Visibility study for Tractor with Rear Implement

This paper details a process involving digital content creation tools to conduct visibility studies for machinery that utilize vision-based perception system. In this paper we go through the process of preparing over 50 unique tillage implements with Light geometry attached to assess areas of potential sensor occlusion. We optimized the CAD Geometry of the model by removing Duplicate parts, Wiring, Floating geometry. Also, optimization of heavier parts was required and ensuring of high-altitude parts (i.e. SMV, Starfire, Lights, brackets) was important to ensure proper visibility studies. Making sure that the setup of the implement matched that of its corresponding vehicle was also Pertinent. The developed high-fidelity models that are used to Conduct perception occlusion analysis, develop simulations, quickly verify component geometries. Occlusion analyses facilitate cross-team discussions of the perception system coverage and expedite product development. Moreover, the generated high-fidelity small-sized digital assets can be used to generate synthetic scenarios in simulation and thus facilitate software qualification. This ability to execute simulations leveraging high quality and controlled inputs, can help reduce the burden of in field-testing this limiting the exposure to uncontrolled variables and difficult to reproduce scenarios. The ability to quickly verify component geometries and simulate various scenarios and machine configurations allows for a more agile development process. Teams can iterate faster, respond to feedback more effectively, and bring innovations to market more rapidly. The insights gained from Camera visibility studies can be integrated with emerging technologies such as artificial intelligence and machine learning. This integration can lead to the development of smarter perception systems that continuously learn and adapt, enhancing overall safety and performance.