Combined with new generations of low-power motors and sensors, the new ASIC – which operates on milliwatts of power – could help intelligent swarm robots operate for hours instead of minutes.
The chips use a hybrid digital-analogue time-domain processor in which the pulse-width of signals encodes information. The neural network IC accommodates both model-based programming and collaborative reinforcement learning, potentially providing the small robots larger capabilities for reconnaissance, search-and-rescue and other missions.
Researchers demonstrated robotic cars driven by these ASICs at the 2019 IEEE International Solid-State Circuits Conference (ISSCC).
“We are trying to bring intelligence to these very small robots so they can learn about their environment and move around autonomously, without infrastructure,” said Arijit Raychowdhury, associate professor in Georgia Tech’s School of Electrical and Computer Engineering. “To accomplish that, we want to bring low-power circuit concepts to these very small devices so they can make decisions on their own.”
The cars use inertial and ultrasound sensors to determine their location and detect objects around them. Information from the sensors goes to the hybrid ASIC, which serves as the “brain” of the vehicles. Instructions then go to a Raspberry Pi controller, which sends instructions to the electric motors.
The team is working with collaborators on motors that use micro-electromechanical (MEMS) technology able to operate with much less power than conventional motors.
“We want to build a system in which sensing power, communications and computer power, and actuation are at about the same level, on the order of hundreds of milliwatts,” said Raychowdhury, “providing runtimes of several hours on a couple of AA batteries.”
