Abstract: Example localization systems and methods are described. In one implementation, a method receives a camera image from a vehicle camera and cleans the camera image using a VAE-GAN (variational autoencoder combined with a generative adversarial network) algorithm. The method further receives a vector map related to an area proximate the vehicle and generates a synthetic image based on the vector map. The method then localizes the vehicle based on the cleaned camera image and the synthetic image.

Abstract: Systems, methods, and devices for determining a location of a vehicle or other device are disclosed. A method includes receiving sensor data from a sensor and determining a prior map comprising LIDAR intensity values. The method includes extracting a sub-region of the prior map around a hypothesis position of the sensor. The method includes extracting a Gaussian Mixture Model (GMM) distribution of intensity values for a region of the sensor data by expectation-maximization and calculating a log-likelihood for the sub-region of the prior map based on the GMM distribution of intensity values for the sensor data.

Abstract: Example localization systems and methods are described. In one implementation, a method receives a camera image from a vehicle camera and cleans the camera image using a VAE-GAN (variational autoencoder combined with a generative adversarial network) algorithm. The method further receives a vector map related to an area proximate the vehicle and generates a synthetic image based on the vector map. The method then localizes the vehicle based on the cleaned camera image and the synthetic image.

Abstract: Example localization systems and methods are described. In one implementation, a method receives a camera image from a vehicle camera and cleans the camera image using a VAE-GAN (variational autoencoder combined with a generative adversarial network) algorithm. The method further receives a vector map related to an area proximate the vehicle and generates a synthetic image based on the vector map. The method then localizes the vehicle based on the cleaned camera image and the synthetic image.

Abstract: Example localization systems and methods are described. In one implementation, a method receives a camera image from a vehicle camera and cleans the camera image using a VAE-GAN (variational autoencoder combined with a generative adversarial network) algorithm. The method further receives a vector map related to an area proximate the vehicle and generates a synthetic image based on the vector map. The method then localizes the vehicle based on the cleaned camera image and the synthetic image.

Abstract: Methods and apparatus for real time machine vision and point-cloud data analysis are provided, for remote sensing and vehicle control. Point cloud data can be analyzed via scalable, centralized, cloud computing systems for extraction of asset information and generation of semantic maps. Machine learning components can optimize data analysis mechanisms to improve asset and feature extraction from sensor data. Optimized data analysis mechanisms can be downloaded to vehicles for use in on-board systems analyzing vehicle sensor data. Semantic map data can be used locally in vehicles, along with onboard sensors, to derive precise vehicle localization and provide input to vehicle to control systems.

Abstract: Systems, methods, and devices for determining a location of a vehicle or other device are disclosed. A method includes receiving sensor data from a sensor and determining a prior map comprising LIDAR intensity values. The method includes extracting a sub-region of the prior map around a hypothesis position of the sensor. The method includes extracting a Gaussian Mixture Model (GMM) distribution of intensity values for a region of the sensor data by expectation-maximization and calculating a log-likelihood for the sub-region of the prior map based on the GMM distribution of intensity values for the sensor data.

Abstract: A system, comprising a processor; and a memory, the memory storing instructions executable by the processor to receive image data from a vehicle sensor installed in a vehicle, transform the image data into global coordinate data, estimate fractal dimension values of the global coordinate data, and determine calibrated parameters based on the fractal dimension values to operate the vehicle sensor.

Abstract: A system, comprising a processor; and a memory, the memory storing instructions executable by the processor to receive image data from a vehicle sensor installed in a vehicle, transform the image data into global coordinate data, estimate fractal dimension values of the global coordinate data, and determine calibrated parameters based on the fractal dimension values to operate the vehicle sensor.

Abstract: A reinforcing ring (10) for a fenestration (32) of a stent graft which can be surface treated such as by passivation and/or electropolishing. The reinforcing ring has several turns of a substantially inextensible resilient wire (12) in a circular two dimensional planar shape and terminal ends (14) at each end of the wire. The terminal ends each comprising a loop (14) and a tail (16). The tail is folded back and extends around the circular shape. Each of the tails of the terminal loops can have an enlarged end. The reinforcing ring can be straightened out for surface treatment such as passivation and/or electropolishing with substantially no part of the circular shape, the loops or tails touching each other.

Abstract: Methods and apparatus for real time machine vision and point-cloud data analysis are provided, for remote sensing and vehicle control. Point cloud data can be analyzed via scalable, centralized, cloud computing systems for extraction of asset information and generation of semantic maps. Machine learning components can optimize data analysis mechanisms to improve asset and feature extraction from sensor data. Optimized data analysis mechanisms can be downloaded to vehicles for use in on-board systems analyzing vehicle sensor data. Semantic map data can be used locally in vehicles, along with onboard sensors, to derive precise vehicle localization and provide input to vehicle to control systems.

