Abstract: A method includes: accessing a virtual building model defining a constellation of virtual elements, each virtual element representing a building element of a building on a construction site and associated with an installation location of the building element; for a first lift event at a crane, accessing first lift event data; correlating the first lift event with a first building element represented by a first virtual element; in response to correlating the first lift event with the first building element, annotating the first virtual element in the virtual building model with detection of installation of the first building element; identifying a second virtual element, linked to and preceding the first virtual element in the virtual building model; and in response to absence of detection of installation of a second building element prior to installation of the first building element, generating a notification indicating an erroneous installation order.

Abstract: A semiconductor metrology system including a spectrum acquisition tool for collecting, using a first measurement protocol, baseline scatterometric spectra on first semiconductor wafer targets, and for various sources of spectral variability, variability sets of scatterometric spectra on second semiconductor wafer targets, the variability sets embodying the spectral variability, a reference metrology tool for collecting, using a second measurement protocol, parameter values of the first semiconductor wafer targets, and a training unit for training, using the collected spectra and values, a prediction model using machine learning and minimizing an associated loss function incorporating spectral variability terms, the prediction model for predicting values for production semiconductor wafer targets based on their spectra.

Abstract: Systems and methods are provided for vehicle navigation. In one implementation, a system may comprise at least one processor. The processor may be programmed to receive an image associated with the environment of the host vehicle. The processor may analyze the image to identify a side of a parked vehicle; a first structural feature of the parked vehicle in a forward region of the side of the parked vehicle or a second structural feature of the parked vehicle in a rear region of the side of the parked vehicle; and a door feature of the parked vehicle in a vicinity of the first or the second structural features. The processor may then determine, based on a subsequent image, a change of an image characteristic of the door feature of the parked vehicle and alter a navigational path of the host vehicle based on the change of the image characteristic.

Abstract: Systems and methods are provided for navigating a host vehicle. At least one processing device may be programmed to receive an image representative of an environment of the host vehicle; determine a planned navigational action for the host vehicle; analyze the image to identify a target vehicle in the environment of the host vehicle; determine a next-state lateral distance between the host vehicle and the target vehicle that would result if the planned navigational action was taken; determine a lateral braking distance for the host vehicle and the target vehicle based on a maximum yaw rate capability, a maximum change in turn radius capability, and a current lateral speed of the host vehicle and the target vehicle; and implement the planned navigational action if the determined next-state distance is greater than a sum of the lateral braking distances for the host vehicle and the target vehicle.

Abstract: Among the various aspects of the present disclosure is the provision of compositions for single-cell reporter assays and methods of use thereof. Also provided are methods of determining individual activities of a plurality of nucleic acid regulatory elements, identifying a regulatory element having cell type-specific activity, or determining variance in activity of a plurality of nucleic acid regulatory elements.

Abstract: One variation of a method for monitoring lift events at a construction site includes: deriving a lifting profile from a first timeseries of load values, output by a load sensor coupled to a crane hook, during a first time period; deriving an oscillation characteristic from a first timeseries of motion values, output by a motion sensor coupled to the crane hook, during the first time period; identifying a type of an object carried by the crane hook during the first time period based on the lifting profile and the oscillation characteristic; selecting a load handling specification for the object based on the type of the object; accessing a second timeseries of motion values output by the motion sensor during a second time period; and, in response to the second timeseries of motion values deviating from the load handling specification, activating an object motion alarm for the object.

Abstract: Systems and methods are provided for vehicle navigation. In one implementation, a system may comprise an interface to obtain sensing data of an environment of the host vehicle. A processing device may be configured to determine a planned navigational action for the host vehicle; identify a target vehicle in the environment of the host vehicle; predict a resulting distance between the host and target vehicles if the planned action were taken; determine a host vehicle stopping distance based on a braking rate, maximum acceleration capability, and current speed of the host vehicle; determine a target vehicle stopping distance based on a braking rate and current speed of the target vehicle; and continue with the planned navigational action while the predicted distance is greater than a minimum safe longitudinal distance calculated based on the host vehicle stopping distance and the target vehicle stopping distance.

