How humanoids learn to read the room

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As humanoids move into more complex roles, the safety, sensing and interaction demands will only grow. Ostrem believes the future lies in better AI at the edge — both in terms of improved accuracy in object classification, and optimized low-power edge processing.

ADI already has sensing and perception, connectivity and battery management figured out in the automotive sphere. The natural next step is leveraging those technologies into emerging applications like humanoids.

“In some ways, humanoid robots are where cars were many years ago,” says Ostrem. “The architecture isn’t fully set, and there is significant room for industry collaboration around standardizing interfaces to stimulate the ecosystem around humanoid robots.” Already in wide use throughout the automotive industry, ADI’s Gigabit Multimedia Serial Link (GMSL) technology transports video data in real time, in a single stream capable of carrying many gigabits per second. In humanoid robots, this enables redundancy and fast, local processing of visual data, which enables these systems to identify and understand what the visual data means about their surroundings using physical AI to process visual data locally in the robot, rather than sending it to the cloud.

Vision alone is not enough, however; if a robot is going to work collaboratively with humans, it needs intelligent hearing, too. “Being able to speak in natural language and having a conversational user interface is a very powerful way to communicate with a robot,” says Ostrem.