Google’s hive-mind robot arms learn to negotiate a cluttered world

Getting robots to pick up objects with the same dexterity and success-rate as a five-year-old child is no minor challenge in the development of flexible automation systems. Amazon, in its determination to end controversies about working conditions (by emptying its warehouses of all humans), is already conducting extensive research into the problem of getting auto-picker robots to identify target objects in a cluttered environment. Predictably the best-funded tech research entity on the planet is no laggard in this area. A new paper [PDF] led by Google research scientist Sergey Levine details his team’s attempts to leverage a convolutional neural network in order to teach robots how to grasp objects in unpredictable and unordered environments. The paper, entitled Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collection,…


Link to Full Article: Google’s hive-mind robot arms learn to negotiate a cluttered world

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