cannot handle arbitrary changes to the safe set in practice. In our approach, we work with safety samples to construct the CBF online by assuming a flexible GP prior on these samples, and term our formulation as a Gaussian CBF. GPs have favorable properties such as analytical tractability and robust uncertainty estimation. |