FINDING
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What are the opportunities for Human-Robot Collaboration in the Seafood Processing Industry? This NSF-funded project sought to innovate and detail the full capability of networked technologies, located at every part of the supply chain. Focusing on elements such as the fishing vessel, the loading dock, the factory, the restaurant, and the home, the team detailed everything from conceptual renders, to experiment protocol, to biotically adaptive robotic prototypes.
An increased ability of sensing and reasoning technologies, we hope that the consumers will connect more directly to the factory, to the boat, and to the fish. We hope by doing so there will be a fundamental shift towards responsible environmental practices and healthier workplace environments. Other potentials exist to minimize supply chain waste by-products, including embodied carbon and packaging discards. Increasing profit is not the only utility of these heaps of data: the same data can hold bad actors responsible for malpractice, connect the consumer more directly to the processes that provide them food, and increase the quality of life for those doing the actual seafood processing.
Providing more than a theory, the research group designed Human-Robot Interfaces and experiments to train our algorithms. The main interface components relied on gesture recognition and projection for the main, while there was an underlying system that adjusted the robot’s behavior to various biometric readings collected throughout the exercise. Ergonomic hand-offs and positioning were informed by exercise routines to minimize fatigue and unnecessary body strain. If the system began to detect fatigue, it would adjust its own working habits for a more harmonious collaboration. This system can be interrupted manually to still give the worker their own autonomy.
The process making a user interface flowchart that informed programing gesture controls and a responsive projection screen proved to be a valuable exercise in building a collective understanding in an interdisciplinary team. This required development of the composition and design of the interface itself at the same time as a physical adaptation to the UR-10 robot to be able to physically support such an interface.
