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Multi sensors data fusion and Object detection algorithms for in-disaster scene situation awareness
Multi sensors data fusion and Object detection algorithms for in-disaster scene situation awareness
This Deliverable called “Multi sensors data fusion and Object detection algorithms for in-disaster scene situation awareness” is the result of the Task 3.4 of Search&Rescue Project where the design and development of Obstacle Detection System (ODS) is described. In particular the following topic are introduced: the scope of a Robotic solution with an ODS onboard, the importance of the ODS within the S&R Project and the specific advantages to have a multi sensor data fusion algorithm. Then the System Overview is presented treating the related references, the Machine learning, AI, the Processing Unit, the Implementation notes and finally their integration in the selected S&R rescue Robot. In the following chapters the main topics are described: the architecture of Obstacle Detection System with smart sensors, special synchronisation and depth estimation; the implementation of Obstacle Detection Algorithms and finally the Fusion and Tracking operations. At the end of the deliverable there are references to the Robot System Integration (with recall to the D5.4) and the related Verification and Validation of the System.
Multi sensors, Situation Awareness
Multi sensors, Situation Awareness
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[1] Hartley, R., Zisserman, A. (2003). Multiple View Geometry in Computer Vision. New York, NY, USA: Cambridge University Press. ISBN: 0521540518
[2] Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016). You Only Look Once: Unified, Real-Time Object Detection. arXiv.
[3] Redmon, J., & Farhadi, A. (2016). YOLO9000: Better, Faster, Stronger. arXiv.
[4] J. Redmon and A. Farhadi (2018). Yolov3: An incremental improvement. arXiv.
[5] Bochkovskiy, A., Wang, C.-Y., & Liao, H.-Y. M. (2020). YOLOv4: Optimal Speed and Accuracy of Object Detection. arXiv.
[6] Cybenko, G.V. (1989). Approximation by superpositions of a sigmoidal function. Mathematics of Control, Signals and Systems, 2, 303-314. [OpenAIRE]
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[10] J. K. Uhlmann (1992). Algorithms for multiple target tracking. American Scientist, 80(2):128-141
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citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!This Deliverable called “Multi sensors data fusion and Object detection algorithms for in-disaster scene situation awareness” is the result of the Task 3.4 of Search&Rescue Project where the design and development of Obstacle Detection System (ODS) is described. In particular the following topic are introduced: the scope of a Robotic solution with an ODS onboard, the importance of the ODS within the S&R Project and the specific advantages to have a multi sensor data fusion algorithm. Then the System Overview is presented treating the related references, the Machine learning, AI, the Processing Unit, the Implementation notes and finally their integration in the selected S&R rescue Robot. In the following chapters the main topics are described: the architecture of Obstacle Detection System with smart sensors, special synchronisation and depth estimation; the implementation of Obstacle Detection Algorithms and finally the Fusion and Tracking operations. At the end of the deliverable there are references to the Robot System Integration (with recall to the D5.4) and the related Verification and Validation of the System.