Detection of dynamic obstacles out of the line of sight for autonomous vehicles to increase safety based on shadows
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | eng |
| Published: |
Massachusetts Institute of Technology
2019
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/1721.1/121657 |
| _version_ | 1826209892051976192 |
|---|---|
| author | Naser, Felix Maximilian. |
| author2 | Daniela Rus. |
| author_facet | Daniela Rus. Naser, Felix Maximilian. |
| author_sort | Naser, Felix Maximilian. |
| collection | MIT |
| description | This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. |
| first_indexed | 2024-09-23T14:34:15Z |
| format | Thesis |
| id | mit-1721.1/121657 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T14:34:15Z |
| publishDate | 2019 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1216572019-09-14T03:06:24Z Detection of dynamic obstacles out of the line of sight for autonomous vehicles to increase safety based on shadows Naser, Felix Maximilian. Daniela Rus. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Electrical Engineering and Computer Science. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019 Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (pages 85-89). Moving obstacles occluded by corners are a potential source for collisions in mobile robotics applications such as autonomous vehicles. In this work, we address the problem of anticipating such potential collisions by proposing a vision-based detection algorithm for obstacles which are outside of a vehicle's direct line of sight. Our method detects shadows of obstacles hidden around corners and automatically classifies these unseen obstacles as "dynamic" or "static". We evaluate our proposed detection algorithm on real-world corners and a large variety of simulated environments to assess generalizability in different challenging surface and lighting conditions. For the image registration step we compare a visual odometry method (i.e. DSO) with a fiducial marker system (i.e. AprilTags). The mean classification accuracy on simulated data is around 80% and on real-world corners approximately for both image registration methods 70%. Additionally, we integrate our detection system on a full-scale autonomous wheelchair and demonstrate its feasibility as an additional safety mechanism through real-world experiments. We release our real-time-capable implementation of the proposed ShadowCam algorithm and the dataset containing simulated and real-world data under an open-source license. by Felix Maximilian Naser. S.M. S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science 2019-07-15T20:31:27Z 2019-07-15T20:31:27Z 2019 2019 Thesis https://hdl.handle.net/1721.1/121657 1102050932 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 89 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Naser, Felix Maximilian. Detection of dynamic obstacles out of the line of sight for autonomous vehicles to increase safety based on shadows |
| title | Detection of dynamic obstacles out of the line of sight for autonomous vehicles to increase safety based on shadows |
| title_full | Detection of dynamic obstacles out of the line of sight for autonomous vehicles to increase safety based on shadows |
| title_fullStr | Detection of dynamic obstacles out of the line of sight for autonomous vehicles to increase safety based on shadows |
| title_full_unstemmed | Detection of dynamic obstacles out of the line of sight for autonomous vehicles to increase safety based on shadows |
| title_short | Detection of dynamic obstacles out of the line of sight for autonomous vehicles to increase safety based on shadows |
| title_sort | detection of dynamic obstacles out of the line of sight for autonomous vehicles to increase safety based on shadows |
| topic | Electrical Engineering and Computer Science. |
| url | https://hdl.handle.net/1721.1/121657 |
| work_keys_str_mv | AT naserfelixmaximilian detectionofdynamicobstaclesoutofthelineofsightforautonomousvehiclestoincreasesafetybasedonshadows |