Robotic Grasping Via RF-Visual Sensing And Learning
Described is the design, implementation, and evaluation of a robotic system configured to search for and retrieve RFID-tagged items in line-of-sight, non-line-of-sight, and fully-occluded settings. The robotic system comprises a robotic arm having a camera and antenna strapped around a portion there...
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Zusammenfassung: | Described is the design, implementation, and evaluation of a robotic system configured to search for and retrieve RFID-tagged items in line-of-sight, non-line-of-sight, and fully-occluded settings. The robotic system comprises a robotic arm having a camera and antenna strapped around a portion thereof (e.g. a gripper) and a controller configured to receive information from the camera and (radio frequency) RF information via the antenna and configured to use the information provided thereto to implement a method that geometrically fuses at least RF and visual information. This technique reduces uncertainty about the location of a target object even when the object is fully occluded. Also described is a reinforcement-learning network that uses fused RF-visual information to efficiently localize, maneuver toward, and grasp a target object. The systems and techniques described herein find use in many applications including robotic retrieval tasks in complex environments such as warehouses, manufacturing plants, and smart homes. |
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