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...
में बचाया:
| मुख्य लेखक: | |
|---|---|
| स्वरूप: | इलेक्ट्रोनिक पुस्तक अध्याय |
| भाषा: | अंग्रेज़ी |
| प्रकाशित: |
KIT Scientific Publishing
2023
|
| श्रृंखला: | Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie
48 |
| विषय: | |
| ऑनलाइन पहुंच: | OAPEN Library: download the publication OAPEN Library: description of the publication |
| टैग: |
टैग जोड़ें
कोई टैग नहीं, इस रिकॉर्ड को टैग करने वाले पहले व्यक्ति बनें!
|
MARC
| LEADER | 00000naaaa2200000uu 4500 | ||
|---|---|---|---|
| 001 | oapen_2024_20_500_12657_77094 | ||
| 005 | 20231031 | ||
| 003 | oapen | ||
| 006 | m o d | ||
| 007 | cr|mn|---annan | ||
| 008 | 20231031s2023 xx |||||o ||| 0|eng d | ||
| 020 | |a KSP/1000158509 | ||
| 040 | |a oapen |c oapen | ||
| 024 | 7 | |a 10.5445/KSP/1000158509 |c doi | |
| 041 | 0 | |a eng | |
| 042 | |a dc | ||
| 072 | 7 | |a TNK |2 bicssc | |
| 100 | 1 | |a Taş, Ömer Şahin |4 auth | |
| 245 | 1 | 0 | |a Motion Planning for Autonomous Vehicles in Partially Observable Environments |
| 260 | |b KIT Scientific Publishing |c 2023 | ||
| 300 | |a 1 electronic resource (222 p.) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie |v 48 | |
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a 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. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
| 546 | |a English | ||
| 650 | 7 | |a Building construction & materials |2 bicssc | |
| 653 | |a Robotics; Planning under Uncertainty; Decision Making; Information Gathering; Motion Planning; Robotik; Automatisiertes Fahren; Planung unter Unsicherheiten; Entscheidungsfindung; Bewegungsplanung | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://library.oapen.org/bitstream/id/5bb51f9e-8964-4bf0-8fc1-1a6d60d14be3/motion-planning-for-autonomous-vehicles-in-partially-observable-environments.pdf |7 0 |z OAPEN Library: download the publication |
| 856 | 4 | 0 | |a www.oapen.org |u https://library.oapen.org/handle/20.500.12657/77094 |7 0 |z OAPEN Library: description of the publication |