Abstract: Systems and methods are provided for vehicle navigation. In one implementation, a system may comprise an interface to obtain sensing data of an environment of the host vehicle. A processing device may be configured to determine a planned navigational action for the host vehicle; identify a target vehicle in the environment of the host vehicle; predict a following distance between the host vehicle and the target vehicle that would result if the planned navigational action was taken; determine a host vehicle braking distance based on a braking capability, acceleration capability, and speed of the host vehicle; determine a target vehicle braking distance, based on a speed and maximum braking capability of the target vehicle; and implement the planned navigational action when the predicted following distance is greater than a minimum safe longitudinal distance based on the determined host vehicle braking distance and the determined target vehicle braking distance.

Abstract: Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a system for navigating a vehicle includes at least one processing device programmed to receive, from an image capture device, a plurality of images associated with an environment of the vehicle, analyze at least one of the plurality of images to identify a navigable region in the environment of the vehicle, identify, based on the at least one of the plurality of images, at least one barrier associated with an edge of the navigable region, and determine a type of the at least one barrier. The at least one processing device is also programmed to determine a navigational path of the vehicle based on the determined type of the at least one barrier, and cause the vehicle to travel on at least a portion of the determined navigational path.

Abstract: One variation of a method for tracking lift events at a construction site includes: accessing a timeseries of load values output by a weight sensor, coupled to a crane hook, and a first geospatial location of the crane hook during a first time period; deriving a lifting profile at the first geospatial location from the timeseries of load values; deriving a weight of the object from the timeseries of load values; identifying a type of the object carried by the crane hook during the first time period based on the lifting profile; accessing a second geospatial location of the crane hook during unloading of the object from the crane hook; and generating a lift event record defining the type of the object, the weight of the object, a pickup location of the object at the first geospatial location, and a drop-off location of the object at the second geospatial location.

Abstract: One variation of a method for monitoring lift events at a construction site includes: deriving a lifting profile from a first timeseries of load values, output by a load sensor coupled to a crane hook, during a first time period; deriving an oscillation characteristic from a first timeseries of motion values, output by a motion sensor coupled to the crane hook, during the first time period; identifying a type of an object carried by the crane hook during the first time period based on the lifting profile and the oscillation characteristic; selecting a load handling specification for the object based on the type of the object; accessing a second timeseries of motion values output by the motion sensor during a second time period; and, in response to the second timeseries of motion values deviating from the load handling specification, activating an object motion alarm for the object.

Abstract: One variation of a method for monitoring lift events at a construction site includes: deriving a lifting profile from a first timeseries of load values, output by a load sensor coupled to a crane hook, during a first time period; deriving an oscillation characteristic from a first timeseries of motion values, output by a motion sensor coupled to the crane hook, during the first time period; identifying a type of an object carried by the crane hook during the first time period based on the lifting profile and the oscillation characteristic; selecting a load handling specification for the object based on the type of the object; accessing a second timeseries of motion values output by the motion sensor during a second time period; and, in response to the second timeseries of motion values deviating from the load handling specification, activating an object motion alarm for the object.

Abstract: Systems and methods are provided for vehicle navigation. In one implementation, a processing device may be configured to obtain a planned driving action for accomplishing a navigational goal of a host vehicle; receive sensor data from an environment surrounding the host vehicle; identify a target vehicle moving in the environment and a velocity of the target vehicle; calculate a stopping distance and a predicted trajectory for the target vehicle; calculate a planned trajectory for the host vehicle corresponding to the planned driving action; identify an intersection of the planned trajectory for the host vehicle with the predicted trajectory for the target vehicle; determine a braking action of the host vehicle to comply with a safety requirement; and cause the braking action to be applied to decelerate the host vehicle to change the planned trajectory, until the changed trajectory does not intersect the predicted trajectory of the target vehicle.

