A better way to control shape-shifting soft robots
A new machine-learning technique can train and control a reconfigurable soft robot that can dynamically change its shape to complete a task. The researchers also built a simulator that can evaluate control algorithms for shape-shifting soft robots.
Scientists have designed swarms of microscopic robots that communicate and coordinate using sound waves, much like bees or birds. These self-organizing micromachines can adapt to their surroundings, reform if damaged, and potentially undertake complex tasks such as cleaning polluted areas, delivering targeted medical treatments, or exploring hazardous environments.
Robotics researchers, engineers and materials scientists showed it is possible to make programmable, nonelectronic circuits that control the actions of soft robots by processing information encoded in bursts of compressed air.
Tool use has long been a hallmark of human intelligence, as well as a practical problem to solve for a vast array of robotic applications. But machines are still wonky at exerting just the right amount of force to control tools that aren't rigidly attached to their hands.