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In recent times, a number of reference implementations of Simultaneous Localization and Mapping (SLAM) and navigation techniques have been made publicly available via the ROS Community. Several implementations have transitioned to commercial products (vacuum robots, drones, warehouse robots, etc.). However, in such cases, they are specialized and optimized for their specific domains of deployment. In particular, their success criteria have been based primarily on mission completion and safety of humans around them. In this light, deployment in any new operational design domain (ODD) requires at least a careful verification of performance and often re-optimization. We seek the technological gaps that need to be addressed to ensure the mobile robots are fit for automotive manufacturing environments. Automotive final assembly environments pose significant additional challenges for mobile robot deployment.

This paper presents an approach for performing software in the loop testing of autonomous vehicle software developed in the Autoware framework. Autoware is an open source software for autonomous driving that includes modules such as localization, detection, prediction, planning and control [8]. Multitudes of autonomous driving frameworks exist today, each having its own pros and cons. Often, MATLAB-Simulink is used for rapid prototyping, system modeling and testing, specifically for the lower-level vehicle dynamics and powertrain control features. For the autonomous software, the Robotic Operating System (ROS) is more commonly used for integrating distributed software components so that they can easily share information through a publish and subscribe paradigm. Thorough testing and evaluation of such complex, distributed software, implemented on a physical vehicle poses significant challenges in terms of safety, time, and cost, especially when considering rare edge cases.