A controller controls a motion of an object performing a task for changing a state of the object from a start state to an end state while avoiding collision of the object with an obstacle according to an optimal trajectory determined by solving an optimization problem of the dynamics of the object producing an optimal trajectory for performing the task subject to constraints on a solution of first-order stationary conditions modeling a minimum distance between the convex hull of the object and the convex hull of the obstacle using complementarity constraints.

The present teaching relates to a method and system for path planning. A target is tracked via one or more sensors. Information of a desired pose of an end-effector with respect to the target and a current pose of the end-effector is obtained. Also, a minimum distance permitted between an arm including the end-effector and each of at least one obstacle identified between the current pose of the end-effector and the target is obtained. A weighting factor previously learned is retrieved and a cost based on a cost function is computed in accordance with a weighted smallest distance between the arm including the end-effector and the at least one obstacle, wherein the smallest distance is weighted by the weighting factor. A trajectory is computed from the current pose to the desired pose by minimizing the cost function.

The work program production system includes a photographing unit that photographs an image including an object to be welded, a coordinate system setting unit that sets a user coordinate system based on a marker included in the image photographed by the photographing unit, a point-group-data plotting unit that detects a specific position of the marker on the basis of the image, sets the detected specific position on point group data acquired by a distance measurement sensor that measures a distance to the object to be welded, and plots, in the user coordinate system, the point group data to which coordinates in the user coordinate system using the set specific position as an origin are given, and a program production unit that produces a welding program so as to allow a welding robot virtually placed in the user coordinate system to perform a welding operation on the basis of the point group data plotted in the user coordinate system, while avoiding interference with the point group data.

The present teaching relates to a method and system for path planning. A target is tracked via one or more sensors. Information of a desired pose of an end-effector with respect to the target and a current pose of the end-effector is obtained. Also, a minimum distance permitted between an arm including the end-effector and each of at least one obstacle identified between the current pose of the end-effector and the target is obtained. A weighting factor previously learned is retrieved and a cost based on a cost function is computed in accordance with a weighted smallest distance between the arm including the end-effector and the at least one obstacle, wherein the smallest distance is weighted by the weighting factor. A trajectory is computed from the current pose to the desired pose by minimizing the cost function.

An offline teaching device for reducing an amount of time required to generate a motion route with which interference could be avoided, the offline teaching device including at least one processor. The processor generates, as a result of a motion program that includes a plurality of teaching points being input, numerous interpolation points on a motion route of a tool distal-end point of a robot, the motion route being formed among the teaching points in accordance with the motion program; and detects whether interference occurs between each of the generated interpolation points and a peripheral device.

Methods, systems, and apparatus, including computer-readable storage devices, for robot navigation using 2D and 3D path planning. In the disclosed method, a robot accesses map data indicating two-dimensional layout of objects in a space and evaluates candidate paths for the robot to traverse. In response to determining that the candidate paths do not include a collision-free path across the space for a two-dimensional profile of the robot, the robot evaluates a three-dimensional shape of the robot with respect to a three-dimensional shape of an object in the space. Based on the evaluation of the three-dimensional shapes, the robot determines a collision-free path to traverse through the space.

Disclosed are a collision avoidance method for a moving device, a collision avoidance apparatus for a moving device, and a computer-readable storage medium. This application relates to the field of artificial intelligence technologies. According to the method, a parking direction of a moving device in an avoidance area is adjusted, so that a startup time used by the moving device after avoidance completes may be reduced. The method includes: determining a target path direction of a moving device; determining a first candidate parking direction and a second candidate parking direction; determining, based on the target path direction, a target parking direction of the moving device from the first candidate parking direction and the second candidate parking direction; and controlling, based on the target parking direction, the moving device to be parked in the avoidance area.

Provided is a method for computer-aided user assistance during the activation of a movement planner for a machine, in which: a user interface is provided and can be used by a user to specify parameterization data for the movement planner, wherein the parameterization data comprise a machine model and an environment model; the collision-free movement space and the collision-prone movement space of the machine in the configuration space are determined on the basis of parameterization data specified via the user interface; one or more features with respect to the collision-free and/or collision-prone movement space are determined; a predefined plausibility criterion is checked for a respective feature of at least some of the features, wherein, if the plausibility criterion has not been satisfied, an output in the form of a warning message is produced via the user interface.

Solutions for multi-robot configurations are co-optimized, to at least some degree, across a set of non-homogenous parameters based on a given set of tasks to be performed by robots in a multi-robot operational environment. Non-homogenous parameters may include two or more of: the respective base position and orientation of the robots, an allocation of tasks to respective robots, respective target sequences and/or trajectories for the robots. Such may be executed pre-runtime. Output may include for each robot: workcell layout, an ordered list or vector of targets, optionally dwell time durations at respective targets, and paths or trajectories between each pair of consecutive targets. Output may provide a complete, executable, solution to the problem, which in the absence of variability in timing, can be used to control the robots without any modification. A genetic algorithm, e.g., Differential Evolution, may optionally be used in generating a population of candidate solutions.

A technique for automatically finding a collision-free return-to-home path for a robot. The technique includes running a simulated virtual 3D environment which emulates the physical robot and workcell in real time, including the positions and poses of all robots, workpieces and obstacles in the workcell. Upon request by an operator, a return-to-home path search is executed based on the virtual 3D environment, where the path search calculates a solution which moves the robot from a current position to its home or recovery position while avoiding collisions with other robots, workpieces or objects in the workcell. In addition to collision avoidance, the path search considers other constraints such as prohibited zones in the workspace and robot joint positions. When the recovery path is computed, the solution program is sent back to the physical environment for execution by the physical robot.