Completed at the Experience Design Lab
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.
Preceding all of the work on this topic, we spent months compiling everything that we could about the fishing industry. Species trends to embodied caron estimates, hot fishing spots and fishing spots at risk of total depletion. How workers have typically been treated in the industry, as well as the evolution of tools throughout time. We sought to break down the spatial typologies of where seafood processing physically takes place, before delving in what data is extracted already, and what do future trends then indicate for all of these different aspects of the industry with an increasingly collaborative robotic workplace.