Abstract: A computer accesses a first symbolic expression for an output matrix as a function of an input matrix at a computing device comprising processing circuitry and memory. The computer computes a first Jacobian of the input matrix with respect to an input tangent space. The computer computes a second Jacobian of the output matrix with respect to the input matrix. The computer computes a third Jacobian of an output tangent space with respect to the input matrix. The computer applies symbolic matrix multiplication to the first Jacobian, the second Jacobian, and the third Jacobian to obtain a second symbolic expression for the output tangent space with respect to the input tangent space. The computer provides a representation of the second symbolic expression, the second symbolic expression representing a computed tangent-space Jacobian.

Abstract: Autonomous aerial navigation in low-light and no-light conditions includes using night mode obstacle avoidance intelligence and mechanisms for vision-based unmanned aerial vehicle (UAV) navigation to enable autonomous flight operations of a UAV in low-light and no-light environments using infrared data.

Abstract: A method includes receiving, at a security platform, a plurality of threat indicators associated with current intrusive activities with respect to computing resources of a first entity and receiving, at the security platform, a plurality of threat datasets associated with prior intrusive activities with respect to computing resources associated with one or more entities including the first entity. The method further includes receiving, at the security platform, a plurality of environmental datasets associated with the computing resources of the first entity and determining an alert level associated with a first threat indicator of the plurality of threat indicators based on the plurality of threat datasets and the plurality of environmental datasets. The method further includes generating, responsive to the alert level satisfying an alert threshold criterion, an alert associated with the first threat indicator for one or more users of the first entity.

Abstract: Autonomous aerial navigation in low-light and no-light conditions includes using night mode obstacle avoidance intelligence, training, and mechanisms for vision-based unmanned aerial vehicle (UAV) navigation to enable autonomous flight operations of a UAV in low-light and no-light environments using infrared data.

Abstract: Systems and methods to recommend templates for project-level graphical user interfaces within a collaboration environment are described herein. Exemplary implementations may: manage environment state information maintaining a collaboration environment; manage information defining project-level graphical user interfaces; monitor use of the collaboration environment by the users determined metric values for use metrics of the users; create templates for the project-level graphical user interfaces based on the metric values; generate and deliver template recommendations for the project-level graphical user interfaces; effectuate presentation of the project-level graphical user interfaces for the individual projects in the collaboration environment; and/or perform other operations.

Abstract: In some examples, an unmanned aerial vehicle (UAV) may determine a plurality of contour paths spaced apart from each other along at least one axis associated with a scan target. For instance, each contour path may be spaced away from a surface of the scan target based on a selected distance. The UAV may determine a plurality of image capture locations for each contour path. The image capture locations may indicate locations at which an image of a surface of the scan target is to be captured. The UAV may navigate along the plurality of contour paths based on a determined speed while capturing images of the surface of the scan target based on the image capture locations.

Abstract: Systems and methods to recommend templates for project-level graphical user interfaces within a collaboration environment are described herein. Exemplary implementations may: manage environment state information maintaining a collaboration environment; manage information defining project-level graphical user interfaces; monitor use of the collaboration environment by the users determined metric values for use metrics of the users; create templates for the project-level graphical user interfaces based on the metric values; generate and deliver template recommendations for the project-level graphical user interfaces; effectuate presentation of the project-level graphical user interfaces for the individual projects in the collaboration environment; and/or perform other operations.

Abstract: A plurality of data sets characterizing prior intrusive activities with respect to computing resources associated with one or more entities are received at a security platform. One or more rule generation policies each pertaining to at least one type of intrusive activity are received at a security platform. The one or more rule generation policies are applied to the plurality of data sets characterizing the prior intrusive activities to generate a plurality of intrusive activity detection rules. The plurality of intrusive activity detection rules are caused to be used to detect subsequent intrusive activities.

Abstract: Autonomous aerial navigation in low-light and no-light conditions includes using night mode obstacle avoidance intelligence, training, and mechanisms for vision-based unmanned aerial vehicle (UAV) navigation to enable autonomous flight operations of a UAV in low-light and no-light environments using infrared data.

Abstract: A method of preventing arc flaring events for a welding system is provided. The method includes determining, by a controller, a real-time welding output characteristic of the welding system. The method additionally includes comparing, by the controller, the real-time welding output characteristic to a threshold welding output characteristic. The method further includes controlling an operating characteristic of the welding system in response to a determination that the real-time welding output characteristic exceeds the threshold welding output characteristic.

