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Thursday, December 17, 2020

Machine learning for autonomous AI systems and robotics | Technology - Open Access Government

Chief Scientist at Dynamic Object Language Labs Inc, Dr Paul Robertson explains how autonomous AI systems are key to achieving synergy between humans and robotics that can work together as a team.

Sheep
Photo: Open Access Government

Artificial Intelligence (A.I.) and Autonomous Robotics are advancing rapidly and becoming robust and reliable in a number of fields, but there remains much to be done before intelligent robots can work together with us as assistants. Today, most robots are either tele-operated or perform precisely defined missions. In many cases the human overhead required to use a robot exceeds the usefulness of having it.

There is a clear need for human-robot teams in which humans and robots work side-by-side. Homogeneous teams, involve team members doing the same work. In such a case, the value comes from parallelism, such as picking grapes from vines. Heterogeneous teams consists of specialised individuals, or specialised subgroups. Our research concerns this latter kind of team. A.I. systems and autonomous robots have vastly different strengths and weaknesses from human team members. The value of the team comes from mobilising their diverse capabilities. A robot that can fly offers a unique and valuable skill. The benefits that can come from heterogeneous mixed human robot teams are immense...

The herding dogs soon learn the map of the fields and the whereabouts of the gates. Knowing the map and knowing that the other dogs share the same model permits the dogs to depend less on sound cues from the farmer. A model of the sheep allows the dogs to attend to the occasional sheep that stray from the others.

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Source: Open Access Government