Abstract: An object identification method is disclosed. The method includes training a first neural network for a first set of conditions regarding a first plurality of objects, training a second neural network for a second set of conditions regarding a second plurality of objects, receiving a plurality of target images associated with a target set of conditions in which to identify objects, analyzing the plurality of target images using the first and second neural networks to identify objects in the plurality of target images resulting in object identification information, and selecting the first neural network or the second neural network as a preferred neural network for the target set of conditions based on an analysis of the object identification information.

Abstract: An object identification and collection method is disclosed. The method includes receiving a pick-up path that identifies a route in which to guide an object-collection system over a target geographical area to pick up objects, determining a current location of the object-collection system relative to the pick-up path, and guiding the object-collection system along the pick-up path over the target geographical area based on the current location. The method further includes capturing images in a direction of movement of the object-collection system along the pick-up path, identifying a target object in the images; tracking movement of the target object through the images, determining that the target object is within range of an object picker assembly on the object-collection system based on the tracked movement of the target object, and instructing the object picker assembly to pick up the target object.

Abstract: A re-timer device includes transceiver circuitry. The transceiver circuitry includes clock generation circuitry and first receiver circuitry. The clock generation circuitry generates a first clock signal. The first receiver circuitry receives the first clock signal and a first input signal. The first receiver circuitry generates a first frequency offset value based on the first input signal and the first clock signal. The first input signal has a first frequency and the first clock signal has a second frequency different than the first frequency. The first receiver circuitry outputs the first frequency offset value.

Abstract: An object-collection system is disclosed. The system including a vehicle connected to a bucket, a camera connected to the vehicle, and an object picking assembly configured to pick up objects off of ground. The system further includes a processor that obtains object information for identified objects, guides the object-collection system over a target geographical area toward the identified objects based on the object information, captures images of the ground relative to the object picker as the object-collection system is guided towards the identified objects, identifies a target object in the images, tracks movement of the target object across the images as the object-collection system is guided towards the identified objects, and employs the tracked movement of the target object to instruct the object picker to pick up the target object.

Abstract: An object-collection system is disclosed. The system including a vehicle connected to a bucket, a camera connected to the vehicle, and an object picking assembly configured to pick up objects off of ground. The system further includes a processor that obtains object information for identified objects, guides the object-collection system over a target geographical area toward the identified objects based on the object information, captures images of the ground relative to the object picker as the object-collection system is guided towards the identified objects, identifies a target object in the images, tracks movement of the target object across the images as the object-collection system is guided towards the identified objects, and employs the tracked movement of the target object to instruct the object picker to pick up the target object.

Abstract: An object identification method is disclosed. The method includes obtaining images of a target geographical area and telemetry information of an image-collection vehicle at a time of capture, analyzing each image to identify objects, and determining a position of the objects. The method further includes determining an image capture height, determining a position of the image using the capture height and the telemetry information, performing a transform on the image based on the capture height and the telemetry information, identifying the objects in the transformed image, determining first pixel locations of the objects within the transformed image, performing a reverse transform on the first pixel locations to determine second pixel locations in the image, and determining positions of the objects within the area based on the second pixel locations within the captured image and the determined image position.

Abstract: An object-collection system is disclosed. The system includes a mechanical arm assembly, a receptacle, an end-effector, and a user input device. The mechanical arm assembly has multiple degrees of freedom and is configured to pick up small objects off of the ground surface. The receptacle holds small objects that are picked up by the mechanical arm assembly. The end-effector is positioned at a proximal end of the mechanical arm assembly. The end-effector grasps and acquires small objects from the ground surface. The user input device provides operator control input from an operator on the ground vehicle to actuate the multiple degrees of freedom of the mechanical arm assembly and to actuate the end-effector. The user input signals from the user input device control electric or hydraulic actuators in the object collection system.

Abstract: An object identification and collection method is disclosed. The method includes receiving a pick-up path that identifies a route in which to guide an object-collection system over a target geographical area to pick up objects, determining a current location of the object-collection system relative to the pick-up path, and guiding the object-collection system along the pick-up path over the target geographical area based on the current location. The method further includes capturing images in a direction of movement of the object-collection system along the pick-up path, identifying a target object in the images; tracking movement of the target object through the images, determining that the target object is within range of an object picker assembly on the object-collection system based on the tracked movement of the target object, and instructing the object picker assembly to pick up the target object.

Abstract: An object identification method is disclosed. The method includes obtaining images of a target geographical area and telemetry information of an image-collection vehicle at a time of capture, analyzing each image to identify objects, and determining a position of the objects. The method further includes determining an image capture height, determining a position of the image using the capture height and the telemetry information, performing a transform on the image based on the capture height and the telemetry information, identifying the objects in the transformed image, determining first pixel locations of the objects within the transformed image, performing a reverse transform on the first pixel locations to determine second pixel locations in the image, and determining positions of the objects within the area based on the second pixel locations within the captured image and the determined image position.

Abstract: An object identification method is disclosed. The method includes training a first neural network for a first set of conditions regarding a first plurality of objects, training a second neural network for a second set of conditions regarding a second plurality of objects, receiving a plurality of target images associated with a target set of conditions in which to identify objects, analyzing the plurality of target images using the first and second neural networks to identify objects in the plurality of target images resulting in object identification information, and selecting the first neural network or the second neural network as a preferred neural network for the target set of conditions based on an analysis of the object identification information.

