An apparatus and a method for planning contact-interaction trajectories are provided. The apparatus is a robot that accepts contact interactions between the robot and the environment. The robot stores a dynamic model representing geometric, dynamic, and frictional properties of the robot and the environment, and a relaxed contact model to representing dynamic interactions between the robot and the object via virtual forces. The robot further determines, iteratively until a termination condition is met, a trajectory, associated control commands for controlling the robot, and virtual stiffness values by performing optimization reducing stiffness of the virtual force and minimizing a difference between the target pose of the object and a final pose of the object moved from the initial pose. Further, an actuator moves a robot arm of the robot according to the trajectory and the associated control commands.

A method of teaching in a holding force for holding an object by a gripper of a robot manipulator, the gripper having gripper jaws elastically deformable in a reversible manner, the method including: closing the gripper until the gripper jaws contact the object at contact points of the gripper jaws; externally applying a desired closing force at connection points of the gripper jaws to gripper jaw bearings such that the connection points move relative to the contact points, thereby elastically deforming the gripper jaws; actuating a gripper drive to maintain the current position of the connection points and terminating the closing force externally applied onto the connection points; and ascertaining and storing a value of a gripping force or a gripping torque, wherein the gripping force or the gripping torque is produced by elastic deformation of the gripper jaws and is exerted onto the connection points by the gripper jaws.

Provided is a control device of a robot hand. The robot hand includes a first finger and a second finger of which finger pad surfaces are opposed to each other. The control device includes: a target object determining unit that is configured to be able to determine a target object; a operation mode selector that is configured to be able to select an operation mode between a first operation mode and a second operation mode in accordance with the target object determined by the target object determining unit, the second operation mode in which contact areas of the finger pad surfaces of the first finger and the second finger with the target object are wider than in the first operation mode; and a hand controller that is configured to be able to control an operation of the robot hand upon gripping the target object in the operation mode selected by the operation mode selector.

An end-effector may include a base, a plurality of underactuated fingers coupled to the base; and an adhesion gripper coupled to the base. An end-effector may include a base, an actuator, a first underactuated finger comprising a proximal link and a distal link, the proximal link including a distal end, a guide for a first tendon spaced a first distance away from the distal end of the proximal link and the distal link including a lever arm disposed on a proximal side to the distal pad and which extends in a volar direction from a first axis, and a node disposed on the lever arm sized and shaped to receive a first tendon. The end-effector may include a first revolute joint compliant in a first direction disposed between the base and the proximal link; and a second revolute joint compliant in the first direction disposed between the proximal link and the distal link.

A manipulation controller is provided for reorienting an object by a manipulator of a robotic system. The manipulation controller includes an interface controller configured to acquire measurement data from sensors arranged on the robotic system, at least one processor, and a memory configured to store a computer-implemented method. The instructions of the method include acquiring measurement data from vision sensors and force sensors arranged on the robotic system, determining an input-output relation for the object based on a nonlinear static model representing input-output relationships between contact forces and movements of the object on the workbench, representing interaction between the object and the manipulator using complementarity constraints to capture the contact state between the object and the manipulator, formulating a representation for frictional stability of the object based on the non-linear static model at the external contacts with the workbench; formulating a bilevel optimization problem so as to maximize the frictional stability over a position trajectory of the object being manipulated on the workbench, estimating uncertainty value in physical parameters to be compensated by performing the bilevel optimization problem, solving the bilevel optimization problem using the non-linear optimization solver and generating control data with respect to a sequence of the contact forces being applied to the object by using the manipulator.

A method for object grasping, including: determining features of a scene; determining candidate grasp locations; determining a set of candidate grasp proposals for the candidate grasp locations; optionally modifying a candidate grasp proposal of the set; determining grasp scores associated with the candidate grasp proposals; selecting a set of final grasp proposals based on the grasp scores; and executing a grasp proposal from the set of final grasp proposals.

A method for object grasping, including: determining features of a scene; determining candidate grasp locations; determining a set of candidate grasp proposals for the candidate grasp locations; optionally modifying a candidate grasp proposal of the set; determining grasp scores associated with the candidate grasp proposals; selecting a set of final grasp proposals based on the grasp scores; and executing a grasp proposal from the set of final grasp proposals.

A control method of a manipulator is provided. The method includes photographing a target using a camera and detected the target using the photographed data. A holding motion for the target is set based on the detected target and a robot is operated to hold the target based on the set holding motion.

A robot hand includes a motor, claws configured to grip a workpiece in accordance with rotation of the motor, an encoder configured to detect a rotational position of the motor, and a control device configured to control a torque of the motor such that the claws grip the workpiece in accordance with the rotational position.

A set of one or more potentially graspable features for one or more objects present in a workspace area are determined based on visual data received from a plurality of cameras. For each of at least a subset of the one or more potentially graspable features one or more corresponding grasp strategies are determined to grasp the feature with a robotic arm and end effector. A score associated with a probability of a successful grasp of a corresponding feature is determined with respect to each of a least a subset of said grasp strategies. A first feature of the one or more potentially graspable features is selected to be grasped using a selected grasp strategy based at least in part on a corresponding score associated with the selected grasp strategy with respect to the first feature. The robotic arm and the end effector are controlled to attempt to grasp the first feature using the selected grasp strategy.