A controller for virtual armored vehicles comprising fixed base with a pivot, a housing associated with the fixed base by a rotary mechanism located on the pivot of the fixed base and allowing the housing to rotate relative to the fixed base, right and left handles connected by a common shaft passing through the housing and having its own independent rotary mechanism permitting inclination of the handles, the rotary mechanism of the housing and the independent rotary mechanism of the shaft are provided with mechanisms for returning the housing and the shaft to the central positions in the absence of pressure from the user, rotation sensors of the housing and the common shaft with the handles, microcontroller functionally connected to the rotation sensors, means for communication of the microcontroller to a host device, and a power source.

A training apparatus for fast-rope training includes a platform-supporting structure having one or more containers and at least one platform configured for use in fast-rope training. At least one attachment is provided for attaching a fast-rope. The platform-supporting structure is supportable by a surface. The at least one attachment is located higher than the platform and spaced laterally from the platform-supporting structure such that the at least one attachment overhangs the surface so a fast rope can hang from the at least one attachment, past the platform and toward the surface.

A communications training system is provided having a user interface, a computer-based simulator and a performance measurement database. The user interface is configured to receive a speech communication input from the user based on a training content and the computer-based simulator is configured to transform the speech communication to a text data whereby the text data can be aligned to performance measurement database values to determine a performance measure of the speech communication. The format of the text data and the performance measurement database values enable the speech communication to be aligned with predefined performance measurement database values representing expected speech communications for that training content.

Disclosed herein are embodiments for managing a task including one or more skills. A server stores a virtual environment, software agents configured to collect data generated when a user interacts with the virtual environment to perform the task, and a predictive machine learning model. The server generates virtual entities during the performance of the task, and executes the predictive machine learning model to configure the virtual entities based upon data generated when the user interacts with the virtual environment. The server generates the virtual environment and the virtual entities configured for interaction with the user during display by the client device, and receives the data collected by the software agents. The system displays a user interface at the client device to indicate a measurement of each of the skills during performance of the task. The server trains the predictive machine learning model using this measurement of skills during task performance.

A system, includes a memory in communication with a processor, the memory storing instructions that when executed by the processor cause the processor to receive a first location of a real vehicle, receive an updated location of the real vehicle, compute, utilizing at least the first location and the updated location, a future location of the real vehicle at a predetermined time in the future and output data to a display device adapted to display to a user of the display device at the predetermined time a mixed reality representation of an environment surrounding the real vehicle as viewed from the future location.

Examples are disclosed that relate to methods and systems for classifying the possession or control of a target asset. One example provides a system comprising one or more computing devices having processors and associated memories storing instructions executable by the processors. The instructions are executable to conduct a simulation or observation of an in-field event comprising a plurality of actors controlling a plurality of in-field assets. The system is further configured to monitor telemetry data from each of the in-field assets. In addition, tagging data is received from an in-field asset under the control of a member of the friendly group. A training data set is generated including the telemetry data and the tagging data, and an artificial intelligence model is trained to predict whether a run-time target asset is in the possession or control of the friendly or the unfriendly actor, or lost, based on run-time telemetry data.

A virtual reality training system according to an aspect of the invention may include a floor system having a base of a particular length and width, an object member configured to be detachably installed on the floor system, an input unit configured to assign a first position, which corresponds to the position of an object within a virtual reality space having a length and width smaller than or equal to the length and width of the base of the floor system, and a mapping unit configured to compute and output a second position, for installing the object member on the floor system, computed as a position on the floor system corresponding to the first position within the virtual reality space.

A lightweight training aid is disclosed including selectively positioned posable appendages for use in various training exercises. The training aid may be formed of one or more separable and distinct portions including a head module, a torso module and a leg module, and combinations thereof. The head module and/or leg module may be releasably coupled to the torso module by interchangeable mounting arrangements. Appendages of the training aid may be posable, at least within a set range of motion, within any of a potentially infinite number of orientations. Methods of using such a training aid also are disclosed.

A map generation device (10) generates linearization information expressing at least one or the other of a marking line of a roadway and a road shoulder edge based on measurement information of a periphery of the roadway. The measurement information is obtained by a measurement device. The map generation device (10) calculates an evaluation value expressing a reliability degree of partial information, for each partial information constituting the linearization information. A map editing device (20) displays the partial information in different modes according to the evaluation value, thereby displaying the linearization information. The map editing device (20) accepts input of editing information for the displayed linearization information.

A simulation system may comprise a headset and an equipment. A wireless communication interface of the headset may receive position information from the equipment. The headset may detect a passively-instrumented object represented in a captured image. The headset may detect a wearable device coupled to the passively-instrumented object. The headset may determine position information for the passively-instrumented object. The headset may present an image of virtual equipment corresponding to the equipment in accordance with the position information from the equipment and the position information detected for the passively-instrumented object.