Abstract: Methods and apparatus for real time machine vision and point-cloud data analysis are provided, for remote sensing and vehicle control. Point cloud data can be analyzed via scalable, centralized, cloud computing systems for extraction of asset information and generation of semantic maps. Machine learning components can optimize data analysis mechanisms to improve asset and feature extraction from sensor data. Optimized data analysis mechanisms can be downloaded to vehicles for use in on-board systems analyzing vehicle sensor data. Semantic map data can be used locally in vehicles, along with onboard sensors, to derive precise vehicle localization and provide input to vehicle to control systems.

Abstract: Methods and apparatus for real time machine vision and point-cloud data analysis are provided, for remote sensing and vehicle control. Point cloud data can be analyzed via scalable, centralized, cloud computing systems for extraction of asset information and generation of semantic maps. Machine learning components can optimize data analysis mechanisms to improve asset and feature extraction from sensor data. Optimized data analysis mechanisms can be downloaded to vehicles for use in on-board systems analyzing vehicle sensor data. Semantic map data can be used locally in vehicles, along with onboard sensors, to derive precise vehicle localization and provide input to vehicle to control systems.

Abstract: A reinforcing ring (10) for a fenestration (32) of a stent graft which can be surface treated such as by passivation and/or electropolishing. The reinforcing ring has several turns of a substantially inextensible resilient wire (12) in a circular two dimensional planar shape and terminal ends (14) at each end of the wire. The terminal ends each comprising a loop (14) and a tail (16). The tail is folded back and extends around the circular shape. Each of the tails of the terminal loops can have an enlarged end. The reinforcing ring can be straightened out for surface treatment such as passivation and/or electropolishing with substantially no part of the circular shape, the loops or tails touching each other.

Abstract: A prosthesis deployment device having a elongate catheter body and a trigger wire guide concentric about the elongate catheter body where the trigger wire guide comprises three trigger wire lumens separate and apart from a guide wire lumen, with three trigger wires being at least partially disposed in the three trigger wire lumens and configured to engage a portion of a prosthesis to retain the prosthesis adjacent to the trigger wire guide.

Abstract: A reinforcing ring (10) for a fenestration (32) of a stent graft which can be surface treated such as by passivation and/or electropolishing. The reinforcing ring has several turns of a substantially inextensible resilient wire (12) in a circular two dimensional planar shape and terminal ends (14) at each end of the wire. The terminal ends each comprising a loop (14) and a tail (16). The tail is folded back and extends around the circular shape. Each of the tails of the terminal loops can have an enlarged end. The reinforcing ring can be straightened out for surface treatment such as passivation and/or electropolishing with substantially no part of the circular shape, the loops or tails touching each other.

Abstract: A trigger wire guide for a prosthesis deployment device. The prosthesis deployment device has a proximal end extending to a proximal nose cone dilator and having a trigger wire or wires and trigger wire release mechanism to retain the proximal end of a prosthesis adjacent the nose cone dilator. The trigger wire guide retains the trigger wire or wires to prevent fouling of the trigger wire with a prosthesis when the prosthesis is carried on the deployment device. The guide can be crimped or soldered to a guide wire catheter or concentric with it.

Abstract: A prosthesis deployment device having a elongate catheter body and a trigger wire guide concentric about the elongate catheter body where the trigger wire guide comprises three trigger wire lumens separate and apart from a guide wire lumen, with three trigger wires being at least partially disposed in the three trigger wire lumens and configured to engage a portion of a prosthesis to retain the prosthesis adjacent to the trigger wire guide.

Abstract: A fastening for fixing an exposed stent (2) to a graft material (1). At least two spaced apart fastenings (7, 8) are used, each fastening has at least one turn and preferably two turns of an elongate flexible fiber through the graft material and around a portion of the stent. Each fastening has a knot (9) which is at least two thumb knots and preferably four thumb knots.

Abstract: An aquatic passive sampling device is disclosed comprising a diffusion-limiting membrane and a receiving phase itself comprising an immobilised solid phase material supported by a solid support. The solid support and membrane features enable the device to be adapted for use forcontinuously monitoring a variety of micropollutants, including polar organic, non-polar organic and inorganic analytes. Furthermore, the analytes may be collected by short column extraction rather than batch extraction.