MIT researchers have developed a deep learning neural network to aid the design of soft-bodied robots, such as these iterations of a robotic elephant. (Image: Courtesy of the researchers)

There are some tasks that traditional rigid robots aren’t cut out for. Soft-bodied robots, on the other hand, may be able to interact with people more safely or slip into tight spaces with ease. But for robots to reliably complete their programmed duties, they need to know the whereabouts of all their body parts. That’s a tall task for a soft robot that can deform in a virtually infinite number of ways.

MIT researchers developed an algorithm to help engineers design soft robots that collect more useful information about their surroundings. The algorithm suggests an optimized placement of sensors within the robot’s body, allowing it to better interact with its environment and complete assigned tasks. The advance is a step toward the automation of robot design.

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