An autonomous vehicle (AV) includes features that allows the AV to comply with applicable regulations and statues for performing safe driving operation. An example system for an AV includes a communications gateway device. The communications gateway device includes a plurality of modules each configured for different communication mediums or applications. In particular, the plurality of modules includes a first module for communicating with a remote computer. Via the first module, vehicle operational data is reported to the remote computer, and instructional data is received from the remote computer. The modules further include a second module for communicating with devices located within a vicinity external to the vehicle, and a third module configured to communicate with subsystems located within the vehicle. The example AV system includes a second communications gateway device that is configured to be redundant.

A system is for determining a position on a golf course. The system has a master unit and at least one slave unit. The master unit and the at least one slave unit are adapted to communicate through a telecommunications network. The master unit comprises a receiver for a satellite navigation system, the receiver being operable at a fixed position on the golf course. The master unit is configured to: obtain a position determined by the receiver; process the displacement between the obtained position and the fixed position; and make the processed displacement available to the at least one slave unit through the telecommunications network. A slave unit then makes use of the processed displacement to improve positions determined by itself.

A mobile cleaning robot that includes a drive system configured to navigate around an operational environment, a ranging device configured to communicate with other ranging devices of respective electronic devices that are in the operational environment, and processors in communication with the ranging device that are configured to receive a distance measurement from the respective electronic devices present in the operational environment, each distance measurement representing a distance between the mobile cleaning robot and a respective electronic device, tag each of the distance measurements with location data indicative of a spatial location of the mobile cleaning robot in the operational environment, determine spatial locations of each of the electronic devices in the operational environment, and populate a visual representation of the operating environment with visual indications of the electronic devices in the operating environment.

An unmanned aerial vehicle (UAV) carries a camera, sends data from the camera, and receives commands. The UAV is connected to a messaging platform. Pictures or video clips received from the UAV are selected and placed in messages broadcast by an account associated with the UAV. Video footage from the camera is live-streamed in a card-type message. Account holders of the messaging platform may control the UAV with commands embedded in messages and directed towards an account associated with the UAV. Controllable elements of the UAV include UAV location, camera orientation, camera subject, UAV-mounted lighting, a UAV-mounted display, a UAV-mounted projector, UAV-mounted speakers, and a detachable payload. UAV control may be determined through democratic means. Some UAV functionality may be triggered through aggregated engagements on the messaging platform. The UAV may include a display screen and/or a microphone to provide for telepresence or interview functionality.

Provided is a detection and classification system and method for small unmanned aircraft systems (sUAS). The system and method detect and classify multiple simultaneous heterogeneous RC transmitters/sUAS downlinks from the RF signature using Object Detection Deep Convolutional Neural Networks (DCNNs). The method further utilizes not only passive RF, but may also utilize Electro Optic/Infrared (EO/IR), radar and acoustic sensors as well, with a fusion of the individual sensor classifications. Detection and classification with Identification Friend or Foe (IFF) of individual sUAS in a swarm, multi-modal approach for high confidence classification, decision, and implementation on a low C-SWaP (cost, size, weight and power) NVIDIA Jetson TX2 embedded AI platform is achieved.

A teleoperations system may be used to selectively override conditions detected by an autonomous vehicle to enable the autonomous vehicle to effectively ignore detected conditions that are identified as false positives by the teleoperations system. Furthermore, a teleoperations system may be used to generate commands that an autonomous vehicle validates prior to executing to confirm that the commands do not violate any vehicle constraints for the autonomous vehicle. Still further, an autonomous vehicle may be capable of dynamically varying the video quality of one or more camera feeds that are streamed to a teleoperations system over a bandwidth-constrained wireless network based upon a current context of the autonomous vehicle.

A method is provided. An unmanned aerial vehicle (UAV) is operated. A position of the UAV is determined while in flight, and a nonce is generated. A Merkel root is generated based at least in part on a timestamp and the position of the UAV. A current block is calculated based at least in part on a previous block, the Merkel root, and the nonce, and the current block, the timestamp, the nonce, the prior block, and the position of the UAV are transmitted.

Operating conditions corresponding to a harvesting operation being performed by a mobile harvesting machine are detected along with a priority of a first performance pillar metric relative to a second performance pillar metric. An operating characteristic of the mobile harvesting machine is detected and a performance pillar metric value is identified for the first performance pillar metric based on the detected operating characteristic. A performance limitation corresponding to the first performance pillar metric is identified based on the detected operating conditions and an aggressiveness setting is detected that is indicative of an operating settings change threshold. It is then determined whether a settings change is to be performed based on the first performance pillar metric value, the priority of the first performance pillar metric, the first performance limitation and the settings change threshold and if the settings change is to be performed, a settings change actuator is controlled to execute the settings change.

A flight management system for unmanned aerial vehicles (UAVs), in which the UAV is equipped for cellular fourth generation (4G) flight control. The UAV carries on-board a 4G modem, an antenna connected to the modem for providing for downlink wireless RF. A computer is connected to the modem. A 4G infrastructure to support sending via uplink and receiving via downlink from and to the UAV. The infrastructure further includes 4G base stations capable of communicating with the UAV along its flight path. An antenna in the base station is capable of supporting a downlink to the UAV. A control centre accepts navigation related data from the uplink. In addition, the control centre further includes a connection to the 4G infrastructure for obtaining downlinked data. A computer for calculating location of the UAV using navigation data from the downlink.

A communication optimization system/method for mobile networks uses a server that generates waypoints based on a first communication network within a route to be travelled by an aerial vehicle, the aerial vehicle comprising a communication hub configured to communicate with at least one communication node, a communication hub controller configured control movement of a steerable antenna, and an aerial vehicle controller configured control movement of the aerial vehicle. The server then transmits the waypoints to the aerial vehicle controller; periodically monitors networks not connected to the communication hub; when a second communication network not connected to the communication hub satisfies a threshold, transmits causes the communication controller to steer the steerable antenna in a direction of the second communication network, further causing the communication hub to communicate and connect with the second communication network.