Motivation: A significant barrier to adoption of digital manufacturing technologies is possible vulnerability of cyber infrastructure to malicious attacks. Thus, cybersecurity frameworks and standards have been developed by organizations including NIST, ISA, IEC and ISO. However, these standards are numerous and are vastly spread over the cybersecurity landscape, which is difficult for SMM’s to leverage these standards and frameworks.

Approach: This project aims to develop an accessible OT cybersecurity web portal to guide SMM’s towards adopting OT cybersecurity best practices. This portal will act as a one-stop-shop for SMM’s to survey the cybersecurity standards landscape in addition to viewing best practices. 

Partnerships: This work is sponsored by MxD and is done in collaboration with Calumet Electronics and MK Morse.

Motivation: Mobile robots, including autonomous cars, rely on a host of perception sensors to locally map their environments to supplement GNSS technology. However, evaluation of these maps are inherently difficult due to the unstructured nature of outdoor environments. Hence, there is a lack of evaluation technologies for automated driving sensor technologies.

Approach: This research aims to develop test methods to evaluate the construction of HD maps for mobile robot perception technology. These methods are systematically designed to evaluate camera, lidar, radar, and sensor fusion technologies.

Partnerships: This research is sponsored by the Autonomous Vehicles Working Group at NIST.

Motivation: As manufacturing applications become more decentralized and high-mix low-volume, multiple sensor technologies will be leveraged in a facility. However, the resiliency of these sensor technologies in agile manufacturing environments is unexplored. Thus, manufacturers are hesitant to use multiple sensors in manufacturing applications due to the lack of knowledge regarding their robustness.

Approach: This research aims to develop a multi-modal sensor fusion model for robotic pick-and-place applications. Depth cameras and RGB cameras are being used for evaluation. Furthermore, this research studies the influence of both early sensor and late sensor fusion in agile manufacturing environments.