Abstract: The present disclosure relates to systems and methods for road edge detection and mapping, for vehicle wheel identification and navigation based thereon, and for classification of objects as moving or non-moving. Such systems and methods may include the use of trained systems, such as one or more neural networks. Further, autonomous vehicle systems may incorporate aspects of one or more of the disclosed systems and methods.

Abstract: Determining three-dimensional structure in a road environment using a system mountable in a host vehicle including a camera connectible to a processor. Multiple image frames are captured in the field of view of the camera. In the image frames, a line is selected below which the road is imaged. The line separates between upper images essentially excluding images of the road and lower images essentially including images of the road. One or more of the lower images is warped, according to a road homography to produce at least one warped lower image. The three-dimensional structure may be provided from motion of a matching feature within the upper images or from motion of a matching feature within at least one of the lower images and at least one warped lower image.

Abstract: One variation of a method for tracking lift events at a construction site includes: accessing a timeseries of load values output by a weight sensor, coupled to a crane hook, and a first geospatial location of the crane hook during a first time period; deriving a lifting profile at the first geospatial location from the timeseries of load values; deriving a weight of the object from the timeseries of load values; identifying a type of the object carried by the crane hook during the first time period based on the lifting profile; accessing a second geospatial location of the crane hook during unloading of the object from the crane hook; and generating a lift event record defining the type of the object, the weight of the object, a pickup location of the object at the first geospatial location, and a drop-off location of the object at the second geospatial location.

Abstract: Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a system for navigating a vehicle includes at least one processing device programmed to receive, from an image capture device, a plurality of images associated with an environment of the vehicle, analyze at least one of the plurality of images to identify a navigable region in the environment of the vehicle, identify, based on the at least one of the plurality of images, at least one barrier associated with an edge of the navigable region, and determine a type of the at least one barrier. The at least one processing device is also programmed to determine a navigational path of the vehicle based on the determined type of the at least one barrier, and cause the vehicle to travel on at least a portion of the determined navigational path.

Abstract: A drip irrigation unit, comprising: a bottom, generally cup-shaped, member having a bottom member base in which a plant-inserting opening is defined, a peripheral closed-loop wall extending upward from a peripheral edge of the bottom member to a first apex, and an internal closed-loop wall extending upwards from a peripheral edge of the plant-inserting opening to a second apex that is lower than the first apex, the peripheral and internal walls being integral with the bottom member base and defining a water reservoir, and a top member having an aperture and a rim, an annular surface defined between the rim and the aperture being downwardly sloped towards the aperture and defining a generally funnel-shape, the top member being connectable to at least one of the first or second apexes, such that the plant-inserting opening and the aperture become aligned, the internal closed-loop wall having at least one perforation vertically distanced from the bottom member base, the at least one perforation defining a water

Abstract: A system for navigating a host vehicle may receive an image representative of an environment of the host vehicle and determine a planned navigational action for accomplishing a navigational goal of the host vehicle. The system may identify a target vehicle, determine a current speed of the target vehicle, and assume a maximum braking rate capability of the target vehicle. The system may determine a next-state distance between the host vehicle and the target vehicle that would result if the planned navigational action was taken. The system may implement the planned navigational action if the host vehicle may be stopped using a predetermined sub-maximal braking rate within a distance that is less than the determined next-state distance summed together with a target vehicle travel distance determined based on the current speed of the target vehicle and the maximum braking rate capability of the target vehicle.

Abstract: One variation of a method for monitoring processes and progress at a construction site includes: accessing spatial and temporal representations of a sequence of construction tasks planned on the construction site; accessing a first set of load characteristics derived from data captured by a smart hook, arranged on a crane operated at the construction site, and a drop-off location of the smart hook during a first lift event at the crane; correlating the first lift event with a first construction task, in the sequence of construction tasks, based on the first set of load characteristics and the drop-off location; identifying a first notification trigger, in a set of notification triggers linked to the sequence of construction tasks, assigned to the first construction task; and transmitting a first notification to a computing device, associated with a user, according to the first notification trigger, the first notification identifying the first construction task.