A method includes: accessing a virtual model defining a geometry of a workpiece; navigating an optical sensor about the workpiece; accessing an image of the workpiece; detecting a marker, on the workpiece, depicted in the image; defining a first workpiece region of the workpiece bounded by the marker; defining a toolpath within the first workpiece region based on a geometry of the first workpiece region represented in the virtual model; assigning a first target force to the first toolpath; and during a processing cycle accessing a first sequence of force values output by a force sensor coupled to the sanding head, navigating the sanding head across the first workpiece region according to the first toolpath, and based on the first sequence of force values, deviating the sanding head from the first toolpath to maintain forces of the sanding head on the workpiece proximal the first target force.

A robot control apparatus includes a robot control part that controls a robot; and a force detection information acquisition part that acquires force detection information from a force detection unit. The robot control part, in which a range of control values for operating a robot by force control based on the force detection information is designated, operates the robot based on the control values and the designated range.

Systems and methods are provided for an automation system. The systems and methods calculate a motion trajectory of a manipulator and an end-effector. The end-effector is configured to grasp a target object. The motion trajectory defines successive positions of the manipulator and the end-effector along a plurality of via-points toward the target object. The systems and methods further acquire force/torque (F/T) data from an F/T sensor associated with the end-effector, and adjusts the motion trajectory based on the F/T data.

A device for robotic direct lead-through teaching includes a robot, a replacing member and a lead-through teaching member. The robot has an operation member coupled with the replacing member. The lead-through teaching member mounted replaceably at the replacing member has a force sensor. The force sensor has six-axis load information. A path teaching is executed manually upon the operation member of the robot so as to store coordinate information. In additional, a method for robotic direct lead-through teaching is also provided.

A method includes: accessing a coating thickness range for workpiece coating; triggering an optical sensor to capture scan data representing the workpiece; triggering a depth sensor to capture a first depth value; assembling the scan data into a first virtual model representing the workpiece; defining first spray parameters corresponding to a minimum coating thickness; defining a first toolpath; driving a coating applicator along the first toolpath to spray the coating onto the workpiece; triggering the depth sensor to capture a second depth value; calculating a first coating thickness based on the first depth value and the second depth value; in response to the first coating thickness falling below the target minimum coating thickness defining a second set of spray parameters and a second toolpath; and driving the coating applicator along the second toolpath to spray the coating onto the workpiece according to the second set of spray parameters.

Systems and methods are provided for an automation system. The systems and methods calculate a motion trajectory of a manipulator and an end-effector. The end-effector is configured to grasp a target object. The motion trajectory defines successive positions of the manipulator and the end-effector along a plurality of via-points toward the target object. The systems and methods further acquire force/torque (F/T) data from an F/T sensor associated with the end-effector, and adjusts the motion trajectory based on the F/T data.

A robotic controller is provided for generating sequences of movement primitives for sequential tasks of a robot having a manipulator. The controller includes at least one control processor, and a memory circuitry storing a dictionary including the movement primitives, a pretrained learning module, and a graph-search based planning module having instructions stored thereon. The controller to perform steps acquiring a planned task provided by an interface device operated by a user, wherein the planned task is represented by an initial state and a goal state with respect to an object, generating a planning graph by searching a feasible path of the object for the novel task using the graph-search based planning module and selecting movement primitives from the dictionary in the pretrained learning module, wherein the pretrained learning module has been trained based on demonstration tasks, parameterizing the feasible path represented by the movement primitives as dynamic movement primitives (DMPs) using the initial state and goal state, and implementing the parameterized feasible path as a trajectory according to the selected movement primitives using the manipulator of the robot by tracking and following the parameterized for the planned task.

A force sensor unit includes a force sensor, a casing housing the force sensor within a space surrounded by one end portion, another end portion, and a side portion, an attachment member having a first attachment portion that can be attached to a robot arm of a robot and a second attachment portion detachably attached to the one end portion of the casing in a position different from that of the first attachment portion, and a wiring cable connected to the force sensor and routed from inside the casing to outside of the casing, wherein a positioning portion for positioning with respect to the robot arm is provided in the first attachment portion, and a part of the wiring cable is provided along a circumferential direction of the side portion.

It A waste sorting robot (100) comprises a manipulator (101) moveable within a working area (102). A gripper (103) is connected to the manipulator (101) and arranged to selectively grip a waste object (104, 104a, 104b, 104c) in the working area (102). A controller (108) is in communication with a sensor (107) and is configured to receive detected object parameters, and determine a throw trajectory (109) of the gripped waste object (104) towards a target position (106) based on the detected object parameters of the gripped waste object (104). The controller (108) is configured to send control instructions to the gripper (103) and/or manipulator (101) so that the gripper (103) and/or manipulator (101) accelerates the gripped waste object (104) and releases the waste object (104) at a throw position with a throw velocity and throw angle towards the target position (106) so that the waste object (104) is thrown along the determined throw trajectory (109). A related method of controlling a waste robot is also disclosed.

A method includes: accessing a coating thickness range for workpiece coating; triggering an optical sensor to capture scan data representing the workpiece; triggering a depth sensor to capture a first depth value; assembling the scan data into a first virtual model representing the workpiece; defining first spray parameters corresponding to a minimum coating thickness; defining a first toolpath; driving a coating applicator along the first toolpath to spray the coating onto the workpiece; triggering the depth sensor to capture a second depth value; calculating a first coating thickness based on the first depth value and the second depth value; in response to the first coating thickness falling below the target minimum coating thickness defining a second set of spray parameters and a second toolpath; and driving the coating applicator along the second toolpath to spray the coating onto the workpiece according to the second set of spray parameters.