skip to main content
10.1145/3284516.3284540acmotherconferencesArticle/Chapter ViewAbstractPublication PagesiccmaConference Proceedingsconference-collections
research-article

Occupancy Grid Fusion Prototyping Using Automotive Virtual Validation Environment

Authors Info & Claims
Published:12 October 2018Publication History

ABSTRACT

This paper walks through the occupancy grid fusion algorithm prototyping process. The implementation consists of core fusion algorithms using probability derived from inverse sensor models. Preliminary results are obtained using an automotive virtual validation tool and phenomenological sensor models of radars, lidars and selected functions of vision sensors. The purpose of the developed framework is to perform a relative performance assessment between certain grid computation and fusion methods. Assessment is carried out by comparing computed results with reference data. Virtual validation is used to enable quick and cost effective reference data generation in comparison to real world testing.

References

  1. J. Carvalho and R. Ventura. Comparative evaluation of occupancy grid mapping methods using sonar sensors. In J. M. Sanches, L. Micó, and J. S. Cardoso, editors, Pattern Recognition and Image Analysis, pages 889--896, Berlin, Heidelberg, 2013. Springer Berlin Heidelberg.Google ScholarGoogle ScholarCross RefCross Ref
  2. A. Chen and M. Sarazen. Simulations pave the road for self-driving technologies, 2017.Google ScholarGoogle Scholar
  3. T. Colleens, J. J. Colleens, and D. Ryan. Occupancy grid mapping: An empirical evaluation. In 2007 Mediterranean Conference on Control Automation, pages 1--6, June 2007.Google ScholarGoogle ScholarCross RefCross Ref
  4. A. Elfes and L. Matthies. Sensor integration for robot navigation: Combining sonar and stereo range data in a grid-based representataion. In 26th IEEE Conference on Decision and Control, volume 26, pages 1802--1807, Dec 1987.Google ScholarGoogle ScholarCross RefCross Ref
  5. C. Galvez del Postigo Fernandez. Grid-based multi-sensor fusion for on-road obstacle detection: Application to autonomous driving. Master's thesis, 2015.Google ScholarGoogle Scholar
  6. R. Grewe, M. Komar, A. Hohm, S. Lueke, and H. Winner. Evaluation method and results for the accuracy of an automotive occupancy grid. In 2012 IEEE International Conference on Vehicular Electronics and Safety (ICVES 2012), pages 19--24, July 2012.Google ScholarGoogle ScholarCross RefCross Ref
  7. R. Jungnickel, M. Kohler, and F. Korf. Efficient automotive grid maps using a sensor ray based refinement process. In 2016 IEEE Intelligent Vehicles Symposium (IV), pages 668--675, June 2016.Google ScholarGoogle ScholarCross RefCross Ref
  8. Mathworks. Documentation - robotics system toolbox - occupancy grids, 2018.Google ScholarGoogle Scholar
  9. H. Moravec. Sensor fusion in certainty grids for mobile robots. AI Mag., 9(2):61--74, July 1988. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. H. Moravec and A. Elfes. High resolution maps from wide angle sonar. In Proceedings. 1985 IEEE International Conference on Robotics and Automation, volume 2, pages 116--121, Mar 1985.Google ScholarGoogle ScholarCross RefCross Ref
  11. J. Schauer and A. Nüchter. The peopleremover - removing dynamic objects from 3-d point cloud data by traversing a voxel occupancy grid. IEEE Robotics and Automation Letters, 3(3):1679--1686, July 2018.Google ScholarGoogle ScholarCross RefCross Ref
  12. P. Skruch, R. Dlugosz, K. Kogut, P. Markiewicz, D. Sasin, and M. Rozewicz. The simulation strategy and its realization in the development process of active safety and advanced driver assistance systems. In SAE Technical Paper. SAE International, Apr 2015.Google ScholarGoogle ScholarCross RefCross Ref
  13. L. Stanislas and T. Peynot. Characterisation of the delphi electronically scanning radar for robotics applications. In Australasian Conference on Robotics and Automation (ACRA 2015), Canberra, A.C.T, December 2015.Google ScholarGoogle Scholar
  14. S. Thrun, W. Burgard, and D. Fox. Probabilistic Robotics (Intelligent Robotics and Autonomous Agents). The MIT Press, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Z. Wang, D. Yi, X. Duan, J. Yao, and D. Gu. Measurement Data Modeling and Parameter Estimation. Boca Raton: CRC Press, 2012.Google ScholarGoogle Scholar
  16. R. Zou. Free space detection based on occupancy gridmap. Master's thesis, 2012.Google ScholarGoogle Scholar

Index Terms

  1. Occupancy Grid Fusion Prototyping Using Automotive Virtual Validation Environment

                          Recommendations

                          Comments

                          Login options

                          Check if you have access through your login credentials or your institution to get full access on this article.

                          Sign in
                          • Published in

                            cover image ACM Other conferences
                            ICCMA 2018: Proceedings of the 6th International Conference on Control, Mechatronics and Automation
                            October 2018
                            198 pages
                            ISBN:9781450365635
                            DOI:10.1145/3284516

                            Copyright © 2018 ACM

                            Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

                            Publisher

                            Association for Computing Machinery

                            New York, NY, United States

                            Publication History

                            • Published: 12 October 2018

                            Permissions

                            Request permissions about this article.

                            Request Permissions

                            Check for updates

                            Qualifiers

                            • research-article
                            • Research
                            • Refereed limited

                          PDF Format

                          View or Download as a PDF file.

                          PDF

                          eReader

                          View online with eReader.

                          eReader