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...
Bewaard in:
Hoofdauteur: | Taş, Ömer Şahin (auth) |
---|---|
Formaat: | Elektronisch Hoofdstuk |
Taal: | Engels |
Gepubliceerd in: |
KIT Scientific Publishing
2023
|
Reeks: | Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie
48 |
Onderwerpen: | |
Online toegang: | OAPEN Library: download the publication OAPEN Library: description of the publication |
Tags: |
Voeg label toe
Geen labels, Wees de eerste die dit record labelt!
|
Gelijkaardige items
-
Motion Planning for Autonomous Vehicles in Partially Observable Environments
door: Taş, Ömer Şahin
Gepubliceerd in: (2023) -
Probabilistic Motion Planning for Automated Vehicles
door: Naumann, Maximilian
Gepubliceerd in: (2021) -
Probabilistic Motion Planning for Automated Vehicles
door: Naumann, Maximilian
Gepubliceerd in: (2021) -
A Contribution to Resource-Aware Architectures for Humanoid Robots
door: Kröhnert, Manfred
Gepubliceerd in: (2017) -
Belief State Planning for Autonomous Driving Planning with Interaction, Uncertain Prediction and Uncertain Perception
door: Hubmann, Constantin
Gepubliceerd in: (2021)