A path generation device including an acquisition unit, a setting unit, and a path generation unit. The acquisition unit is configured to acquire pose information relating to an initial pose and a target pose of a robot, position information relating to a position of the robot, obstacle information including a position of an obstacle present in a range of interference with the robot, and specification information relating to a specification including a shape of the robot. The setting unit is configured to, based on a positional relationship between the robot and the obstacle, set a clearance amount representing an amount of clearance to avoid the interference for at least one out of the robot or an obstacle present in a range of interference with the robot.

A processing system is disclosed for providing processing of objects that include a programmable motion device including an end effector, a perception system for recognizing any of the identity, location, and orientation of an object presented in a plurality of objects at an input location, a grasp acquisition system for acquiring the object using the end effector to permit the object to be moved from the plurality of objects to one of a plurality of destination bins, and a motion planning system for determining a changing portion of a trajectory path of the end effector from the object to a base location proximate to the input location, and determining an unchanging portion of a trajectory path of the end effector from the base location to a destination bin location proximate to a destination bin.

A robot simulator includes a storage device that stores model information related to the robot and an obstacle in the vicinity of the robot, and an acquisition device that obtains first input information defining a start position and an end position of operation of the robot. A processing device generates a path for moving the distal end portion of the robot from the start position to the end position while avoiding collisions between the robot and the obstacle based on the first input information and the model information. The processing device also generates image data including an illustration of the obstacle and an index indicating a via-point of the path.

Various embodiments of the technology described herein generally relate to systems and methods for trajectory optimization with machine learning techniques. More specifically, certain embodiments relate to using neural networks to quickly predict optimized robotic arm trajectories in a variety of scenarios. Systems and methods described herein use deep neural networks to quickly predict optimized robotic arm trajectories according to certain constraints. Optimization, in accordance with some embodiments of the present technology, may include optimizing trajectory geometry and dynamics while satisfying a number of constraints, including staying collision-free and minimizing the time it takes to complete the task.

A method for moving along a predetermined path with a robot in an at least a partially automated manner includes determining a deployment position on a current path section of the predetermined path for which a distance parameter satisfies a predetermined condition, and moving to the deployment position with the robot. In one aspect, the robot may be moved to the deployment position if a deployment condition is satisfied. The distance parameter may be determined on the basis of a distance of a current position of the robot relative to the current path section. The predetermined condition may be that the distance parameter has a value that is less than or equal to the values of the distance parameter of all positions in a partial area of the current path section, which is in particular complementary to the deployment position.

A robot controller having a function that simplifies learning and a robot control method. The robot controller includes: a learning section configured to carry out learning of detecting a deviation between a commanded trajectory representing a position of the robot generated according to the command values and an operation trajectory representing an actual position where the robot has moved, and generate a corrected program by adjusting the commanded trajectory; a saving section configured to save the corrected program; and a relearning section configured to carry out relearning on a relearning location, the relearning location being a part of the operation trajectory designated by an operator.

A trajectory generation device includes a storage unit that stores a plurality of trajectories; a trajectory acquisition unit that acquires a trajectory, corresponding to an environment similar to a current environment, from the plurality of trajectories stored in the storage unit; and a trajectory generation unit that calculates a longest trajectory part, which is present in a moving object moving area in the trajectory acquired by the trajectory acquisition unit, and generates a trajectory by connecting both ends of the calculated longest trajectory part to a predetermined start point and a predetermined end point respectively.

A programming device receives a number of local coordinate systems from a user. Each local coordinate system is referenced directly or via at least one other local coordinate system to a global machine coordinate system of a motion-controlled machine. The programming device receives from the user, in each case with reference to one of the local coordinate systems, a number of positions to be approached by the end effector and/or a number of obstacles to be bypassed by the end effector. The programming device determines, with reference to the positions to be approached received from the user and the obstacles received from the user in the global machine coordinate system, the path to be traveled by the end effector The programming device stores the path to be traveled by the end effector as a first file so that it can be retrieved again at a later time.

Based on the premise that a step-out will occur in a stepping motor, this invention provides a suitable countermeasure for when a step-out occurs. A robot device includes: a robot arm mechanism having a joint; a stepping motor that generates motive power that actuates the joint; a motor driver that drives the stepping motor; a trajectory calculating section that calculates a trajectory along which an attention point of the robot arm mechanism moves from a current position to a final target position; a command value outputting section that outputs a command value in accordance with the trajectory calculated by the trajectory calculating section to the motor driver; and a step-out detecting section that detects a step-out of the stepping motor. The robot device also includes a system control section. When a step-out is detected, the system control section controls the trajectory calculating section and the command value outputting section so as to recalculate a trajectory to the final target position from a position of the attention point that is shifted due to the step-out, and to move the attention point in accordance with the recalculated trajectory.

An offline teaching device has a calculation unit which calculates a second position of a second tool on a work line which is separated by a predetermined distance from a first position of a first tool on the work line, calculates a workpiece position where the first tool in the first position contacts or adjoins the workpiece, and calculates a workpiece position and posture such that the second tool in the second position contacts or adjoins the workpiece by changing the posture of the workpiece from the workpiece position with respect to the first tool, while maintaining the work posture of the first tool, and has a generation unit which generates a robot teaching position based on the position and posture of the workpiece and the holding position of the workpiece, and generates a program such that the first tool and the second tool pass along the work line.