motion-planning-for-autonomous-vehicles-in-partially-observable-environments.pdf
This work develops a motion planner that compensates the deficiencies from perception modules by exploiting the reaction capabilities of a vehicle. The work analyzes present uncertainties and defines driving objectives together with constraints that ensure safety. The resulting problem is solved in...
| Γλώσσα: | English |
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| Έκδοση: |
KIT Scientific Publishing
2023
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| Διαθέσιμο Online: | https://doi.org/10.5445/KSP/1000158509 |
| Περίληψη: | This work develops a motion planner that compensates the deficiencies from perception modules by exploiting the reaction capabilities of a vehicle. The work analyzes present uncertainties and defines driving objectives together with constraints that ensure safety. The resulting problem is solved in real-time, in two distinct ways: first, with nonlinear optimization, and secondly, by framing it as a partially observable Markov decision process and approximating the solution with sampling. |
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