10532results about "Navigation instruments" patented technology

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

An improved system and method is disclosed of accessing mapping data for a geographical area comprising speed limit data for a first road segment, accessing second mapping data providing speed limit data for a plurality of corresponding road segments from a second source, determining an overlap amount between the candidate road segments and the first road segment, using overlap data to identify a first subset of the candidate road segments, identifying a first speed limit that has a highest likelihood of being accurate from speed limits respectively associated with road segments in the second subset of the candidate road segments, transmitting the first speed limit in association with a map comprising the first geographical area to a vehicle device.

Approaches presented herein provide for the use of language models to generate tokenized descriptions of physical environments. In at least one embodiment, sensor and / or observational data can be obtained for an environment and used to generate a set of perception data. The perception data can be analyzed, along with approximate positional data within the environment, to identify a set of aligned map data. The aligned map data and perception data can be provided as input to a trained language model, which can be trained to correlate and / or fuse the information to generate a single, consistent representation of the environment. The language model can output a tokenized description of the environment, which can be in a domain-specific language, that is a compact but robust textual description of the environment.

The invention discloses a multi-target scene visual SLAM (Simultaneous Localization and Mapping) method fusing target semantics and Gaussian splashing. The method comprises the steps that input data are preprocessed, two-dimensional space masks and semantic information corresponding to the two-dimensional space masks are extracted, global semantic identifiers are distributed to the two-dimensional space masks corresponding to a background and each target, and a target semantic segmentation map is obtained; reading first frame RGBD data as a current frame, acquiring a target semantic segmentation map corresponding to the current frame, and initializing camera pose parameters; respectively establishing an initial target Gaussian splashing model for the background and each target; adopting a Gaussian splash algorithm to render all the target Gaussian splash models to a next frame, and generating an RGB rendering image, a depth rendering image and a target semantic rendering image of the next frame; and designing a loss function between the next frame of rendered image and the corresponding real image, optimizing the pose of the camera, and updating the parameters of the target Gaussian splash model. According to the invention, simultaneous positioning and map construction of multiple target scenes are realized.

A display system of an aircraft includes a display device defining a display area, a vision system for generating an image of an operating environment of the aircraft on the display area, data processors operatively coupled to the display device and the vision system, and non-transitory machine-readable memory operatively coupled to the one or more data processors and storing instructions executable by the one or more processors and configured to cause the one or more processors to, when a condition of the aircraft is met, cause an alteration of a display of flight information on the display area to declutter a cutout region in the image generated by the vision system, the cutout region devoid of imaging generated by the vision system and displaying an Approach Lighting System (ALS) of a runway of intended landing for the aircraft.

Systems and methods are provided for promoting stable aircraft approach conditions. The system comprises a display device that is onboard an aircraft and a controller in communication with the display device. The controller is configured to, by a processor: receive data that includes information relating to an action configured to stabilize an approach of the aircraft during landing thereof and a recommended timing of performing the action relative to a predetermined flight plan of the aircraft, and render a first visual element on the display device that is configured to display the action relative to the flight plan and dynamically indicate the recommended timing of performing the action relative to a geographic position of the aircraft along the flight plan.

The invention belongs to the technical field of intelligent transportation, and particularly relates to a multi-view automatic driving scene reconstruction method based on three-dimensional Gaussian splashing, which comprises the following steps: S1, data acquisition; s2, fast system initialization: setting the received first frame data as a key frame, and processing the first frame data by adopting a Gaussian high-pass filter to reserve most of high-frequency information in the image; s3, key frame selection, wherein dynamic key frame selection under a sliding window is adopted; s4, estimating the pose of the vehicle-mounted camera; and S5, reconstructing an automatic driving scene. According to the method, the precision and the efficiency of three-dimensional reconstruction are improved, the robustness and the real-time performance of the system are enhanced, high-fidelity rendering and dynamic scene editing are realized, and a comprehensive frequency domain analysis and regularization strategy is provided; and the method has a wide application prospect, can also be applied to the fields of high-precision map updating, environment perception and path planning, unmanned aerial vehicle navigation, robot navigation and the like, and provides powerful support for the development of intelligent transportation and automatic driving technologies in the future.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

The invention discloses a laser SLAM (Simultaneous Localization and Mapping) method in a dynamic environment of a well mine, which relates to data processing and comprises the following steps of: performing mapping by utilizing a Cartograph SLAM algorithm; segmenting the PCD point cloud map by adopting an octree-based segmentation method according to a preset movement or deformation frequency threshold value of an object in each region in the well mining environment; adjusting the map resolution of each area in the PCD point cloud map according to the segmentation result; a change detection algorithm is used to carry out change detection on an area with object movement or deformation frequency exceeding a threshold value in the segmented PCD point cloud map, and new point cloud data of the change area is updated to the original PCD point cloud map in an increment mode; carrying out registration and fusion on the PCD point cloud map after local updating and an original PCD point cloud map; the global consistency is improved by aiming at the poor global consistency existing in the laser SLAM mapping of the well industry and mining in the prior art.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

A system may be configured to display a view of an airport moving map (AMM) depicting a location of an aircraft relative to a runway, the runway, a maximum runway overrun awareness and alerting system (ROAAS) model distance (RMD) indicator on the runway, a nominal model distance (NMD) indicator on the runway, and a ROAAS runway end indicator.

