US 12,403,590 B2
Robotic grasping via RF-visual sensing and learning
Tara Boroushaki, Cambridge, MA (US); Isaac S. Perper, Cambridge, MA (US); and Fadel Adib, Cambridge, MA (US)
Assigned to Massachusetts Institute of Technology, Cambridge, MA (US)
Filed by Massachusetts Institute of Technology, Cambridge, MA (US)
Filed on Aug. 15, 2022, as Appl. No. 17/819,685.
Claims priority of provisional application 63/232,698, filed on Aug. 13, 2021.
Prior Publication US 2023/0056652 A1, Feb. 23, 2023
Int. Cl. B25J 9/16 (2006.01); B25J 13/00 (2006.01); B25J 19/02 (2006.01); H01Q 1/22 (2006.01)
CPC B25J 9/1612 (2013.01) [B25J 13/006 (2013.01); B25J 19/023 (2013.01); H01Q 1/2208 (2013.01)] 16 Claims
OG exemplary drawing
 
1. A robotic system comprising:
A robotic member having an end effector;
An imaging device coupled to the robotic member proximate to or on the end effector, the imaging device configured to provide visual information;
A radio frequency (RF) system configured to collect and provide information, the RF system including an antenna coupled to the robotic member proximate to or on the end effector; and
A controller in communication with the robotic member, the imaging device and the RF system, the controller configured to geometrically fuse RF distance information provided thereto by the RF system and visual information provided thereto by the imaging device to reduce uncertainty about a location of a target object even when the object is fully occluded,
Wherein the controller is further configured to:
Iteratively geometrically fuse the RF distance information and the visual information to reduce uncertainty about the target object location;
Determine whether the uncertainty is smaller than a threshold value; and
In response to the uncertainty being smaller than the threshold value, cause the end effector to manipulate the target object.