Raytheon Intelligence and Space to improve human machine teaming by Staff Writers Cambridge MA (SPX) Aug 25, 2022
A Raytheon BBN-led team received an 18-month DARPA contract to investigate new methods and design practices to support effective human-machine teaming as part of the Enhancing Design for Graceful Extensibility program. BBN will work to develop human machine interfaces that enable non-expert operators to understand critical system processes; system performance thresholds based on environmental, physical, and software constraints; and the operating context and mission goals. "This is an exciting opportunity to do both focused human machine interface design work alongside applied research to operationalize the Theory of Graceful Extensibility--the ability of a system to adapt when surprise events push it to its boundaries" explained Jon Sussman-Fort, Raytheon BBN principal investigator. "Our goal is to design a proactive, predictive multi-agent interface system that will reduce human operator workload, increase the number of robots under simultaneous control, and improve system resilience in off-nominal conditions." Today's state-of-the-art modeling plans human interface design after the system is built, making for a more reactive and info-centric environment. By applying TGE at the forefront the team will create a more flexible and adaptive model that can respond better to surprise, in collaboration with human operators. The team's approach is expected to improve: + system performance by using adaptive capacity. + responsiveness by alerting and orienting operators to potential problems. + performance by reducing the risk of system failure. The Raytheon BBN led team includes Mile Two and UMass-Lowell. The work will be conducted at BBN facilities in Middletown, Rhode Island, Cambridge, Massachusetts as well as at Mile Two facilities in Dayton, Ohio.
Researchers create the first artificial vision system for both land and water Boston MA (SPX) Aug 05, 2022 Giving our hardware sight has empowered a host of applications in self-driving cars, object detection, and crop monitoring. But unlike animals, synthetic vision systems can't simply evolve under natural habitats. Dynamic visual systems that can navigate both land and water, therefore, have yet to power our machines - leading researchers from MIT, the Gwangju Institute of Science and Technology (GIST), and Seoul National University in Korea to develop a novel artificial vision system that closely replica ... read more
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