Systems, methods, and related technologies are disclosed for multi-device robot control. In one implementation, input(s) are received and provided to a personal assistant or another application or service. In response, command(s) directed to an external device are received, e.g., from the personal assistant. Based on the command(s), a robot is maneuvered in relation to a location associated with the external device. Transmission of instruction(s) from the robot to the external device is initiated.

Automation security in a networked-based industrial controller environment is implemented. Various components, systems and methodologies are provided to facilitate varying levels of automation security in accordance with security analysis tools, security validation tools and/or security learning systems. The security analysis tool receives abstract factory models or descriptions for input and generates an output that can include security guidelines, components, topologies, procedures, rules, policies, and the like for deployment in an automation security network. The validation tools are operative in the automation security network, wherein the tools perform security checking and/or auditing functions, for example, to determine if security components are in place and/or in suitable working order. The security learning system monitors/learns network traffic patterns during a learning phase, fires alarms or events based upon detected deviations from the learned patterns, and/or causes other automated actions to occur.

A surveillance system may comprise one or more computing devices and one or more robotic surveillance devices. The one or more computing devices may be configured to obtain video data captured by one or more cameras. The one or more computing devices may analyze the video data to determine whether there is any trigger event. In response to determining that there is a trigger event, the one or more computing device may determine an optimal robotic surveillance device among the one or more robotic surveillance devices based on the trigger event and provide an instruction to the optimal robotic surveillance device. The optimal robotic surveillance device may be configured to perform a responding action in response to receiving the instruction.

Operation of an industrial asset control system may be simulated or monitored under various operating conditions to generate a set of operating results. Subsets of the operating results may be used to calculate a normalization function for each of a plurality of operating conditions. Streams of monitoring node signal values over time may be received that represent a current operation of the industrial asset control system. A threat detection platform may then dynamically calculate normalized monitoring node signal values based at least in part on a normalization function in an operating mode database. For each stream of normalized monitoring node signal values, a current monitoring node feature vector may be generated and compared with a corresponding decision boundary for that monitoring node, the decision boundary separating normal and abnormal states for that monitoring node. A threat alert signal may then be automatically transmitted based on results of those comparisons.

Industrial controller modules are configured with security components that implement backplane-level security protocols, thereby preventing installation of unauthorized modular devices on the backplane of an industrial controller. When a modular device is installed in the controller's chassis and interface with the backplane, security components in the processor module or other supervisory module initiates exchange of authentication data with the modular device via the backplane. The authentication data can comprise one or more security challenges to which the modular device must respond correctly before the modular device is permitted to operate on the backplane. These backplane-level security protocols can prevent installation of rogue modules that may be used to collect proprietary control data or interfere with control processes.

A surveillance system may comprise one or more computing devices and one or more robotic surveillance devices. The one or more computing devices may be configured to obtain video data captured by one or more cameras. The one or more computing devices may analyze the video data to determine whether there is any trigger event. In response to determining that there is a trigger event, the one or more computing device may determine an optimal robotic surveillance device among the one or more robotic surveillance devices based on the trigger event and provide an instruction to the optimal robotic surveillance device. The optimal robotic surveillance device may be configured to perform a responding action in response to receiving the instruction.

Systems, methods, and related technologies are disclosed for multi-device robot control. In one implementation, input(s) are received and provided to a personal assistant or another application or service. In response, command(s) directed to an external device are received, e.g., from the personal assistant. Based on the command(s), a robot is maneuvered in relation to a location associated with the external device. Transmission of instruction(s) from the robot to the external device is initiated.

Technologies for managing safety at an industrial site include a method. The method includes receiving, by a compute device in a cloud data center, condition data indicative of a sensed or determined condition at the industrial site. The condition data was produced at least in part by an edge device at the industrial site. The method also includes analyzing, by the compute device and with a model that associates conditions with corresponding safety statuses, the received condition data to determine a corresponding safety status associated with the industrial site. Further, the method includes determining, by the compute device and as a function of the determined safety status, whether a responsive action is to be performed at the industrial site. Additionally, the method includes sending, by the compute device, to the edge device at the industrial site and in response to a determination that a responsive action is to be performed at the industrial site, responsive data indicative of the responsive action to be performed.

Technologies for managing safety at an industrial site include a method. The method includes receiving, by a compute device in a cloud data center, condition data indicative of a sensed or determined condition at the industrial site. The condition data was produced at least in part by an edge device at the industrial site. The method also includes analyzing, by the compute device and with a model that associates conditions with corresponding safety statuses, the received condition data to determine a corresponding safety status associated with the industrial site. Further, the method includes determining, by the compute device and as a function of the determined safety status, whether a responsive action is to be performed at the industrial site. Additionally, the method includes sending, by the compute device, to the edge device at the industrial site and in response to a determination that a responsive action is to be performed at the industrial site, responsive data indicative of the responsive action to be performed.

A mobile robot is configured for operation in a commercial or industrial setting, such as an office building or retail store. The robot can patrol one or more routes within a building, and can detect violations of security policies by objects, building infrastructure and security systems, or individuals. In response to the detected violations, the robot can perform one or more security operations. The robot can include a removable fabric panel, enabling sensors within the robot body to capture signals that propagate through the fabric. In addition, the robot can scan RFID tags of objects within an area, for instance coupled to store inventory. Likewise, the robot can generate or update one or more semantic maps for use by the robot in navigating an area and for measuring compliance with security policies.