Disclosed herein is a method for facilitating tailoring experiences of users, in accordance with some embodiments. Accordingly, the method includes receiving, using a communication device, a data from a device. Further, the method includes analyzing, using a processing device, the data. Further, the method includes determining, using the processing device, a context associated with a user based on the analyzing of the data. Further, the method includes adjusting, using the processing device, at least one of a plurality of reality layers of an artificial environment based on the context. Further, the method includes provisioning, using the processing device, a content corresponding to at least one of the plurality of reality layers of the artificial environment based on the adjusting. Further, the method includes storing, using a storage device, the data and the context.

An emergency module may determine occurrence of emergency events of a vehicle traversing through an environment. The emergency module may rank the emergency events according to importance level associated with each emergency event. The emergency module may select an emergency event based on the ranking. The emergency module may notify a user of the vehicle of the selected emergency event. The emergency module may identify corrective actions associated with the selected emergency event, the identified corrective actions including a user action and a non-user action. The emergency module may perform the non-user action of the identified corrective actions. The emergency module may notify the user of the vehicle of the user action.

The invention discloses a navigation matching correction method based on an inspection robot, and the method comprises the steps: building a feature database through the deployment of a physical calibration object and the recognition of a natural feature object, providing a reliable positioning reference for a robot, achieving the coarse positioning through the fusion of visual and laser radar data in a positioning process, and introducing a dynamic credibility evaluation mechanism. The positioning reliability is quantified in real time through an exponential decay model, when the credibility is lower than a threshold value, the system automatically triggers a compensation behavior to re-search features, in the aspect of multi-robot cooperation, secondary positioning correction is achieved through track matching and data fusion, high-confidence-coefficient reference data are screened through a clustering algorithm, the group positioning precision is improved, and the positioning accuracy is improved. Aiming at a key inspection area, multi-angle image matching is adopted to realize fine positioning, a positioning error is dynamically corrected through a sliding window, the continuity and accuracy of robot navigation in a complex environment are remarkably improved through closed-loop correction and self-adaptive optimization, and the method is suitable for intelligent inspection requirements of railway trains.

A map data generation system includes a storage to store map data for an agricultural machine that performs self-driving, and a processor. When data of a road is not included in a predetermined region indicated by the map data, the processor is configured or programmed to generate data of the road in the predetermined region based on a trajectory of a vehicle including a GNSS receiver and traveling in the predetermined region, the trajectory being acquired in the predetermined region based on GNSS data that is output from the GNSS receiver, and attribute information of the vehicle.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Methods, systems, and devices for leveraging automotive and wearable-based data are described. For example, a system may include a wearable device, a user device associated with the wearable device, and a vehicle. The system may determine when a user is within a proximity of the vehicle based on communications between the vehicle and the wearable device, between the vehicle and the user device, or both. The system may retrieve physiological data measurement from the user via the wearable device based on determining the user is positioned in a proximity of the vehicle, such that one or more operational parameters of the vehicle may be adjusted based on the physiological data. Additionally, or alternatively, the system may receive telemetry data from one more sensors of the vehicle and may provide feedback to the user based on the telemetry data satisfying one or more trigger conditions.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

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.

A collaborative map building method is described in which if it is determined, for example, by a SLAM network edge, that a portion of a map corresponding to a target area of a first region is incomplete, a request to a device is transmitted to move toward the target area. The map is updated based on the scan performed by the device in the target area. Also described is a virtual image guide embodiment in which upon determining that a map of a target area of the first region is incomplete, a virtual guide image is generated on a device to appear at a target location. The user of the device is guided to the target area by the virtual image.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

The invention provides an unmanned aerial vehicle surveying and mapping method and system, electronic equipment and a storage medium, and relates to the technical field of unmanned aerial vehicle surveying and mapping. The method comprises the following steps: carrying out base station position planning based on geographic data and preset factors, and arranging a CORS platform base station; then, acquiring a remote sensing image to construct a three-dimensional model, and performing semantic segmentation to obtain key ground feature information; and generating a multi-modal environment semantic map for surveying and mapping route planning based on registration of the key surface feature information and the geographic data. The unmanned aerial vehicle obtains surveying and mapping data, CORS positioning information and surveying and mapping image data in real time according to the surveying and mapping route, and environment semantic positioning data is obtained based on the surveying and mapping image data and multi-mode environment semantic map registration. And finally, performing registration processing by comprehensively utilizing the CORS positioning information, the environmental semantic positioning data and the surveying and mapping data to obtain target surveying and mapping data. Through the scheme, the surveying and mapping accuracy of the unmanned aerial vehicle is improved.