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MODISSA: a multipurpose platform for the prototypical realization of vehicle-related applications using optical sensors

arXiv 2105.13580 ↗First posted 28 May 2021cs.CV cs.SY eess.IVcited by 0

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Abstract (arXiv)

We present the current state of development of the sensor-equipped car MODISSA, with which Fraunhofer IOSB realizes a configurable experimental platform for hardware evaluation and software development in the context of mobile mapping and vehicle-related safety and protection. MODISSA is based on a van that has successively been equipped with a variety of optical sensors over the past few years, and contains hardware for complete raw data acquisition, georeferencing, real-time data analysis, and immediate visualization on in-car displays. We demonstrate the capabilities of MODISSA by giving a deeper insight into experiments with its specific configuration in the scope of three different applications. Other research groups can benefit from these experiences when setting up their own mobile sensor system, especially regarding the selection of hardware and software, the knowledge of possible sources of error, and the handling of the acquired sensor data.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 13 of its 48 references that are in the map. First posted on arXiv 28 May 2021.

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References · 13

  1. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  2. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  3. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  4. 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,436
  5. 2019Argoverse: 3D Tracking and Forecasting with Rich Mapscited by 728
  6. 2020One Thousand and One Hours: Self-driving Motion Prediction Datasetcited by 239
  7. 2020A2D2: Audi Autonomous Driving Datasetcited by 189
  8. 2018The ApolloScape Open Dataset for Autonomous Driving and its Applicationcited by 188
  9. 2017Semantic3D.net: A new Large-scale Point Cloud Classification Benchmarkcited by 158
  10. 2017Paris-Lille-3D: a large and high-quality ground truth urban point cloud dataset for automatic segmentation and classificationcited by 65
  11. 2015Semantic Instance Annotation of Street Scenes by 3D to 2D Label Transfercited by 39
  12. 2019DublinCity: Annotated LiDAR Point Cloud and its Applicationscited by 31
1 more
  1. 2019AMZ Driverless: The Full Autonomous Racing Systemcited by 28

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