Abstract: An object identification and collection method is disclosed. The method includes receiving a pick-up path that identifies a route in which to guide an object-collection system over a target geographical area to pick up objects, determining a current location of the object-collection system relative to the pick-up path, and guiding the object-collection system along the pick-up path over the target geographical area based on the current location. The method further includes capturing images in a direction of movement of the object-collection system along the pick-up path, identifying a target object in the images; tracking movement of the target object through the images, determining that the target object is within range of an object picker assembly on the object-collection system based on the tracked movement of the target object, and instructing the object picker assembly to pick up the target object.

Abstract: An object identification method is disclosed. The method includes training a first neural network for a first set of conditions regarding a first plurality of objects, training a second neural network for a second set of conditions regarding a second plurality of objects, receiving a plurality of target images associated with a third set of conditions in which to identify objects, analyzing the plurality of target images using the first and second neural networks to identify objects in the plurality of target images resulting in object identification information, and selecting the first neural network or the second neural network as a preferred neural network for the third set of conditions based on an analysis of the object identification information.

Abstract: A multi-modulus frequency divider circuit includes first and second frequency division stages. The first frequency division stage receives a first input clock signal having a first oscillating frequency, a first modulus input signal, and a first division bit. The first frequency division stage divides the first oscillating frequency by a first division ratio, and generates a second input clock signal having a second oscillating frequency. The second frequency division stage receives the second input clock signal, a second modulus input signal, and a second division bit. The second frequency division stage generates an output clock signal having an output oscillating frequency by dividing the second oscillating frequency by a second division ratio.

Abstract: An object identification and collection method is disclosed. The method includes receiving a pick-up path that identifies a route in which to guide an object-collection system over a target geographical area to pick up objects, determining a current location of the object-collection system relative to the pick-up path, and guiding the object-collection system along the pick-up path over the target geographical area based on the current location. The method further includes capturing images in a direction of movement of the object-collection system along the pick-up path, identifying a target object in the images; tracking movement of the target object through the images, determining that the target object is within range of an object picker assembly on the object-collection system based on the tracked movement of the target object, and instructing the object picker assembly to pick up the target object.

Abstract: An object identification method is disclosed. The method includes obtaining images of a target geographical area and telemetry information of an image-collection vehicle at a time of capture, analyzing each image to identify objects, and determining a position of the objects. The method further includes determining an image capture height, determining a position of the image using the capture height and the telemetry information, performing a transform on the image based on the capture height and the telemetry information, identifying the objects in the transformed image, determining first pixel locations of the objects within the transformed image, performing a reverse transform on the first pixel locations to determine second pixel locations in the image, and determining positions of the objects within the area based on the second pixel locations within the captured image and the determined image position.

Abstract: An object identification and collection method is disclosed. The method includes employing an image-collection vehicle to capture first images of a target geographical area, identifying one or more objects in the first images, and guiding an object-collection system over the target geographical area toward the one or more identified objects. The method further includes determining object information for each of the identified objects and guiding the object-collection system based on the object information. The method may further include capturing second images of the ground relative to the object-collection system as the object-collection system is guided toward the one or more identified objects, identifying a target object in the second images, and instructing the object-collection system to pick up the target object.

Abstract: An object identification method is disclosed. The method includes training a first neural network for a first set of conditions regarding a first plurality of objects, training a second neural network for a second set of conditions regarding a second plurality of objects, receiving a plurality of target images associated with a third set of conditions in which to identify objects, analyzing the plurality of target images using the first and second neural networks to identify objects in the plurality of target images resulting in object identification information, and selecting the first neural network or the second neural network as a preferred neural network for the third set of conditions based on an analysis of the object identification information.

Abstract: An object-collection system is disclosed. The system including a vehicle connected to a bucket, a camera connected to the vehicle, and an object picking assembly configured to pick up objects off of ground. The system further includes a processor that obtains object information for identified objects, guides the object-collection system over a target geographical area toward the identified objects based on the object information, captures images of the ground relative to the object picker as the object-collection system is guided towards the identified objects, identifies a target object in the images, tracks movement of the target object across the images as the object-collection system is guided towards the identified objects, and employs the tracked movement of the target object to instruct the object picker to pick up the target object.

Abstract: In a semiconductor chip for an electronic device, a programmable trim code is independent from a default trim code. An output trim code is produced by selecting either the default trim code or the programmable trim code. The default trim code for a plurality of the semiconductor chips is set by forming metal interconnects according to a first metal layout in a metal interconnect layer during fabrication of at least one of the semiconductor chips. The default trim code is reset by forming the metal interconnects according to a second metal layout in the metal interconnect layer during fabrication of subsequent semiconductor chips.

Abstract: A clock and data recovery (CDR) circuit that receives an input signal and generates clock and sampled output signals includes a phase-frequency detector (PFD) circuit, a control circuit, a digital-to-analog converter (DAC), a current-controlled oscillator (CCO) and a data sampler. The PFD generates intermediate and fine digital control signals. The DAC receives the intermediate digital control signal as a coarse digital control signal and the fine digital control signal and generates an output current. The CCO receives the output current and generates the clock signal. The coarse digital control signal is used to coarse calibrate a frequency of the clock signal and the fine digital control signal is used to fine calibrate the frequency of the clock signal. The data sampler receives the clock signal and samples the input signal at the frequency of the clock signal to generate the sampled output signal.