Motion Planning for Autonomous Vehicles in Partially Observable Environments
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...
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| Format: | eBook |
| Language: | English |
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KIT Scientific Publishing
2023
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| Series: | Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie
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| Collection: | Directory of Open Access Books - Collection details see MPG.ReNa |
| Summary: | 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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| Item Description: | Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/ |
| Physical Description: | 1 electronic resource (222 p.) |
| ISBN: | 1000158509 9783731512998 |