METHOD AND SYSTEM FOR DEXTEROUS MANIPULATION BY A ROBOT

    公开(公告)号:US20250065492A1

    公开(公告)日:2025-02-27

    申请号:US18414069

    申请日:2024-01-16

    Abstract: A system for dexterous robot manipulation includes a first robot configured to perform real simulations. The system also includes at least one computer configured to perform a set of virtual simulations including a robot model, develop a first policy for robot maneuvering based on the set of virtual simulations, and record a trajectory of the robot model during the set of virtual simulations. The at least one computer is also configured to perform a set of real simulations including the first robot, where the first robot mimics the recorded trajectory of the robot model, and develop a second policy for robot maneuvering based on the set of real simulations. The at least once computer is also configured to deploy the second policy to at least one of the first robot and a second robot to perform dexterous manipulation.

    METHOD AND SYSTEM FOR DEXTEROUS MANIPULATION BY A ROBOT

    公开(公告)号:US20250065493A1

    公开(公告)日:2025-02-27

    申请号:US18414084

    申请日:2024-01-16

    Abstract: A system for dexterous robot manipulation includes a first robot configured to perform real simulations with a real object, and at least one computer configured to perform a set of virtual simulations including a robot model and a virtual object corresponding to the first robot and the real object, and develop a trajectory of the robot model based on virtual simulation information of the robot model and the virtual object generated in the set of virtual simulations. The at least one computer is also configured to perform a set of real simulations including the first robot and the real object, wherein the first robot mimics the trajectory of the robot model, and develop a policy for robot maneuvering based on the set of real simulations, and deploy the policy to at least one of the first robot and a second robot to perform dexterous manipulation.

    SYSTEM AND METHOD FOR PROVIDING IN HAND ROBOTICS DEXTEROUS MANIPULATION OF OBJECTS

    公开(公告)号:US20240091938A1

    公开(公告)日:2024-03-21

    申请号:US18090967

    申请日:2022-12-29

    CPC classification number: B25J9/1664 B25J9/1697 B25J15/10

    Abstract: A system and method for providing in hand robotics dexterous manipulation of an object that include determining a geometry of an object, a position of the object, and a placement of at least one robotic finger of a robot upon the object. The system and method also include computing a direction of rolling or rotation of the object by the at least one robotic finger. The system and method additionally include updating a position of the object that is manipulated by the robot. The system and method further include updating contact points of the at least one robotic finger with respect to contacting the object in a manner that ensures that a viable grasp is enforced to have force closure to retain the object.

    OBJECT MANIPULATION
    4.
    发明申请

    公开(公告)号:US20230080768A1

    公开(公告)日:2023-03-16

    申请号:US17539989

    申请日:2021-12-01

    Abstract: A robot for object manipulation may include sensors, a robot appendage, actuators configured to drive joints of the robot appendage, a planner, and a controller. Object path planning may include determining poses. Object trajectory optimization may include assigning a set of timestamps to the poses, optimizing a cost function based on an inverse kinematic (IK) error, a difference between an estimated required wrench and an actual wrench, and a grasp efficiency, and generating a reference object trajectory based on the optimized cost function. Grasp sequence planning may be model-based or deep reinforcement learning (DRL) policy based. The controller may implement the reference object trajectory and the grasp sequence via the robot appendage and actuators.

    ROBOT-MEDIATED PHYSICAL HUMAN-HUMAN INTERACTION

    公开(公告)号:US20240424663A1

    公开(公告)日:2024-12-26

    申请号:US18341318

    申请日:2023-06-26

    Abstract: Robot-mediated physical human-human interaction may be implemented by receiving an interaction wrench signal indicative of a wrench force associated with a first robot portion, receiving an end-effector pose signal indicative of a pose associated with a second robot portion, generating a constraint signal indicative of a constraint associated with the first robot portion based on the end-effector pose signal associated with the second robot portion, and implementing the constraint associated with the first robot portion as feedback on the second robot portion. The robot-mediated physical human-human interaction may enable creation of robot-mediated physical interaction between multiple humans in a general setting while considering constraints with different priorities for each robot portion.

