The monitoring of a technical system using sensor data. In the event of the failure of a sensor, in this case, for the failed sensor, virtual sensor data are created on the basis of the remaining functional sensors. In this case, the sensors for the calculation of the virtual sensor data are selected in two stages. In a first step, firstly, possible candidates of sensors are ascertained on the basis of a knowledge-based approach and the topology of the system. A second step involves calculating a mathematical relationship between the sensor data of a faulty sensor and the possible candidates of sensors for the calculation of the virtual sensor data. Those sensors which form a suitable basis for the calculation of the virtual sensor data can be identified in this way.

A position measuring device includes a scale carrier with a measuring scale. A scanner is configured to generate position signals by scanning the measuring scale. A processor is configured to process the position signals into a digital position value. An interface is configured to communicate with downstream electronics. At least one collision sensor is assigned to the position measuring device, and is configured to generate analog or digital measured values from a time characteristic of which collision events are determinable. The measured values are fed to an evaluator configured to determine the collision events by evaluating the time characteristic of the measured values in a controller.

In described embodiments of method for executing autonomous bin picking, a physical environment comprising a bin containing a plurality of objects is perceived by one or more sensors. Multiple artificial intelligence (AI) modules feed from the sensors to compute grasping alternatives, and in some embodiments, detected objects of interest. Grasping alternatives and their attributes are computed based on the outputs of the AI modules in a high-level sensor fusion (HLSF) module. A multi-criteria decision making (MCDM) module is used to rank the grasping alternatives and select the one that maximizes the application utility while satisfying specified constraints.

A parallel kinematic manipulator system having three degrees of freedom and a method of controlling and visualizing work objects using force feedback and oscillation algorithms is provided. Three co-planar linear actuators operate symmetrically and parallel to an effector arm and are pivotally connected by three magnetic disc swivel joints to a base plate. The disc swivel joints each include a convex upper and lower swivel member having two dimensional gear patterns structured into their contacting and non-sliding surfaces. A pulsed illumination source consists of an annular LED array and is synchronized to the oscillation frequencies of the system to provide visual filtering capabilities. A control unit includes a method for keeping a work object balanced by force feedback and without the need for angle sensors at the end-effector, as well as methods for rotation of work objects and control of the pulsed illumination source. Sound trap ridges are included as part of the housing to reduce system noise.

Systems and methods are described for reacting to a feature in an environment of a robot based on a classification of the feature. A system can detect the feature in the environment using a first sensor on the robot. For example, the system can detect the feature using a feature detection system based on sensor data from a camera. The system can detect a mover in the environment using a second sensor on the robot. For example, the system can detect the mover using a mover detection system based on sensor data from a lidar sensor. The system can fuse the data from detecting the feature and detecting the mover to produce fused data. The system can classify the feature based on the fused data and react to the feature based on classifying the feature.

A parallel kinematic manipulator system having three degrees of freedom and a method of controlling and visualizing work objects using force feedback and oscillation algorithms is provided. Three co-planar linear actuators operate symmetrically and parallel to an effector arm and are pivotally connected by three magnetic disc swivel joints to a base plate. The disc swivel joints each include a convex upper and lower swivel member having two dimensional gear patterns structured into their contacting and non-sliding surfaces. A pulsed illumination source consists of an annular LED array and is synchronized to the oscillation frequencies of the system to provide visual filtering capabilities. A control unit includes a method for keeping a work object balanced by force feedback and without the need for angle sensors at the end-effector, as well as methods for rotation of work objects and control of the pulsed illumination source. Sound trap ridges are included as part of the housing to reduce system noise.

A method for controlling a robotic manipulator according to a task comprises accepting a feedback signal including a sequence of multi-modal observations of a state of execution of the task. The multi-modal observations are processed with a neural network having a self-attention module with a hierarchically conditioned output to produce a skill of the robotic manipulator and an action conditioned on the skill. The neural network is trained in a supervised manner with demonstration data to produce a sequence of skills and a corresponding sequence of actions for the actuators of the robotic manipulator to perform the task. The method further comprises determining one or more control commands for the one or more actuators based on the produced action and submitting the one or more control commands to the one or more actuators causing a change of the state of execution of the task.