
Open access
Date
2015Type
- Journal Article
Abstract
In this work an overview of the local mo-tion planning and dynamic perception framework withinthe V-Charge project is presented. This framework en-ables the V-Charge car to autonomously navigate in dy-namic mixed-traffic scenarios. Other traffic participantsare detected, classified and tracked from a combinationof stereo and wide-angle monocular cameras. Predictionsof their future movements are generated utilizing infras-tructure information. Safe motion plans are acquired witha system-compliant sampling-based local motion planner.We show the navigation performance of this vision-onlyautonomous vehicle in both simulation and real-world ex-periments. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000112343Publication status
publishedExternal links
Journal / series
it - Information TechnologyVolume
Pages / Article No.
Publisher
De GruyterSubject
Automotive; autonomous navigation; motion planning; environment perceptionOrganisational unit
03737 - Siegwart, Roland Y. / Siegwart, Roland Y.
Funding
269916 - V-Charge - Autonomous Valet Parking and Charging for e-Mobility (EC)
Notes
It was possible to publish this article open access thanks to a Swiss National Licence with the publisher.More
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