Pushy robots learn the fundamentals of object manipulation

Researchers have compiled a dataset that captures the detailed behavior of a robotic system physically pushing hundreds of different objects. Using the dataset — the largest and most diverse of its kind — researchers can train robots to 'learn' pushing dynamics that are fundamental to many complex object-manipulation tasks, including reorienting and inspecting objects, and uncluttering scenes.

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Giving robots a faster grasp

Engineers have found a way to significantly speed up the planning process required for a robot to adjust its grasp on an object by pushing that object against a stationary surface. Whereas traditional algorithms would require tens of minutes for planning out a sequence of motions, the new team's approach shaves this planning process down to less than a second.

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New soft actuators could make soft robots less bulky

Engineers have developed a way to build soft robots that are compact, portable and multifunctional. The advance was made possible by creating soft, tubular actuators whose movements are electrically controlled, making them easy to integrate with small electronic components. As a proof of concept, engineers used the new actuators to build an untethered, battery-powered, walking soft robot and a soft gripper.

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Biologically-inspired skin improves robots' sensory abilities

Sensitive synthetic skin enables robots to sense their own bodies and surroundings – a crucial capability if they are to be in close contact with people. Inspired by human skin, a team has developed a system combining artificial skin with control algorithms and used it to create the first autonomous humanoid robot with full-body artificial skin.

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