Abstract: An autonomous vehicle that is equipped with image capture devices can use information gathered from the image capture devices to plan a future three-dimensional (3D) trajectory through a physical environment. To this end, a technique is described for image-space based motion planning. In an embodiment, a planned 3D trajectory is projected into an image-space of an image captured by the autonomous vehicle. The planned 3D trajectory is then optimized according to a cost function derived from information (e.g., depth estimates) in the captured image. The cost function associates higher cost values with identified regions of the captured image that are associated with areas of the physical environment into which travel is risky or otherwise undesirable. The autonomous vehicle is thereby encouraged to avoid these areas while satisfying other motion planning objectives.

Abstract: An autonomous vehicle that is equipped with image capture devices can use information gathered from the image capture devices to plan a future three-dimensional (3D) trajectory through a physical environment. To this end, a technique is described for image-space based motion planning. In an embodiment, a planned 3D trajectory is projected into an image-space of an image captured by the autonomous vehicle. The planned 3D trajectory is then optimized according to a cost function derived from information (e.g., depth estimates) in the captured image. The cost function associates higher cost values with identified regions of the captured image that are associated with areas of the physical environment into which travel is risky or otherwise undesirable. The autonomous vehicle is thereby encouraged to avoid these areas while satisfying other motion planning objectives.

Abstract: Autonomous aerial navigation in low-light and no-light conditions includes using night mode obstacle avoidance intelligence, training, and mechanisms for vision-based unmanned aerial vehicle (UAV) navigation to enable autonomous flight operations of a UAV in low-light and no-light environments using infrared data.

Abstract: An autonomous vehicle that is equipped with image capture devices can use information gathered from the image capture devices to plan a future three-dimensional (3D) trajectory through a physical environment. To this end, a technique is described for image-space based motion planning. In an embodiment, a planned 3D trajectory is projected into an image-space of an image captured by the autonomous vehicle. The planned 3D trajectory is then optimized according to a cost function derived from information (e.g., depth estimates) in the captured image. The cost function associates higher cost values with identified regions of the captured image that are associated with areas of the physical environment into which travel is risky or otherwise undesirable. The autonomous vehicle is thereby encouraged to avoid these areas while satisfying other motion planning objectives.

Abstract: A calibration of an unmanned aerial vehicle is performed without the use of a magnetometer. The unmanned aerial vehicle generates a first acceleration vector in a navigation frame of reference and a second acceleration vector in a GPS frame of reference. The unmanned aerial vehicle estimates a heading of the unmanned aerial vehicle based on the first acceleration vector and the second acceleration vector. The unmanned aerial vehicle performs a calibration based on the estimated heading of the unmanned aerial vehicle.

Abstract: A computer accesses an input element storage and an output element storage. The computer accesses a symbolic expression for output element storage as a function of the input element storage. The computer computes, using a symbolic computation engine of the computer, a symbolic expression for the tangent space Jacobian of the output element storage with respect to an input tangent space. The computer outputs the computed expression.

Abstract: An autonomous vehicle that is equipped with image capture devices can use information gathered from the image capture devices to plan a future three-dimensional (3D) trajectory through a physical environment. To this end, a technique is described for image-space based motion planning. In an embodiment, a planned 3D trajectory is projected into an image-space of an image captured by the autonomous vehicle. The planned 3D trajectory is then optimized according to a cost function derived from information (e.g., depth estimates) in the captured image. The cost function associates higher cost values with identified regions of the captured image that are associated with areas of the physical environment into which travel is risky or otherwise undesirable. The autonomous vehicle is thereby encouraged to avoid these areas while satisfying other motion planning objectives.

Abstract: An autonomous vehicle that is equipped with image capture devices can use information gathered from the image capture devices to plan a future three-dimensional (3D) trajectory through a physical environment. To this end, a technique is described for image-space based motion planning. In an embodiment, a planned 3D trajectory is projected into an image-space of an image captured by the autonomous vehicle. The planned 3D trajectory is then optimized according to a cost function derived from information (e.g., depth estimates) in the captured image. The cost function associates higher cost values with identified regions of the captured image that are associated with areas of the physical environment into which travel is risky or otherwise undesirable. The autonomous vehicle is thereby encouraged to avoid these areas while satisfying other motion planning objectives.

Abstract: Systems and methods to recommend templates for project-level graphical user interfaces within a collaboration environment are described herein. Exemplary implementations may: manage environment state information maintaining a collaboration environment; manage information defining project-level graphical user interfaces; monitor use of the collaboration environment by the users determined metric values for use metrics of the users; create templates for the project-level graphical user interfaces based on the metric values; generate and deliver template recommendations for the project-level graphical user interfaces; effectuate presentation of the project-level graphical user interfaces for the individual projects in the collaboration environment; and/or perform other operations.

Abstract: Immunoglobulin lambda variable domain sequence adapted for expression with non-native N terminal signal peptide, comprising a deletion at IMGT position 1.