Aspects of the subject disclosure include a pressure-sensing device consisting of a housing including a membrane and one or more piezoresistive elements disposed on the membrane to sense a displacement due to a deflection of the membrane. A first set of electrodes is disposed over the membrane, and a second set of electrodes is disposed on a permeable port of the device at a distance from the membrane. The first and second sets of electrodes form an electrostatic actuator to exert a repulsive force onto the membrane to reduce the deflection of the membrane.

Example methods and systems for calibrating sensors using road map data are provided. An autonomous vehicle may use various vehicle sensors to assist in navigation. Within examples, the autonomous vehicle may calibrate vehicle sensors through performing a comparison or analysis between information about the environment received by sensors with similar information provided by map data (e.g., a road map). The autonomous vehicle may compare object locations as provided by the sensors and as shown by map data. Based on the comparison, the autonomous vehicle may adjust various sensors to accurately reflect the information as provided by the road map. In some instances, the autonomous vehicle may adjust the position, height, orientation, direction-of-focus, scaling, or other parameters of a sensor based on the information provided by a road map.

A flash detection device comprises at least a first and a second sensor module, wherein each of the sensor modules comprises at least a photodiode for detecting an irradiance emitted by a source, and the first sensor module comprises at least an angular efficiency attenuator configured for attenuating the irradiance received by the photodiode according to a predetermined angular efficiency profile, wherein the at least first and second sensor modules are configured for collecting light from substantially the same field of view, and the angular efficiency attenuator of the first sensor module causes the first and second sensor modules to have complementary predetermined angular efficiency profiles, so that, for angles of view within a common field of view of the first and second sensor modules, a combination of irradiance measurements of the first and second sensor modules enables to derive an irradiance source angle of the source.

A flash detection device comprises at least a first and a second sensor module, wherein each of the sensor modules comprises at least a photodiode for detecting an irradiance emitted by a source, and the first sensor module comprises at least an angular efficiency attenuator configured for attenuating the irradiance received by the photodiode according to a predetermined angular efficiency profile, wherein the at least first and second sensor modules are configured for collecting light from substantially the same field of view, and the angular efficiency attenuator of the first sensor module causes the first and second sensor modules to have complementary predetermined angular efficiency profiles, so that, for angles of view within a common field of view of the first and second sensor modules, a combination of irradiance measurements of the first and second sensor modules enables to derive an irradiance source angle of the source.

A solar tracker system including a tracker apparatus including a plurality of solar modules, each of the solar modules being spatially configured to face in a normal manner in an on sun position in an incident direction of electromagnetic radiation derived from the sun, wherein the solar modules include a plurality of PV strings, and a tracker controller. The tracker controller includes a processor, a memory, a power supply configured to provide power to the tracker controller, a plurality of power inputs configured to receive a plurality of currents from the plurality of PV strings, a current sensing unit configured to individually monitor the plurality of currents, a DC-DC power converter configured to receive the plurality of power inputs powered from the plurality of PV strings to supply power to the power supply, and a motor controller, wherein the tracker controller is configured to track the sun position.

A solar tracker system including a tracker apparatus including a plurality of solar modules, each of the solar modules being spatially configured to face in a normal manner in an on sun position in an incident direction of electromagnetic radiation derived from the sun, wherein the solar modules include a plurality of PV strings, and a tracker controller. The tracker controller includes a processor, a memory, a power supply configured to provide power to the tracker controller, a plurality of power inputs configured to receive a plurality of currents from the plurality of PV strings, a current sensing unit configured to individually monitor the plurality of currents, a DC-DC power converter configured to receive the plurality of power inputs powered from the plurality of PV strings to supply power to the power supply, and a motor controller, wherein the tracker controller is configured to track the sun position.

An apparatus includes a dynamic vision sensor (DVS) configured to output an asynchronous stream of sensor event data, a CMOS image sensor configured to output frames of image data, an inertial measurement unit (IMU), a processor and a memory. The memory contains instructions, which when executed by the processor, cause the apparatus to generate a semantic segmentation of a time-stamped frame, which is based on one or more of an output of the CMOS image sensor, or a synthesized event frame based on an output from the DVS and an output from the IMU over a time interval. The semantic segmentation includes a semantic label associated with a region of the time-stamped frame. When executed, the instructions further cause the apparatus to determine, based on the semantic segmentation, a simplified object representation in a coordinate space, and update a stable semantic map based on the simplified object representation.

An apparatus includes a dynamic vision sensor (DVS) configured to output an asynchronous stream of sensor event data, and a complementary metal-oxide-semiconductor (CMOS) image sensor configured to output frames of image data. The apparatus further includes a hybrid feature handler configured to receive, as an input, one or more of a DVS output or a CMOS image sensor output, and provide tracked features to a visual-inertial simultaneous location and mapping (SLAM) pipeline performing inside-out device tracking, and a sensor scheduler configured to switch off the CMOS image sensor based on a current value of one or more CMOS control factors.

A system and method for rank estimation of electromagnetic emitters is provided. One aspect of the disclosure provides creating a graph of angles of arrival (AoAs) versus range and using a polynomial curve fit against the graph to determine a rank estimation of electromagnetic emitters. Another aspect of the disclosure provides using a search over parameters of the multiple polynomial curve fits, for each hypothesized rank, to optimize the rank estimation results. This search may be a greedy search to improve speed of convergence. Another aspect of the disclosure provides a metric score to select the highest probability rank (number of emitters) based on the agreement between the multiple polynomial curve fits and residual AoA errors.

A system and method for rank estimation of electromagnetic emitters is provided. One aspect of the disclosure provides creating a graph of angles of arrival (AoAs) versus range and using a polynomial curve fit against the graph to determine a rank estimation of electromagnetic emitters. Another aspect of the disclosure provides using a search over parameters of the multiple polynomial curve fits, for each hypothesized rank, to optimize the rank estimation results. This search may be a greedy search to improve speed of convergence. Another aspect of the disclosure provides a metric score to select the highest probability rank (number of emitters) based on the agreement between the multiple polynomial curve fits and residual AoA errors.