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1.发明申请公开(公告)号：US20220126453A1
公开(公告)日：2022-04-28
申请号：US17077937
申请日：2020-10-22
摘要： A controller is provided for interactive classification and recognition of an object in a scene using tactile feedback. The controller includes an interface configured to transmit and receive the control, sensor signals from a robot arm, gripper signals from a gripper attached to the robot arm, tactile signals from sensors attached to the gripper and at least one vision sensor, a memory module to store robot control programs, and a classifier and recognition model, and a processor to generate control signals based on the control program and a grasp pose on the object, configured to control the robot arm to grasp the object with the gripper. Further, the processor is configured to compute a tactile feature representation from the tactile sensor signals and to repeat gripping the object and computing a tactile feature representation with the set of grasp poses, after which the processor, processes the ensemble of tactile features to learn a model which is utilized to classify or recognize the object as known or unknown.
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公开(公告)号：US20220305646A1
公开(公告)日：2022-09-29
申请号：US17214810
申请日：2021-03-27
摘要： A system for parameter tuning for robotic manipulators is provided. The system includes an interface configured to receive a task specification, a plurality of physical parameters, and a plurality of control parameters, wherein the interface is configured to communicate with a real-world robot via a robot controller. The system further includes a memory to store computer-executable programs including a robot simulation module, a robot controller, and an auto-tuning module a processor, in connection with the memory. In this case, the processor is configured to acquire, in communication with the real-world robot, state values of the real-world robot, state values of the robot simulation module, simultaneously update, by use of a predetermined optimization algorithm with the auto-tuning module, an estimate of one or more of the physical, and said control parameters, and store the updated parameters.
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3.发明授权公开(公告)号：US11794350B2
公开(公告)日：2023-10-24
申请号：US17077937
申请日：2020-10-22
CPC分类号： B25J9/1697 , B25J9/163 , B25J9/1612 , B25J9/1694 , B25J13/08 , B25J13/084 , B25J15/0033 , G01L1/02 , G06N20/00 , G06T7/70 , G06V20/10 , G05B2219/39543 , G05B2219/40553 , G05B2219/40575 , G05B2219/40625 , G06T2207/20081
摘要： A controller is provided for interactive classification and recognition of an object in a scene using tactile feedback. The controller includes an interface configured to transmit and receive the control, sensor signals from a robot arm, gripper signals from a gripper attached to the robot arm, tactile signals from sensors attached to the gripper and at least one vision sensor, a memory module to store robot control programs, and a classifier and recognition model, and a processor to generate control signals based on the control program and a grasp pose on the object, configured to control the robot arm to grasp the object with the gripper. Further, the processor is configured to compute a tactile feature representation from the tactile sensor signals and to repeat gripping the object and computing a tactile feature representation with the set of grasp poses, after which the processor, processes the ensemble of tactile features to learn a model which is utilized to classify or recognize the object as known or unknown.
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公开(公告)号：US20240288870A1
公开(公告)日：2024-08-29
申请号：US18475442
申请日：2023-09-27
发明人： Chiori Hori , Jonathan Le Roux , Devesh Jha , Siddarth Jain , Radu Ioan Corcodel , Diego Romeres , Puyuang Peng , Xinyu Liu , David Harwath
CPC分类号： G05D1/0246 , G06V10/82 , G06V20/41 , G06V20/46 , G06V20/49 , G10L15/02 , G10L15/16 , G10L15/1815
摘要： A method, a system and a computer program product are provided for applying a neural network including an action sequence decoder for generating an action sequence for a robot to perform a task. The neural network is applied to generate the action sequence based on recordings demonstrating humans performing tasks. In an example, the method comprises collecting a recording and a sequence of captions describing scenes in the recording; extracting feature data from the recording; encoding the extracted feature data to produce a sequence of encoded features; and applying the action sequence decoder to produce a sequence of actions for the robot based on the sequence of encoded features having a semantic meaning corresponding to a semantic meaning of the sequence of captions. The feature data includes features of a video signal, an audio signal, and/or text transcription capturing a performance of the task.
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公开(公告)号：US11975451B2
公开(公告)日：2024-05-07
申请号：US17214810
申请日：2021-03-27
CPC分类号： B25J9/163 , B25J9/1671 , B25J13/088
摘要： A system for parameter tuning for robotic manipulators is provided. The system includes an interface configured to receive a task specification, a plurality of physical parameters, and a plurality of control parameters, wherein the interface is configured to communicate with a real-world robot via a robot controller. The system further includes a memory to store computer-executable programs including a robot simulation module, a robot controller, and an auto-tuning module a processor, in connection with the memory. In this case, the processor is configured to acquire, in communication with the real-world robot, state values of the real-world robot, state values of the robot simulation module, simultaneously update, by use of a predetermined optimization algorithm with the auto-tuning module, an estimate of one or more of the physical, and said control parameters, and store the updated parameters.
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公开(公告)号：US20230330853A1
公开(公告)日：2023-10-19
申请号：US17659246
申请日：2022-04-14
发明人： Chungwei Lin , Yebin Wang , Rien Quirynen , Devesh Jha , Bingnan Wang , William Vetterling , Siddarth Jain , Scott Bortoff
CPC分类号： B25J9/1664 , B25J9/1653 , B25J5/007 , B62D15/0285
摘要： The present disclosure provides a system and a method for controlling a motion of a robot from a starting point to a target point within a bounded space with a floorplan including one or multiple obstacles. The method includes solving for an electric potential in a bounded virtual space formed by scaling the floorplan of the bounded space with the one or multiple obstacles and applying charge to at least one bound of the bounded virtual space while treating the scaled obstacles as metallic surfaces with a constant potential value, wherein the electric potential provides multiple equipotential curves within the bounded virtual space. The method further includes selecting an equipotential curve with a potential value different from a potential value of an obstacle equipotential curve, determining a motion path based on the selected equipotential curve, and controlling the motion of the robot based on the determined motion path.
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