A virtual teaching system includes a semi-autonomous device to perform a task such as cleaning a target environment. The semi-autonomous device includes one or more sensors configured to record environmental data from the target environment that can be used to construct a virtual environment. The semi-autonomous device is operably coupled to an analysis system. The analysis system includes a processor to perform multiple functions, such as constructing the virtual environment from the recorded environmental data and supporting operation of a user interface. The user interface can be operably coupled to the processor, allowing a human operator to teach a virtual device in the virtual environment to perform an action sequence. Once the virtual device has been taught an action sequence in the virtual environment, the analysis system can transfer the recorded action sequence to the semi-autonomous device for use in the target environment.

A robot management system (RMS) includes a plurality of service robots deployed within an operations venue that includes a plurality of gaming devices, an operator terminal presenting a graphical user interface (GUI) to an operator, and a robot management system server (RMS server) configured in networked communication with the plurality of service robots. The RMS server is configured to: identify location data for the service robots; create an interactive overlay map of the operations venue that includes a static map of the operations venue, overlay data showing the location data of the plurality of service robots over the static map, and an interactive icon for each service robot of the plurality of service robots; display, via the GUI, the overlay map; receive a first input indicating a selection of a first interactive icon associated with a first service robot; and display current status information associated with the first service robot.

An example system includes a plurality of processor modules. Each of the plurality of processor modules is communicatively couplable to an autonomous system of a plurality of autonomous systems. Each of the processor modules includes an autonomous software defined network (A-SDN) data-plane communications controller. The system further includes a portable network controller including an A-SDN control-plane communications controller.

A system includes one or more processors that are configured to receive data from one or more sensors, to determine whether one or more characteristics of a driver or an occupant indicate driving control of a vehicle should transfer from the driver based on the data, and to enable a remote operator to control operation of the vehicle in response to determining that the driving control should transfer from the driver.

The systems and methods disclosed herein are configured to provide a mobile device for remotely controlling the movement of a vehicle and trailer. The mobile device provides a user engagement input for display and use of a control input. The control input may be used to generate a signal for controlling the movement of the vehicle and trailer.

In some examples, a computing apparatus may include one or more non-transitory computer-readable storage media and program instructions stored on the one or more computer-readable storage media that, when executed by one or more processors, direct the computing apparatus to perform various steps. For example, the program instructions may continually present a graphical user interface (GUI) at the computing apparatus including a display of a current view of the physical environment from a perspective of an aerial vehicle. The program instructions may detect user interactions with the GUI while the aerial vehicle is in flight. The user interactions may include instructions directing the aerial vehicle to maneuver within the physical environment and configure parameters for scanning a three-dimensional (3D) scan volume. The program instruction may then transmit, to the aerial vehicle, data encoding the instructions for performing a 3D scan of the 3D scan volume.

A robot cleaner includes: a communication interface configured to operate in an AP mode in which the communication interface outputs a wireless signal corresponding to a wireless signal output value of an AP device; and a processor configured to: control to sequentially move the robot cleaner to measurement locations, output the wireless signal output through the AP mode of communication interface and, with respect to the wireless signal, obtain signal strength information related to a connection strength between the robot cleaner and electronic devices disposed in the space, respectively, at the measurement locations; and based on the signal strength information, identify a measurement location at which a signal strength of the electronic devices is a threshold value or more, as a recommended AP location of the AP device, among the measurement locations.

Apparatus and methods for controlling a path of an autonomous mobile device based upon defining a series of origination positions and destination positions, each destination position correlating with position coordinates. A current position of an autonomous vehicle is determined via location automation such as real time communication systems and an approved pathway is generated to guide the autonomous vehicle. The position coordinates may be a set of values that accurately define a position in two dimensional 2D or three-dimensional (3D) space. Position coordinates may include cartesian coordinates.

A location processing device includes a selection member configured to select multiple flight vehicles to form a flight group. The location processing device also includes a determination member configured to determine first relative location information of the multiple flight vehicles of the flight group while instructing an operation device configured to control the multiple flight vehicles to perform operations.

A system and method of navigating a vehicle, the vehicle comprising a scanning device and a self-contained navigation system (SCNS) operatively connected to a computer, the method comprising: operating the scanning device for repeatedly executing a scanning operation, each operation includes scanning an area surrounding the vehicle, thereby generating respective scanning output data; operating the computer for generating, based on the scanning output data, a relative map representing at least a part of the area, the map having known dimensions and being relative to a position of the vehicle, wherein the map comprises cells, each cell classified to a class from at least two classes, comprising traversable and non-traversable, and characterized by dimensions equal or larger than an accumulated drift value of the SCNS; wherein non-traversable cells correspond to identified obstacles; receiving SCNS data and updating a position of the vehicle relative to the cells based on the SCNS data.