An object can be moved via a robotic system with a combination of force and position control. The control system can include the object to be moved, the robotic system that moves the object, at least one force sensor, at least one position sensor, and a controller. A position control output, a force control output, and a hybrid weighting value can each be determined by the controller based on sensor data and then combined to determine an amount of position control and/or force control to be applied to move the object and/or modify an object in motion's trajectory.

A computing system and method for estimating friction and/or center of mass (CoM) are presented. The system may perform the method by selecting at least one of: (i) a first joint from among a plurality of joints, or (ii) a first arm segment from among a plurality of arm segments. The computing system further outputs a set of one or more movement commands for causing robot arm movement that includes relative movement between the first arm segment and a second arm segment via the first joint, and receiving a set of actuation data and a set of movement data associated with the first joint or the first arm segment. The computing system further determines, based on the set of actuation data and the set of movement data, at least one of: (i) a friction parameter estimate or (ii) a CoM estimate.

As a preferred embodiment of the present invention, a device for controlling a collaborative robot includes a collision detection unit configured to sense a collision of the collaborative robot; a control unit configured to control an operation mode of the collaborative robot when the collision detection unit senses the collision; and a collision countermeasure unit configured to apply, when the collision detection unit senses the collision, a collision compensation value to each of a plurality of joints in the collaborative robot so as to change a proceeding direction of a force applied to the each of the plurality of joints.

A robotic system is provided for assembling parts together. In the assembly process, both parts are moving separately with one part moving on an assembly base and another part moving on a moveable arm of a robot base. Motion data is measured by an inertial measurement unit (IMU) sensor. Movement of the robot base or moveable arm is then compensated based on the measured motion to align the first and second parts with each other and assemble the parts together.

A method for retrieving an inventory item based on a handling robot, where the handling robot includes: a storage frame; and a material handling device installed on the storage frame, and including a telescopic arm and a manipulator installed to the telescopic arm; and the method for retrieving an inventory item includes: driving, by the telescopic arm, the manipulator to extend to a preset position of warehouse shelf along a preset horizontal reference line; loading, by the manipulator that is remained on the reference line, the inventory item located in the preset position; driving, by the telescopic arm, the manipulator loaded with the inventory item to move to the storage frame along the reference line; and unloading, by the manipulator that is remained on the reference line, the inventory item to the storage frame.

A decoupling control method for a humanoid robot includes: decomposing tasks of the humanoid robot to obtain kinematic tasks and dynamic tasks, and classifying corresponding joints of the humanoid robot into kinematic task joints or dynamic task joints; solving desired positions and desired speeds of the kinematic task joints for performing the kinematic tasks according to desired positions and desired speeds of ends in the kinematic tasks using inverse kinematics; calculating torques of the kinematic task joints based on the desired positions and desired speeds of the kinematic task joints; and solving a pre-built optimization model of torques required for the dynamic task joints based on the calculated torques of the kinematic task joints, to obtain torques required by the dynamic task joints for performing the dynamic tasks.

A direct pose feedback (DPF) control method applied to a DPF controlled machine is provided. The DPF control method includes a pose compensation control in addition to the position feedback control. The pose compensation control includes an initiation step, a reference system step, an actual pose calculation step and a position compensation step. The sum of the primary driving value and the compensation driving value is output to the driver of each of the motors. The advantage of the DPF control method is that the existing real-time position control loop in the controller can remain unchanged, while the pose compensation control is added to eliminate tool pose error resulted from geometric errors in the machine. The DPF controlled machine uses a pose measuring mechanism to measure the actual pose of the tool and to compensate the tool pose error. Hence, the DPF controlled machine is free of geometric errors.

A robot control device includes: a creep-information storage unit that stores an amount of bending in correspondence with a cumulative time, the bending occurring in a robot due to creep deformation; a mastering-data storage unit that stores mastering data of the robot; a timer that measures the cumulative time; and a correction unit that corrects the mastering data stored in the mastering-data storage unit based on the amount of bending stored in the creep-information storage unit in correspondence with the cumulative time measured by the timer.

A method and a robot controller for controlling a robot arm, where the robot arm comprises a plurality of robot joints connecting a robot base and a robot tool flange, where each of the robot joints comprises an output flange movable in relation to a robot joint body and a joint motor configured to move the output flange in relation to the robot joint body. The robot arm is controlled based on vibrational properties of at least one external object connected to the robot arm, where the vibrational properties are received via an external object installation interface by generating control signals for said robot arm based on a target motion and the received vibrational properties of the at least one external object, the control signal comprises control parameters for said joint motor.

A robot control device includes the following: a main control unit; a servo control unit, which receives a position command θc from the main control unit; and a bending correction block (24), which corrects the bending of the reduction gear connected to the servo motor. The bending correction block (24) includes the following: a first position-correction-value calculation means (63), which finds a first position-command correction value θsgc based on the position command θc; and a second position-command-correction-value calculation means (64), which finds a second position-command correction value θskc based on the interference torque τa. The servo control unit drives the servo motor based on a new position command obtained by adding the first position-command correction value θsgc and the second position-command correction value θskc to the position command θc.