A method of treating the surface of a 3D object, comprising obtaining a digital 3D shape representation defining characteristics of the object; using a computerised device to convert the 3D shape representation into a digital 2D shape representation defining the 3D surface of the object as it if laid out flat; using the computerised device to generate a digital 2D tool path representation defining movements an applicator or removal tool would take to treat the surface of the shape defined by the 2D shape representation; using the computerised device to convert the 2D tool path representation to a digital 3D tool path representation defining movements that the applicator or removal tool will take to deposit material on, or remove it from, the surface to treat the 3D object; and using the 3D tool path representation to control the applicator tool or removal tool to treat the 3D object.

A method and system for automatic recovery of a machine after a collision event occurred within a workspace environment of the machine is provided. The method may include recording a plurality of configurations of a machine during execution of a task; calculating based on the plurality of recorded configurations, a swept volume occupied by the machine during execution of the task; in response to a collision event, determining, based on the swept volume, a recovery sequence of movements for the machine; and using the recovery sequence of movements to lead the machine back to a predefined known safe position after the collision event occurred.

The invention relates to the technical field of intelligent control, and particularly to a gantry platform kinematics modeling method considering parallelism and perpendicularity errors, which is applied to a gantry platform device. The gantry platform device comprises a crossbeam, a first guide rail and a second guide rail, one end of the crossbeam is in sliding fit with the first guide rail, and the other end of the crossbeam is in sliding fit with the second guide rail; the first guide rail is provided with a first longitudinal motor, and the second guide rail is provided with a second longitudinal motor; and the crossbeam is provided with a transverse motor configured to drive the gantry platform to move along the crossbeam. The method comprises: establishing a two-dimensional coordinate system; constructing a forward kinematics solution model; and constructing an inverse kinematics solution model.

An information processing device acquires trajectory information about a trajectory of a motion of a robot, adjusts parameters of the robot for optimizing two or more evaluation indicators for evaluating the motion of the robot, based on the trajectory information to calculate a plurality of optimal solutions of the two or more evaluation indicators, outputs a solution display image in which the calculated plurality of optimal solutions are rendered on a plane or in a space having the two or more evaluation indicators as a coordinate axis, acquires at least one optimal solution selected by a user from the plurality of optimal solutions displayed in the solution display image, and outputs reference information based on a history of the motion of the robot, the motion corresponding to the at least one optimal solution that has been acquired.

A motion trajectory generation method for generating a motion trajectory of a robot having a plurality of drive axes upon carrying out work at a work position includes: an obtaining step of obtaining a motion condition identified and corresponding to the work position; and a generation step of generating a motion trajectory of the robot by carrying out a search for a plurality of motion trajectories that the robot is able to implement, on the basis of the motion condition, in which in the generation step, priority levels in the search are determined on the basis of the motion condition and work directions for a plurality of work positions, and the search for the plurality of motion trajectories is carried out on the basis of the priority levels.

The temporal logic formula generation device 1X mainly includes a target relation logical formula generation means 331X and a target relation logical formula integration means 332X. The target relation logical formula generation means 331X is configured to generate, based on object-to-object relation information representing a relation between objects in a target state relating to a task of the robot, one or more target relation logical formulas that are temporal logic formulas representing relations, in the target state, between respective pair(s) of objects between which the relation is defined. The target relation logical formula integration means 332X is configured to generate a temporal logic formula into which the target relation logical formulas are integrated.