Abstract: In one embodiment, a method includes causing a radar antenna to transmit a plurality of radar signals at a plurality of sweep angles and, for each of one or more the radar signals reflected back to the radar antenna, calculating a radial-velocity component. The method also includes identifying one of the radial-velocity components, identifying one of the plurality of sweep angles corresponding to the identified radial-velocity components, and calculating an offset of an electrical boresight of the radar antenna based at least in part on the identified sweep angle corresponding to the identified radial-velocity component.

Abstract: Techniques are disclosed for systems and methods to provision a mobile mesh network. A mobile mesh network provisioning system includes a wireless communications module configured to be physically coupled to a fleet vehicle and to form at least a part of a mobile mesh network including a plurality of mobile nodes corresponding to a respective plurality of fleet vehicles, and a logic device configured to communicate with the wireless communications module. The logic device is configured to determine a data route through at least a portion of the mobile mesh network based, at least in part, on a target data destination and a mobile node participation variability associated with the mobile mesh network, and to transmit fleet data associated with the fleet vehicle along the determined data route.

Abstract: In one embodiment, an apparatus includes a first stage and a second stage. The first stage may include a gated-light valve (GLV) that is operable to receive a light beam from a light source and direct the light beam along one dimension to discrete input locations of a second stage. The second stage may be operable to receive the light beam from the first stage at the discrete input locations along the one dimension and direct the light beam through two dimensions to discrete output locations of the second stage to scan a three-dimensional space.

Abstract: In one embodiment, a method includes determining an operational status of a vehicle including a radar antenna. The operational status is related to autonomous-driving operations of the vehicle in an environment. The method includes determining an expected amount of signaling resources associated with the radar antenna to be utilized by the vehicle while the vehicle performs the autonomous-driving operations, based at least on the operational status of the vehicle and the environment. The method includes determining to switch one or more of the signaling resources associated with the radar antenna from a first mode to a second mode based on the expected amount of signaling resources to be utilized by the radar antenna while the vehicle performs the autonomous-driving operations. The method includes causing the one or more of the signaling resources associated with the radar antenna to switch from the first mode to the second mode.

Abstract: In one embodiment, a method includes, by a computing system of a vehicle, providing one or more instructions configured to cause a first radar antenna to broadcast a modulated radar chirp signal. The modulated radar chirp signal may include data. The method includes receiving a first return signal that corresponds to the modulated radar chirp signal reflected off of an object in an environment. The method includes calculating a location for the object using the first return signal. The method includes receiving, from a second radar antenna, a second return signal indicating that the modulated radar chirp signal was received by the second radar antenna.

Abstract: In one embodiment, a method includes receiving sensor data from one or more sensors of each of one or more vehicles, processing a combination of the sensor data to generate an assessment of an area surrounding the one or more vehicles based on one or more points-of-view of the area, the one or more points-of-view of the area generated based on synchronizing the combination of the sensor data, and detecting an occurrence of an event based on the assessment of the area. The method further includes identifying one or more instructions corresponding to the event, the instructions associated with a particular vehicle and sending one or more executable instructions based on the instructions to the particular vehicle.

Abstract: In one embodiment, a method includes accessing an operational status of a vehicle that is coupled to a radar antenna array, accessing sensor data that includes a count of and a location of a plurality of objects within a vicinity of the vehicle, accessing signal strength data associated with one or more base station antennas located within the vicinity of the vehicle, and determining to switch at least some of a plurality of radar resources of the radar antenna array from an object detection mode to a data transfer mode. The determination is based on the operational status, the sensor data, or the signal strength data.

Abstract: In one embodiment, an apparatus includes a transmitter operable to transmit a first light beam from a light source. The apparatus also includes a receiver operable to receive a plurality of return light beams and direct the plurality of return light beams through a first beam splitter to an imaging sensor and a LiDAR sensor. The imaging sensor may be operable to process a first portion of the return light beams into image profile data, and the LiDAR sensor may be operable to process a second portion of the return light beams into depth profile data. In addition, the first and second portions of the return light beams may be received from a shared field of view.

Abstract: The disclosed computer-implemented method may include receiving sensor data associated with a mobile device associated with a vehicle, wherein the sensor data includes at least one of an angular velocity vector, a linear acceleration vector, and a rotational acceleration vector recorded over a period of time, determining an event signature based on the sensor data, and detecting a door closing event associated with the vehicle based at least in part on the event signature. Other methods, systems, and computer-readable media are disclosed.

Abstract: In one embodiment, a method includes accessing first image data generated by a first image sensor having a first filter array that has a first filter pattern. The first filter pattern includes a first filter type corresponding to a spectrum of interest and a second filter type. The method also includes accessing second image data generated by a second image sensor having a second filter array that has a second filter pattern different from the first filter pattern. The second filter pattern includes a number of second filter types, the number of second filter types and the number of first filter types have at least one filter type in common. The method also includes determining a correspondence between one or more first pixels of the first image data and one or more second pixels of the second image data.

