An exoskeleton comprising a plurality of support structures, and a plurality of joint mechanisms each joint mechanism rotatably coupling at least two of the plurality of support structures. A sensor suite discrepancy detection system can be operable to interrogate the suite of sensors within the exoskeleton, and can comprise a plurality of sensor groups, each associated with a respective joint mechanism, and each comprising a plurality of sensors from a suite of sensors. A controller can be configured to recruit at least one substitute sensor from a first sensor group of based on an identified discrepancy between the sensor output data of at least two sensors within the first sensor group and a target sensor within the first sensor group, and to execute a remedial measure associated with a safety mode of the exoskeleton for safe operation of the exoskeleton.

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 robotic assembly operation is provided for assembling a second part to a first part. During setup of the assembly operation, control parameters and a control scheme are set and changed by simulating the operation and testing whether performance requirements are met. A dry run may be performed thereafter, and test data may be collected after running the simulation to determine if the performance requirements are satisfied during the dry run. During production, production data may also be collected and control parameters may be tuned when changes occur during production in order to maintain stable assembly.

An exoskeleton comprising a plurality of support structures, and a plurality of joint mechanisms each joint mechanism rotatably coupling at least two of the plurality of support structures. A sensor discrepancy detection system can be operable to compare sensor output data from a user operated force moment sensor and at least one torque sensor of a joint mechanism. A controller can be configured to recruit at least one substitute sensor from a first sensor group of based on an identified discrepancy between the sensor output data and to execute a remedial measure associated with a safety mode of the exoskeleton for safe operation of the exoskeleton.

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.

A detection system and detection method for the sensors of a robot. A detection system installs three sensors at the motor side and power output terminal of the robot. A detection unit detects the normal or abnormal state of three sensors to index the abnormal sensor for maintenance, and two normal sensors are selected for keeping the robot safety operation without stop.

An estimation system includes an estimator estimating a state of a controlled object on the basis of a plurality of pieces of sensor information representing a state in a periphery of sensors, detected by a plurality of the sensors, and a model regarding the controlled object controlled by the estimation system, and a controller generating a control command for operating the controlled object such that the controlled object acts toward a predefined control target on the basis of the estimated result.

A sensor device using verification includes a sensor component and a verification component. The sensor component is configured to generate first data and second data. The verification component is configured to analyze the first data and the second data and generate verification data based on the first data and the second data.

A sensor device using verification includes a sensor component and a verification component. The sensor component is configured to generate first data and second data. The verification component is configured to analyze the first data and the second data and generate verification data based on the first data and the second data.

A method for monitoring a primary variable is carried out in a device having access to a set of sensors. The method includes the steps of receiving, from a network service, a series of forecasted values for the primary variable, each forecasted value being associated with one of a series of future time points; for at least one of the future time points, predicting a value for the primary variable using data of at least one secondary variable captured by a subset of the set of sensors, comparing the predicted value to the forecasted value associated with the future time point, and switching to a different subset of the set of sensors, if the predicted value deviates from the forecasted value with more than a specified threshold value.