A Little Wiggle Helps Robots Learn the Ropes
A Little Wiggle Helps Robots Learn the Ropes
Researchers at Carnegie Mellon University have developed Wiggle and Go, a method that allows robots to estimate the physical properties of ropes and cables by wiggling them and observing the motion. This enables more reliable planning of movements without prior practice, with applications in manufacturing, construction, and search and rescue. The system was trained in simulation and tested on physical robots, demonstrating the challenges of sim-to-real transfer.
Source: Carnegie Mellon Robotics Institute — News · Read original article ↗
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uld have serious consequences, making it important to predict how the rope will move before acting. Making the system work on a physical robot was the team’s biggest challenge to overcome. The team trained its model entirely in computer simulation, where researchers can develop and test robotic behaviors without repeatedly using physical hardware. “Simulated objects do not always behave exactly like their real-world
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briefly wiggle a rope or cable, observe how it responds, and estimate its physical properties. With that information, the robot can plan its movements more reliably without practicing the task first. “Rigid objects effectively have six degrees of freedom,” said Jeffrey Ichnowski, an assistant professor in CMU’s Robotics Institute. “With ropes or cables, you effectively have infinite degrees of freedom. A rope or cab
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le can bend, twist and stretch along its entire length, making its shape and movement much harder to predict.” Their physical properties add another layer of difficulty. Two ropes or cables can respond differently to the same movement, depending on their length, weight and stiffness. A robot cannot determine those properties simply by looking at the rope or cable, yet it needs to understand how the object will behave
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to move it. That’s where the wiggle comes in. With Wiggle and Go, the robot gives the rope or cable a quick wiggle while an overhead camera records how the resulting wave travels through it. Computer vision algorithms track the movement, and a model uses that information to estimate physical properties that help explain its behavior. The robot then uses those estimates to plan how it will move the rope toward a goal
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Source：Carnegie Mellon Robotics Institute — News · ri.cmu.edu