Projects per year
Abstract
Modern autonomous systems rely on perception modules to process complex sensor measurements into state estimates. These estimates are then passed to a controller, which uses them to make safety-critical decisions. It is therefore important that we design perception systems to minimize errors that reduce the overall safety of the system. We develop a risk-driven approach to designing perception systems that accounts for the effect of perceptual errors on the performance of the fully-integrated, closed-loop system. We formulate a risk function to quantify the effect of a given perceptual error on overall safety, and show how we can use it to design safer perception systems by including a risk-dependent term in the loss function and generating training data in risk-sensitive regions. We evaluate our techniques on a realistic vision-based aircraft detect and avoid application and show that risk-driven design reduces collision risk by 37% over a baseline system.
Original language | English |
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Title of host publication | Proceedings of the NeurIPS 2022 |
Number of pages | 17 |
Publication status | Accepted/In press - 14 Sep 2022 |
Event | The 36th Conference on Neural Information Processing Systems, 2022 - New Orleans, United States Duration: 28 Nov 2022 → 9 Dec 2022 Conference number: 36 https://neurips.cc/Conferences/2022 |
Conference
Conference | The 36th Conference on Neural Information Processing Systems, 2022 |
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Abbreviated title | NeurIPS 2022 |
Country/Territory | United States |
City | New Orleans |
Period | 28/11/22 → 9/12/22 |
Internet address |
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Dive into the research topics of 'Risk-Driven Design of Perception Systems'. Together they form a unique fingerprint.Projects
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UKRI Trustworthy Autonomous Systems Node in Governance and Regulation
Ramamoorthy, R., Belle, V., Bundy, A., Jackson, P., Lascarides, A. & Rajan, A.
1/11/20 → 30/04/24
Project: Research