Abstract: Systems, methods, and non-transitory computer-readable media can determine sensor data collected by a fleet of vehicles while navigating a geographic region. Information describing respective states of a plurality of personal mobility vehicles in the geographic region can be determined based at least in part on the sensor data. One or more operations for managing the personal mobility vehicles can be determined.

Abstract: In one embodiment, a method includes accessing first image data generated by a first image sensor having a first filter array that has a first filter pattern. The first filter pattern includes a number of first filter types. The method also includes accessing second image data generated by a second image sensor having a second filter array that has a second filter pattern different from the first filter pattern. The second filter pattern includes a number of second filter types, the number of second filter types and the number of first filter types have at least one filter type in common. The method also includes determining a correspondence between one or more first pixels of the first image data and one or more second pixels of the second image data based on a portion of the first image data associated with the filter type in common.

Abstract: In one embodiment, an apparatus includes a transmitter operable to transmit a first light beam from a light source. The apparatus also includes a receiver operable to receive a plurality of return light beams and direct the plurality of return light beams through a first beam splitter to an imaging sensor and a LiDAR sensor. The imaging sensor may be operable to process a first portion of the return light beams into image profile data, and the LiDAR sensor may be operable to process a second portion of the return light beams into depth profile data. In addition, the first and second portions of the return light beams may be received from a shared field of view.

Abstract: In one embodiment, a method includes accessing first image data generated by a first image sensor having a first filter array that has a first filter pattern. The first filter pattern includes a first filter type corresponding to a spectrum of interest and a second filter type. The method also includes accessing second image data generated by a second image sensor having a second filter array that has a second filter pattern different from the first filter pattern. The second filter pattern includes a number of second filter types, the number of second filter types and the number of first filter types have at least one filter type in common. The method also includes determining a correspondence between one or more first pixels of the first image data and one or more second pixels of the second image data.

Abstract: In one embodiment, a method includes accessing first image data generated by a first image sensor having a first filter array that has a first filter pattern. The first filter pattern includes a first filter type corresponding to a spectrum of interest and a second filter type. The method also includes accessing second image data generated by a second image sensor having a second filter array that has a second filter pattern different from the first filter pattern. The second filter pattern includes a number of second filter types, the number of second filter types and the number of first filter types have at least one filter type in common. The method also includes determining a correspondence between one or more first pixels of the first image data and one or more second pixels of the second image data.

Abstract: In one embodiment, a method includes accessing first image data generated by a first image sensor having a first filter array that has a first filter pattern. The first filter pattern includes a number of first filter types. The method also includes accessing second image data generated by a second image sensor having a second filter array that has a second filter pattern different from the first filter pattern. The second filter pattern includes a number of second filter types, the number of second filter types and the number of first filter types have at least one filter type in common. The method also includes determining a correspondence between one or more first pixels of the first image data and one or more second pixels of the second image data based on a portion of the first image data associated with the filter type in common.

Abstract: In one embodiment, a method includes receiving sensor data from one or more sensors of each of one or more vehicles, processing a combination of the sensor data to generate an assessment of an area surrounding the one or more vehicles based on one or more points-of-view of the area, the one or more points-of-view of the area generated based on synchronizing the combination of the sensor data, and detecting an occurrence of an event based on the assessment of the area. The method further includes identifying one or more instructions corresponding to the event, the instructions associated with a particular vehicle and sending one or more executable instructions based on the instructions to the particular vehicle.

Abstract: In one embodiment, a computing system accesses contextual data associated with a vehicle operated by a human driver. The contextual data is captured using one or more sensors associated with the vehicle. The system determines one or more predicted vehicle operations by processing the contextual data based at least on information associated with pre-recorded contextual data associated with a number of vehicles. The system detects one or more vehicle operations made by the human driver. The system determines that an event of interest is associated with the contextual data based on a comparison of the one or more vehicle operations made by the human driver and the one or more predicted vehicle operations. The system causes high-resolution contextual data associated with the event of interest to be stored.

Abstract: The disclosed computer-implemented method may include receiving sensor data associated with a mobile device associated with a vehicle, wherein the sensor data includes at least one of an angular velocity vector, a linear acceleration vector, and a rotational acceleration vector recorded over a period of time, determining an event signature based on the sensor data, and detecting a door closing event associated with the vehicle based at least in part on the event signature. Other methods, systems, and computer-readable media are disclosed.

Abstract: In one embodiment, a method includes causing a radar antenna to transmit a plurality of radar signals at a plurality of sweep angles and, for each of one or more the radar signals reflected back to the radar antenna, calculating a radial-velocity component. The method also includes identifying one of the radial-velocity components, identifying one of the plurality of sweep angles corresponding to the identified radial-velocity components, and calculating an offset of an electrical boresight of the radar antenna based at least in part on the identified sweep angle corresponding to the identified radial-velocity component.