Real-Life Experiences in Using Open Source for Autonomy Applications
The open-source paradigm is well known for its unique potential to crowd-source innovation with spectacular examples of success, such as Linux. The knowledge base of methods to build more successful open-source communities has been growing with concepts such as independent governance, community building, and funding mechanisms. In mobility, an open-source autonomy stack called Autoware was the basis of a significant public transportation research project called ISEAUTO, and a companion project, PolyVerif, focused on building validation and verification technologies. This paper outlines the real-life experiences of two teams using the Autoware framework, providing lessons and recommendations for improving open-source development.
Authors
- Raivo Sell (ORCID: https://orcid.org/0000-0003-1409-0206)
- Rahul Razdan (ORCID: https://orcid.org/0000-0003-2092-3227)
- Ehsan Malayjerdi (ORCID: https://orcid.org/0000-0002-6526-6059)
- Mustafa İlhan Akbaş (ORCID: https://orcid.org/0000-0002-5450-3522)
- Mohsen Malayjerdi (ORCID: https://orcid.org/0000-0001-6976-2095)
Institutions
- Tallinn University of Technology (EE)
- Volvo (Sweden) (SE)
- Florida Polytechnic University (US)
- Embry–Riddle Aeronautical University (US)
Publication Details
- Published
- 2024-11-04
- DOI
- https://doi.org/10.3390/engproc2024079019
- Citations
- 2
- Primary Topic
- Reinforcement Learning in Robotics
- Type
- article
- Field-Weighted Citation Impact
- 0.69