    GRASP SELECTION
    6.
    发明公开
    GRASP SELECTION 审中-公开

    公开(公告)号:US20240083021A1

    公开(公告)日:2024-03-14

    申请号:US18080623

    申请日:2022-12-13

    CPC classification number: B25J9/1612 G05B2219/39001 G05B2219/40465

    Abstract: Systems and techniques for grasp selection may include receiving one or more candidate object trajectories and a current grasp of a robotic hand on an object, sampling random candidate grasps for the one or more candidate object trajectories based on the current grasp, generating one or more grasps to be optimized for each of the one or more candidate object trajectories based on the sampled candidate grasps, and optimizing one or more of the grasps to be optimized for each of the one or more candidate object trajectories based on a cost function.

    METHOD AND SYSTEM FOR DEXTEROUS MANIPULATION BY A ROBOT

    公开(公告)号:US20250065506A1

    公开(公告)日:2025-02-27

    申请号:US18414047

    申请日:2024-01-16

    Abstract: A method for dexterous manipulation by a robot includes performing a virtual simulation where a robot model adopts a virtual target position from a virtual initial position, deriving a first policy for maneuvering a robot based on the virtual simulation, performing a first set of real simulations where a first robot adopts a real target position from a real initial position based on the first policy, and deriving a second policy for maneuvering a robot based on sensor data generated in the first set of real simulations. The method also includes combining the first policy and the second policy to derive a third policy for maneuvering a robot. The method also includes causing at least one of the first robot and a second robot to adopt a real target position based on at least one of the third policy and a subsequently derived policy for maneuvering a robot.

    SYSTEM AND METHOD FOR PROVIDING TACTILE SENSOR CALIBRATION

    公开(公告)号:US20240094081A1

    公开(公告)日:2024-03-21

    申请号:US18071035

    申请日:2022-11-29

    CPC classification number: G01L25/00

    Abstract: A system and method for providing tactile sensor calibration that include receiving force data from a force/torque sensor and tactile data from a plurality of taxels of a tactile sensor pad. The system and method also include interpolating the force data and the tactile data and pre-processing the interpolated data to align the force data and the tactile data to match data points. The system and method additionally include dividing the matched data points into individual interactions and computing a linear regression for each segment that is associated with each interaction. The system and method further include determining an amount of force that is absorbed by the tactile sensor pad based on a conversion of tactile measurements sensed by the plurality of taxels into Newtons based on the linear regression computed for each segment.

    SYSTEMS AND METHODS FOR ONLINE ITERATIVE RE-PLANNING

    公开(公告)号:US20240066695A1

    公开(公告)日:2024-02-29

    申请号:US18090966

    申请日:2022-12-29

    CPC classification number: B25J9/1664 B25J9/1689

    Abstract: Systems and methods for online iterative re-planning are provided herein. In one embodiment, a method includes receiving, at a first time step, a first grasp and an initial object pose of an agent. The method also includes generating a first set of candidate object trajectories based on the first grasp and the initial object pose. Candidate object trajectories of the first set of candidate object trajectories provide a number object poses from the initial object pose to a goal for a number of future time steps after the first time step. The method further includes calculating contact points for grasps associated with each candidate object trajectory of the first set of candidate object trajectories. The method further includes selecting a first candidate object trajectory from the first set of candidate object trajectories. The method includes causing the agent to execute the first candidate object trajectory at a second time step.

    ONLINE AUGMENTATION OF LEARNED GRASPING
    10.
    发明公开

    公开(公告)号:US20230339107A1

    公开(公告)日:2023-10-26

    申请号:US17940267

    申请日:2022-09-08

    CPC classification number: B25J9/163 B25J13/006

    Abstract: Systems and methods for online augmentation for learned grasping are provided. In one embodiment, a method is provided that includes identifying an action from a discrete action space. The method includes identifying a second set of grasps of the agent utilizing a transition model based on the action and at least one contact parameter. The at least one contact parameter defines allowed states of contact for the agent. The method includes applying a reward function to evaluate each grasp of the second set of grasps based on a set of contact forces within a friction cone that minimizes a difference between an actual net wrench on the object and a predetermined net wrench. The reward function is optimized online using a lookahead tree. The method includes selecting a next grasp from the second set. The method includes causing the agent to execute the next grasp.

Patent Agency Ranking