Researchers’ algorithm designs soft robots that sense

By OEM Update Editorial May 2, 2021 1:38 pm

Deep-learning technique optimises the arrangement of sensors on a robot’s body to ensure efficient operation.

There are some tasks that traditional robots – the rigid and metallic kind — simply 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 have developed an algorithm to help engineers design soft robots that collect more useful information about their surroundings. The deep-learning algorithm suggests an optimised 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. “The system not only learns a given task, but also how to best design the robot to solve that task,” says Alexander Amini. “Sensor placement is a very difficult problem to solve.

So, having this solution is extremely exciting.” Creating soft robots that complete real-world tasks has been a long running challenge in robotics. Their rigid counterparts have a built-in advantage – a limited range of motion. Rigid robots’ finite array of joints and limbs usually makes for manageable calculations by the algorithms that control mapping and motion planning. Soft robots are not so tractable. Soft-bodied robots are flexible and pliant — they generally feel more like a bouncy ball than a bowling ball. “The main problem with soft robots is that they are infinitely dimensional,” says Spielberg.

Advertising

Your future advertising space? Our media data