Abstract: Systems and methods for depth estimation in accordance with embodiments of the invention are illustrated. One embodiment includes a method for depth estimation. The method includes steps for identifying feature matches across several images, determining a set of homographies based on the identified feature matches, performing an uncalibrated rectification on a first image of the several images based on the set of determined homographies, and performing depth estimation based on at least the rectified image.

Abstract: Systems and techniques for polarization are illustrated. One embodiment includes a system for polarization imaging. The system includes a camera that is an autofocus sensor. The camera includes a main lens. An aperture plane of the main lens is overlaid with a multiplexed polarization filter, where the multiplexed polarization filter includes a plurality of sub-filters; and each sub-filter follows a distinct polarization angle. The camera includes a detector array, wherein the detector array includes a plurality of sensor pixels. The camera includes a microlens array including a plurality of microlenses overlaid over the detector array. The microlens array is placed at a focal plane of the main lens. Each microlens is: unfiltered; and configured to direct incident light to a distinct subset of the sensor pixels. The system further includes a memory storing image data and a processor configured to execute instructions to process the image data.

Abstract: Systems and methods for payload management systems are illustrated. One embodiment includes a delivery mechanism. A mechanical linkage in the delivery mechanism includes rocking bars mounted to: a chassis and a first cross bar The mechanical linkage includes linear actuators that include piston-type actuators configured to move at least one payload in and out of a compartment. One end of each linear actuator is mounted to an individual rocking bar. The mechanical linkage includes at least one grapple, wherein each grapple comprises a hook mounted to a claw; and is mounted to a second cross bar. The hook is configured to open and close around the at least one payload; and rotate around the claw. The delivery mechanism includes a control circuit configured to open, close, and rotate the hook using a grapple motor and/or an end-of-travel switch; and to move the linear actuators relative to the rocking bars.

Abstract: Systems and methods for the application of surface normal calculations are illustrated. One embodiment includes a system for navigation, including: a processor; and instructions stored in a memory that when executed by the processor direct the processor. The processor obtains a set of sensor data, wherein sensor data includes a plurality of polarized images. The processor retrieves at least one navigation query; and a plurality of key-value pairs based on the polarized images. The processor inputs the at least one navigation query and the plurality of key-value pairs into a Cross-Attention Transformer that provides a set of weighted sums, wherein each weighted sum corresponds to: a certain key-value pair from the plurality of key-value pairs; and a certain sensor. The processor updates a model based on the set of weighted sums. The processor navigates the system within a 3D environment according, at least in part, to the model.

Abstract: Systems and techniques performing autonomous navigation are illustrated. One embodiment includes a method for navigation. The method inputs a set of sensor data obtained from a plurality of sensors into at least one convolutional neural network (CNN). The at least one CNN generates a plurality of key-value pairs where each the key-value pair corresponds to an individual sensor from the plurality of sensors; and a value included in the key-value pair is determined based upon a subset of sensor data obtained from the individual sensor. The method inputs at least one navigation query and the plurality of key-value pairs into a Cross-Attention Transformer (CAT). The method obtains, from the CAT, a set of weighted sums, wherein each weighted sum corresponds to: a certain key-value pair; and a certain sensor from the plurality of sensors. The method updates a model depicting a 3D environment based on the set of weighted sums.