Creating a ROS 2 Open Source Distribution

Prof. Dr. Dirk Riehle (Univ. Erlangen / Bayave GmbH) will present on Wednesday, January 11 at 1:30pm PT, UC Santa Cruz, Engineering-2, Room 506 (hybrid event)

Photo credit: FAU / Harald Sippel

Abstract: The Robot Operating System (now ROS 2) is an open source middleware for operating robots. Similarly to Linux, Kubernetes, or OpenStack, ROS 2 has grown to be so complex that building ROS 2 from scratch has become impossible for most users. Hence, like in the other examples, users want to use a preconfigured well-integrated open source distribution of ROS 2. Open source distributions are being created in practice, but have not seen any research yet. In this talk, I will outline the challenges I see with building well-integrated, reproducible/verifiable, and certifiable open source distributions using ROS 2 as the example. I will speculate how beyond research, a commercial product could be created.

Audience: Researchers interested in open source, robotics, and startups

Speaker: Prof. Dr. Dirk Riehle, Univ. Erlangen / Bayave GmbH

Bio: Prof. Dr. Dirk Riehle, M.B.A., is the Professor of Open Source Software at the Friedrich-Alexander University of Erlangen-Nürnberg. Before joining academia, Riehle led the Open Source Research Group at SAP Labs, LLC, in Palo Alto, California (Silicon Valley). Riehle founded the Open Symposium, now the international conference on open collaboration. He was also the lead architect of the first UML virtual machine. He is interested in open source and inner source software engineering, agile software development methods, complexity science and human collaboration, and software system architecture, design, and implementation. Prof. Riehle holds a Ph.D. in computer science from ETH Zürich and an M.B.A. from Stanford Graduate School of Business. He welcomes email at dirk@riehle.org, blogs at https://dirkriehle.com, and tweets as @dirkriehle.

Carlos Maltzahn
Carlos Maltzahn
Adjunct Professor, Founder & Director of CROSS, OSPO

My research interests include programmable storage systems, big data storage & processing, scalable data management, distributed systems performance management, and practical reproducible research.