A robot control apparatus according to one or more embodiments may include: a calculating unit configured to calculate an interference range of a robot based on a model of the robot in a state in which an object is gripped by a gripper with which the robot is equipped; and a planning unit configured to plan a motion of the robot based on the model and the interference range.

Mitigating the reality gap through optimization of one or more simulated hardware parameters for simulated hardware components of a simulated robot. Implementations generate and store real navigation data instances that are each based on a corresponding episode of locomotion of a real robot. A real navigation data instance can include a sequence of velocity control instances generated to control a real robot during a real episode of locomotion of the real robot, and one or more ground truth values, where each of the ground truth values is a measured value of a corresponding property of the real robot (e.g., pose). The velocity control instances can be applied to a simulated robot, and one or more losses can be generated based on comparing the ground truth value(s) to corresponding simulated value(s) generated from applying the velocity control instances to the simulated robot. The simulated hardware parameters and environmental parameters can be optimized based on the loss(es).

Proposed is a capturing apparatus. The capturing apparatus may include a setting unit configured to set environment information of a robot equipped with a camera; and a pattern unit configured to set a capturing pattern of the robot based on the environment information.

A robotic system is disclosed. The system includes a memory configured to store for each of a plurality of items a set of attribute values representing one or more physical attributes of the item. The system includes one or more processors coupled to the communication interface and configured to use the attribute values as inputs to a physic engine configured to compute the stability of a simulated stack of items comprising at least a subset of the plurality of items.

In order to be able to automatically eliminate discrepancies, arising in the course of the configuration of a robot-object system environment, between the reality of the robot-object system environment and its digital representation as a CAD model, without manual on-site commissioning of the robot-object system environment with adaptation of the CAD model to the reality, the following is proposed for configuring a robot-object system environment having at least one object and having a robot for object manipulation and object sensing: synchronizing a digital robot twin, which digitally represents the robot-object system environment and controls the robot for the object manipulation on the basis of a control program, for expedient use of the robot in the robot-object system environment during the object manipulation, appropriately and, in this regard, in one or two stages.

In one aspect, there is provided a computer-implemented method that includes receiving a request to generate workcell data representing physical dimensions of a workcell having a physical robot arm, executing a calibration program that causes the physical robot arm to move within the workcell and record locations within the workcell at which the robot arm made contact with an object, generating, from the locations within the workcell at which one or more sensors of the robot arm recorded a resistance above a threshold, a representation of physical boundaries in the workcell, obtaining an initial virtual representation of the workcell, and updating the initial virtual representation of the workcell according to the representation of physical boundaries generated from executing the calibration program.

A system and a method predict a collision free posture of a kinematic system. The method includes: receiving a 3D virtual environment, receiving a 3D representation of the kinematic system and a set of 3D postures defined for the 3D virtual kinematic system, receiving a target task to be performed by the kinematic system with respect to the surrounding environment, and receiving a prescribed location within the 3D virtual environment. The prescribed location defines a position at which the 3D virtual kinematic system has to be placed within the 3D virtual environment. A collision free detection function (CFD) is applied to a set of input data containing the 3D virtual environment, the target task, the prescribed location and the set of postures. The CFD function outputs a set of collision free postures enabling the kinematic system to perform the target task when located at the prescribed location.

A control device estimates a position and pose of an imaging device relative to a robot based on an image of the robot captured by the imaging device. A simulation device arranges a robot model at a teaching point, and generates a simulation image of the robot model captured by a virtual camera that is arranged so that a position and pose of the virtual camera relative to the robot model in the virtual space coincide with the estimated position and pose of the imaging device. The control device determines an amount of correction of a position and pose of the robot for the teaching point so that the position and pose of the robot on the actual image captured after the robot has been driven according to a movement command to the teaching point approximate to the position and pose of the robot model on the simulation image.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium for selecting actions for an agent in an environment. In one aspect, a system comprises receiving an agent trajectory that characterizes interaction of an agent with an environment to perform one or more initial tasks in the environment; processing the agent trajectory to generate a classification output that comprises a respective classification score for each agent category in a set of possible agent categories, wherein each possible agent category is associated with a respective task selection policy; classifying the agent as being included in a corresponding agent category based on the classification scores; selecting tasks to be performed by the agent in the environment based on the task selection policy of the corresponding agent category; and transmitting, to the agent, data defining the selected tasks to be performed by the agent in the environment.

A handling assembly having a handling device for carrying out at least one working step with and/or on a workpiece in a working region of the handling device, stations being situated in the working region, with at least one monitoring sensor for the optical monitoring of the working region and for provision as monitoring data, with a localization module, the localization module being designed to recognize the stations and to determine a station position for each of the stations.