Abstract: Systems, methods, computing platforms, and storage media for administering a distributed edge computing system utilizing an adaptive edge engine based on a finite state machine behavioral model are disclosed. Exemplary implementations may: select a first workload from one or more workloads; access, for the selected workload, one or more location optimization strategies from a plurality of location optimization strategies; and optimize an objective function across a portion of the one or more endpoints; select one or more endpoints; deploy the workload on at least one selected endpoint; monitor the health of the endpoint-workload deployment; and direct network traffic to the appropriate endpoint.

Abstract: Example embodiments relate to identifying defects in optical detector systems based on extent of stray light. An example embodiment includes a method. The method includes capturing, using an optical detector system, an image of a scene that includes a bright object. The method also includes determining a location of the bright object within the image. Further, the method includes determining, based on the location of the bright object within the image, an extent of stray light from the bright object that is represented in the image. In addition, the method includes determining, by comparing the extent of stray light from the bright object that is represented in the image to a predetermined threshold extent of stray light, whether one or more defects are present within the optical detector system. The predetermined threshold extent of stray light corresponds to an expected extent of stray light.

Abstract: An example method includes capturing, by an image capture device, a first image having a plurality of pixels. Each pixel includes a plurality of channels, and the first image is captured in accordance with first exposure parameters. The method includes determining, by a controller of the image capture device, average pixel intensities for each of the plurality of channels. The method includes determining, by the controller, a weighted average of pixel intensities using the average pixel intensities. The method includes setting, by the controller, a gain that is proportional to a ratio of a desired average pixel intensity relative to the weighted average of pixel intensities. The method includes setting, by the controller, second exposure parameters for a second image based on the gain. The method includes capturing, by the image capture device, the second image in accordance with the second exposure parameters.

Abstract: The present disclosure relates to systems, vehicles, and methods that include adjusting a position of an image sensor with respect to a lens assembly. An example optical system includes a lens assembly having at least one lens. The at least one lens defines an optical axis, a focal distance, and a focal plane. The optical system also includes a lens holder coupled to the lens assembly and a substrate having a first surface. The optical system additionally includes an image sensor attached to the first surface of the substrate. Furthermore, the optical system includes an active compensation system having a piezoelectric structure coupled between the lens holder and the first surface of the substrate. The active compensation system is configured to maintain the image sensor at the focal plane over a predetermined temperature range.

Abstract: An example method includes capturing, by an image capture device, a first image having a plurality of pixels. Each pixel includes a plurality of channels, and the first image is captured in accordance with first exposure parameters. The method includes determining, by a controller of the image capture device, average pixel intensities for each of the plurality of channels. The method includes determining, by the controller, a weighted average of pixel intensities using the average pixel intensities. The method includes setting, by the controller, a gain that is proportional to a ratio of a desired average pixel intensity relative to the weighted average of pixel intensities. The method includes setting, by the controller, second exposure parameters for a second image based on the gain. The method includes capturing, by the image capture device, the second image in accordance with the second exposure parameters.

Abstract: An example method includes capturing, by an image capture device, a first image having a plurality of pixels. Each pixel includes a plurality of channels, and the first image is captured in accordance with first exposure parameters. The method includes determining, by a controller of the image capture device, average pixel intensities for each of the plurality of channels. The method includes determining, by the controller, a weighted average of pixel intensities using the average pixel intensities. The method includes setting, by the controller, a gain that is proportional to a ratio of a desired average pixel intensity relative to the weighted average of pixel intensities. The method includes setting, by the controller, second exposure parameters for a second image based on the gain. The method includes capturing, by the image capture device, the second image in accordance with the second exposure parameters.

Abstract: Example embodiments relate to identifying defects in optical detector systems based on extent of stray light. An example embodiment includes a method. The method includes capturing, using an optical detector system, an image of a scene that includes a bright object. The method also includes determining a location of the bright object within the image. Further, the method includes determining, based on the location of the bright object within the image, an extent of stray light from the bright object that is represented in the image. In addition, the method includes determining, by comparing the extent of stray light from the bright object that is represented in the image to a predetermined threshold extent of stray light, whether one or more defects are present within the optical detector system. The predetermined threshold extent of stray light corresponds to an expected extent of stray light.

Abstract: Example embodiments relate to identifying defects in optical detector systems based on extent of stray light. An example embodiment includes a method. The method includes capturing, using an optical detector system, an image of a scene that includes a bright object. The method also includes determining a location of the bright object within the image. Further, the method includes determining, based on the location of the bright object within the image, an extent of stray light from the bright object that is represented in the image. In addition, the method includes determining, by comparing the extent of stray light from the bright object that is represented in the image to a predetermined threshold extent of stray light, whether one or more defects are present within the optical detector system. The predetermined threshold extent of stray light corresponds to an expected extent of stray light.

Abstract: Example embodiments relate to identifying defects in optical detector systems based on extent of stray light. An example embodiment includes a method. The method includes capturing, using an optical detector system, an image of a scene that includes a bright object. The method also includes determining a location of the bright object within the image. Further, the method includes determining, based on the location of the bright object within the image, an extent of stray light from the bright object that is represented in the image. In addition, the method includes determining, by comparing the extent of stray light from the bright object that is represented in the image to a predetermined threshold extent of stray light, whether one or more defects are present within the optical detector system. The predetermined threshold extent of stray light corresponds to an expected extent of stray light.