Simultaneous Lane-Keeping and Obstacle Avoidance by Combining Model Predictive Control and Control Barrier Functions
We combine Model Predictive Control (MPC) and Control Barrier Function (CBF) design methods to create a hierarchical control law for simultaneous lane-keeping (LK) and obstacle avoidance (OA): at the low level, MPC performs LK via trajectory tracking during nominal operation; and at the high level,...
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Published in | Proceedings of the IEEE Conference on Decision & Control pp. 5285 - 5290 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
06.12.2022
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Subjects | |
Online Access | Get full text |
ISSN | 2576-2370 |
DOI | 10.1109/CDC51059.2022.9992613 |
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Summary: | We combine Model Predictive Control (MPC) and Control Barrier Function (CBF) design methods to create a hierarchical control law for simultaneous lane-keeping (LK) and obstacle avoidance (OA): at the low level, MPC performs LK via trajectory tracking during nominal operation; and at the high level, various CBF-based safety filters that ensure LK and OA are designed and compared across practical scenarios. In particular, we show that Exponential Safety (ESf) and Prescribed-Time Safety (PTSf) filters, which override the MPC control when necessary, result in feasible Quadratic Programs when OA-safety is prioritized. We additionally investigate control designs subject to input constraints by using Input-Constrained-CBFs. Finally, we compare the performance of combinations of ESf, PTSf, and their input-constrained counterparts with respect to the LK and OA goals in two simulation studies for early- and late-detected obstacle scenarios. |
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ISSN: | 2576-2370 |
DOI: | 10.1109/CDC51059.2022.9992613 |