A robot is configured to perform a task on an object using a method for generating a 3D model sufficient to determine a collision free path and identify the object in an industrial scene. The method includes determining a predefined collision free path and scanning an industrial scene around the robot. Stored images of the industrial scene are retrieved from a memory and analyzed to construct a new 3D model. After an object is detected in the new 3D model, the robot can further scan the image in the industrial scene while moving along a collision free path until the object is identified at a predefined certainty level. The robot can then perform a robot task on the object.

Apparatuses, systems, and techniques to grasp objects with a robot. In at least one embodiment, a neural network is trained to determine a grasp pose of an object within a cluttered scene using a point cloud generated by a depth camera.

A device may include a processor. The processor may receive sensor data representative of an environment comprising a robot. The processor may extract features from the sensor data to generate an extracted feature set indicating an observation of the robot within the environment. The processor may generate a feature set indicating an expected observation of the robot within the environment based on pre-defined parameters of the robot. The processor may determine a difference between the observation and the expected observation of the robot. The processor may determine a systemic failure based on the difference between the observation and the expected observation of the robot exceeding a threshold value. The processor may instruct the robot to transition to a non-operative state responsive to the systemic failure being determined.

An automatic positioning method and an automatic control device are provided. The automatic control device includes a processing unit, a memory unit, and a camera unit to automatically control a robotic arm. When the processing unit executes a positioning procedure, the camera unit obtains a first image of the robotic arm. The processing unit analyzes the first image to establish a three-dimensional working environment model and obtains first spatial positioning data. The processing unit controls the robotic arm to move a plurality of times to sequentially obtain a plurality of second images of the robotic arm by the camera unit and analyzes the second images and encoder information of the robotic arm to obtain second spatial positioning data. The processing unit determines whether an error parameter between the first spatial positioning data and the second spatial positioning data is less than a specification value to end the positioning procedure.

A robotic system includes a controller configured to obtain image data from one or more optical sensors and to determine one or more of a location and/or pose of a vehicle component based on the image data. The controller also is configured to determine a model of an external environment of the robotic system based on the image data and to determine tasks to be performed by components of the robotic system to perform maintenance on the vehicle component. The controller also is configured to assign the tasks to the components of the robotic system and to communicate control signals to the components of the robotic system to autonomously control the robotic system to perform the maintenance on the vehicle component.

A robot system models the behavior of a user when the user occupies an operating zone associated with a robot. The robot system predicts future behaviors of the user, and then determines whether those predicted behaviors interfere with anticipated behaviors of the robot. When such interference may occur, the robot system generates dynamics adjustments that can be implemented by the robot to avoid such interference. The robot system may also generate dynamics adjustments that can be implemented by the user to avoid such interference.

A trajectory planning apparatus including a joint axis classification unit for classifying a plurality of joint axes of a robot into axis groups, according to joint axis classification information for classifying into the axis groups including at least a path search axis group, a path search unit for searching for a path of an angle of the joint axis classified into the path search axis group that minimizes an evaluation function for evaluating a planed trajectory, based on trajectory start point information representing a posture of the robot at a start point of the planed trajectory and trajectory endpoint information representing a posture of the robot at an end point of the planned trajectory, and an axis group angle calculation unit for calculating an angle of the joint axis classified into each axis group other than the path search axis group during the search of the path.

Provided is an information processing apparatus that is used to develop a control program of an autonomous operation apparatus including a movable portion or that assists the development. An information processing apparatus that processes a control program of an apparatus to be controlled including a movable portion includes: a computation unit that computes an operation of the apparatus to be controlled according to the control program including a command value of each time period regarding the movable portion; and a holding unit that holds an ideal state of the apparatus to be controlled that operates according to the control program obtained as a computation result of the computation unit, in which the control program is output after adding the ideal state to the control program.

A robot system including a robot apparatus and an imaging apparatus includes a control apparatus configured to control the robot apparatus and the imaging apparatus, and the control apparatus controls, based on a path in which a predetermined part of the robot apparatus is moved, a movement of the imaging apparatus to image the predetermined part even if the robot apparatus is moved.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for planning robotic movements to capture desired sensor measurements. One of the methods includes generating a three-dimensional representation of a robotic operating environment, wherein the robotic operating environment comprises a robot and a sensor, including: generating a first three-dimensional representation of a field of view of the sensor in the robotic operating environment, and generating a second three-dimensional representation of a desired observation of an object in the robotic operating environment; generating a plurality of candidate plans for the robot; selecting, from the candidate plans, a particular candidate plan that intersects the first three-dimensional representation of the field of view of the sensor and the second three-dimensional representation of the desired observation of the object; and causing the robot to execute the particular candidate plan to make the desired observation of the object in the robotic operating environment.