In the field, robots often need to operate in unknown and unstructured environments, where accurate sensing and state estimation (SE) become a major challenge. Cameras have been used with great success in mapping and planning in such environments [1] as well as complex but quasi-static tasks, such as grasping [2], but are rarely integrated into the control loop for unstable … [Read more...] about Learning Fast and Precise Pixel-to-Torque Control: A Platform for Reproducible Research of Learning on Hardware
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