Reactive Obstacle Avoidance for Highly Maneuverable Vehicles Based on a Two-Stage Optical Flow Clustering
This paper proposes a reactive obstacle avoidance approach based solely on image data from a monocular camera stream. By clustering and analyzing the optical flow, this approach is able to identify potential collisions with dynamic obstacles. Epipolar geometry is exploited to derive velocity command...
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| Veröffentlicht in: | IEEE transactions on intelligent transportation systems 2017-08, Vol.18 (8), p.2137-2152 |
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| container_title | IEEE transactions on intelligent transportation systems |
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| creator | Schaub, Alexander Baumgartner, Daniel Burschka, Darius |
| description | This paper proposes a reactive obstacle avoidance approach based solely on image data from a monocular camera stream. By clustering and analyzing the optical flow, this approach is able to identify potential collisions with dynamic obstacles. Epipolar geometry is exploited to derive velocity commands that ensure a collision-free path for a highly maneuverable autonomous vehicle via a real-time optimizer. First, the underlying image processing and optimization principles are explained in detail, before simulation results show the general feasibility of the approach. Finally, real-world tests with the ROboMObil, the German Aerospace Center's robotic electric vehicle, are provided to demonstrate its applicability. |
| doi_str_mv | 10.1109/TITS.2016.2633292 |
| format | Article |
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Finally, real-world tests with the ROboMObil, the German Aerospace Center's robotic electric vehicle, are provided to demonstrate its applicability.</description><subject>Adaptive optics</subject><subject>Biomedical optical imaging</subject><subject>Cameras</subject><subject>Clustering</subject><subject>Collision avoidance</subject><subject>Collision dynamics</subject><subject>Commands</subject><subject>Computer terminals</subject><subject>Dynamics</subject><subject>Image processing</subject><subject>intelligent vehicles</subject><subject>Obstacle avoidance</subject><subject>optical feedback</subject><subject>Optical flow (image analysis)</subject><subject>Optical imaging</subject><subject>Optical sensors</subject><subject>optimization</subject><issn>1524-9050</issn><issn>1558-0016</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kF1LwzAUhosoOKc_QLwJeN2Zj6ZpLudwbjAZuOptSbPTLaM2M2k39u9N2fDqHA7P-x54ouiR4BEhWL7k83w1opikI5oyRiW9igaE8yzG4Xbd7zSJJeb4NrrzfheuCSdkEJlPULo1B0DL0rdK14DGB2vWqtGAKuvQzGy29Ql9qAa6AzhVBuIbtiaQHr0qD2tkG6RQfrTxqlWbULRvjVY1mtb2iCZ151twptncRzeVqj08XOYw-pq-5ZNZvFi-zyfjRaypZG3MOWZCJ5izDDjVMq24XmMhsKSaSJyWMkugEoFKBauY1GnAZcmSilIBULJh9Hzu3Tv724Fvi53tXBNeFkTSVEjBkiRQ5ExpZ713UBV7Z36UOxUEF73Rojda9EaLi9GQeTpnDAD880JklKWU_QFXZXD8</recordid><startdate>20170801</startdate><enddate>20170801</enddate><creator>Schaub, Alexander</creator><creator>Baumgartner, Daniel</creator><creator>Burschka, Darius</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| source | IEEE Electronic Library (IEL) |
| subjects | Adaptive optics Biomedical optical imaging Cameras Clustering Collision avoidance Collision dynamics Commands Computer terminals Dynamics Image processing intelligent vehicles Obstacle avoidance optical feedback Optical flow (image analysis) Optical imaging Optical sensors optimization |
| title | Reactive Obstacle Avoidance for Highly Maneuverable Vehicles Based on a Two-Stage Optical Flow Clustering |
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