A sensor device for process variable determination in an industrial environment, comprising a sensor base and a first expansion module. The sensor base includes circuitry that determines the process variable, a first mechanical interface for mechanically accommodating a first expansion module and a first communication interface to the first expansion module for transmitting measurement and/or control data. In this case, the first expansion module has a second mechanical interface to the sensor base, a third mechanical interface for mechanically accommodating a second expansion module, a second communication interface to the sensor base for transmitting measurement and/or control data, and a third communication interface to the second expansion module for transmitting measurement and/or control data.

The present invention provides a mechanism for causing a safety controller to suitably display various pieces of information from a safety input device. A safety controller acquires a compatible port that connects at least one safety input device, and a safety input signal from the at least one safety input device connected via the compatible port and state information on the safety input device. Further, the safety controller 3 includes the MCU 23 that generates, in accordance with the safety program, a safety output signal based on the safety input signal acquired, and the display device 5a that displays, based on the state information acquired, a state of the safety input device from which the state information is acquired.

Control systems for industrial machinery (e.g., robots) or other devices such as medical devices utilize a safety processor (SP) designed for integration into safety applications and computational components that are not necessarily safety-rated. The SP monitors performance of the non-safety computational components, including latency checks and verification of identical outputs. One or more sensors send data to the non-safety computational components for sophisticated processing and analysis that the SP cannot not perform, but the results of this processing are sent to the SP, which then generates safety-rated signals to the machinery or device being controlled by the SP. As a result, the system may qualify for a safety rating despite the ability to perform complex operations beyond the scope of safety-rated components.

Systems and methods for determining safe and unsafe zones in a workspace—where safe actions are calculated in real time based on all relevant objects (e.g., some observed by sensors and others computationally generated based on analysis of the sensed workspace) and on the current state of the machinery (e.g., a robot) in the workspace—may utilize a variety of workspace-monitoring approaches as well as dynamic modeling of the robot geometry. The future trajectory of the robot(s) and/or the human(s) may be forecast using, e.g., a model of human movement and other forms of control. Modeling and forecasting of the robot may, in some embodiments, make use of data provided by the robot controller that may or may not include safety guarantees.

A system, in particular a manufacturing system, the system including machines, especially stationary and mobile machines, and at least one vehicle and a control, the vehicle having at least one sensor for ascertaining the relative position of a person, in particular a sensor for ascertaining the distance between the vehicle and the person, and for ascertaining the angle between the driving direction of the vehicle and the connecting line between the person and the vehicle, the vehicle having a position acquisition means for sensing the position of the vehicle, in particular a GPS system or a triangulation system for ascertaining the position of the vehicle, the control including a means for ascertaining the safety zone around the person and the machines situated therein, a data transmission channel being provided between the control and the machines.

A functional safety system performs safety analysis on three-dimensional point cloud data measured by a time-of-flight (TOF) sensor that monitors a hazardous industrial area that includes an automation system. To reduce the amount of point cloud data to be analyzed for hazardous conditions, the safety system executes a real-time emulation of the automation system using a digital twin and live controller data read from an industrial controller that monitors and controls the automation system. The safety system generates simulated, or shadow, point cloud data based on the emulation and subtracts this simulate point cloud data from the measured point cloud data received from the TOF sensor. This removes portions of the point cloud data corresponding to known or expected elements within the monitored area. Any remaining entities detected in the reduced point cloud data can be further analyzed for safety concerns.

An interactive autonomous robot is configured for deployment within a social environment. The disclosed robot includes a show subsystem configured to select between different in-character behaviors depending on robot status, thereby allowing the robot to appear in-character despite technical failures. The disclosed robot further includes a safety subsystem configured to intervene with in-character behavior when necessary to enforce safety protocols. The disclosed robot is also configured with a social subsystem that interprets social behaviors of humans and then initiates specific behavior sequences in response.

A detection and tracking system and method using a camera unit on a robot, or alternatively a camera mounted inside the pool overlooking the bottom of the pool, for safety monitoring for use in and around water-related environments. The robot is able to propel itself and move throughout the body of water, both on the surface and underwater, and the camera unit functions both on the surface and underwater. The robot optimizes the cleaning cycle of the body of water utilizing deep learning techniques. The robot has localization sensors and software that allow the robot to be aware of the robot's position in the pool. The camera is able to send its video feed live over the internet, the processing is performed in the cloud, and the robot sends and receives data from the cloud. The processing utilizes deep learning algorithms, including artificial neural networks, that perform video analytics.

Systems, methods, and apparatus for a detector and reflector for automation cell safety and identification are disclosed. In one or more embodiments, a method for machinery safety comprises transmitting, by an active transponder, at least one interrogation signal. The method further comprises receiving, by at least one passive transponder located on a user or on an item, the interrogation signal(s). Also, the method comprises generating, by a non-linear device of the passive transponder(s) in response to the interrogation signal(s), at least one response signal. In addition, the method comprises receiving, by the active transponder, the response signal(s). Additionally, the method comprises determining, by at least one processor, a location of the passive transponder(s) based on the response signal(s). Further, the method comprises determining, by the processor(s), whether the passive transponder(s) is located within a threshold distance away from machinery by using the location of the passive transponder(s).

Control systems for industrial machinery (e.g., robots) or other devices such as medical devices utilize a safety processor (SP) designed for integration into safety applications and computational components that are not necessarily safety-rated. The SP monitors performance of the non-safety computational components, including latency checks and verification of identical outputs. One or more sensors send data to the non-safety computational components for sophisticated processing and analysis that the SP cannot not perform, but the results of this processing are sent to the SP, which then generates safety-rated signals to the machinery or device being controlled by the SP. As a result, the system may qualify for a safety rating despite the ability to perform complex operations beyond the scope of safety-rated components.