Abstract: The present disclosure generally relates to a system of a delivery device for combining sensor data from various types of sensors to generate a map that enables the delivery device to navigate from a first location to a second location to deliver an item to the second location. The system obtains data from RGB, LIDAR, and depth sensors and combines this sensor data according to various algorithms to detect objects in an environment of the delivery device, generate point cloud and pose information associated with the detected objects, and generates object boundary data for the detected objects. The system further identifies object states for the detected object and generates the map for the environment based on the detected object, the generated object proposal data, the labeled point cloud data, and the object states. The generated map may be provided to other systems to navigate the delivery device.

Abstract: Embodiments herein describe a PIM correction circuit. In a base station, TX and RX RF changes, band pass filters, duplexers, and diplexers can have severe memory effects due to their sharp transition bandwidth from pass band to stop band. PIM interference, generated by the TX signals and reflected onto the RX RF chain will include these memory effects. These memory effects make PIM cancellation complex, requiring complicated computations and circuits. However, the embodiments herein use a PIM correction circuit that separates the memory effects of the TX and RX paths from the memory effects of PIM, thereby reducing PIM cancellation complexity and hardware implementation cost.

Abstract: A digital predistortion (DPD) system includes an input configured to receive an input signal. In some examples, a first signal path configured to generate a first signal based on the input signal. In some examples, an error model provider configured to generate an error model signal modeled after a gate bias error voltage associated with the DPD system. In some examples, a first combiner configured to combine the first signal and the error model signal to generate a first intermediate signal, and the DPD system generates an output signal based at least on the first intermediate signal.

Abstract: A fall detection-based help-seeking method and an electronic device, to improve accuracy of fall detection performed by an electronic device and reduce a probability of mistakenly triggering automatic help-seeking of the electronic device. A solution includes: the electronic device includes a motion sensor and the motion sensor includes an acceleration sensor or a gyro sensor. The electronic device collects a first motion parameter of a user by using the motion sensor. The electronic device obtains a fall confidence of the first motion parameter if the first motion parameter matches a first preset fall parameter, where the fall confidence of the first motion parameter is used to represent a probability that the first motion parameter is a motion parameter collected when the user falls. The electronic device sends help-seeking information if the fall confidence of the first motion parameter is greater than a preset confidence threshold.

Abstract: An electronic device may learn a specific somatosensory action completed by a user, and also record a specific remote control key selected by the user, and then the electronic device may associate the action with the key. When recognizing that the user completes the action, the electronic device may simulate a control signal generated by the key, to control a game operation. Accordingly, the user can simply and quickly transform a conventional game into a somatosensory game. In this process, a game manufacturer does not need to perform additional customization work, and the user does not need to use an additional somatosensory device.

Abstract: A method for preventing hand gesture misrecognition is provided. In the method for preventing hand gesture misrecognition, whether a user is exercising is recognized by obtaining motion data of the user in real time, to choose whether to disable a hand gesture recognition function. If the object user is exercising, the electronic device does not perform hand gesture recognition; or if the object user is not exercising, the electronic device performs hand gesture recognition. In addition, in the method, a trigger threshold for hand gesture recognition may further be adaptively adjusted based on a deflection angle between a human body plane of the user and a plane on which the electronic device is located.

Abstract: A swing action detection method is applied to a wearable device including one or more motion sensors and a sound collector. In the method, the wearable device collects a first sound signal using the sound collector to determine whether a user strikes a ball. After a strike action is determined, an exercise parameter of the user is obtained with reference to first exercise data collected by the wearable device using the one or more motion sensors to monitor the strike action of the user, and effectively assist the user in improving a strike rhythm and strike stability.

Abstract: A cycling detection method, an electronic device, and a computer-readable storage medium are provided. The cycling detection method includes: obtaining an acceleration signal and an angular velocity signal collected by a wearable device of a user's foot, and analyzing a time-domain feature of the acceleration signal, a frequency-domain feature of the acceleration signal, a time-domain feature of the angular velocity signal, and/or a frequency-domain feature of the angular velocity signal; filtering the acceleration signal and the angular velocity signal to obtain a target acceleration signal and a target angular velocity signal of the user's cycling if it is determined, based on an analysis result, that a current status of the user is a cycling state; and determining a behavior feature of the user's cycling based on the target acceleration signal and the target angular velocity signal, where the behavior feature includes a cadence feature and a foot posture feature.

Abstract: This application relates to the field of electronic technologies, and provides an action recognition method and apparatus, a terminal device, and a motion monitoring system. Characteristic extraction and action recognition are performed based on motion data collected by data collection apparatuses; a gait characteristic, a swing gesture characteristic, and an image action characteristic of a user are recognized by using a plurality of pieces of motion data; and a type of a hitting action of a player is determined based on the gait characteristic, the swing gesture characteristic, and the image action characteristic. In this way, the hitting action of the player in a motion process can be accurately recognized. This is conducive to performing comprehensive analysis on a comprehensive sports capability of the player, and is more helpful to formulating a personalized training plan for the player.

Abstract: A digital predistortion (DPD) system includes an input configured to receive an input signal. In some examples, a first signal path configured to generate a first signal based on the input signal. In some examples, an error model provider configured to generate an error model signal modeled after a gate bias error voltage associated with the DPD system. In some examples, a first combiner configured to combine the first signal and the error model signal to generate a first intermediate signal, and the DPD system generates an output signal based at least on the first intermediate signal.

Abstract: A transmitter for a communication system comprises a digital pre-distortion (DPD) circuit and adaptation circuitry. The DPD circuit is configured to generate a digital intermediate signal by compensating an input signal for distortions resulting from an amplifier. The amplifier is configured to output an output signal based on the digital intermediate signal. The DPD circuit includes one or more an infinite impulse response (IIR) filters configured to implement a first transfer function based on a first parameter, and a second transfer function based on the first parameter and a time constant. The DPD circuit is configured to generate an adjustment signal based on the first transfer function and the second transfer function. The adaptation circuitry is configured to update the first parameter based on the adjustment signal, the input signal, and the output signal.

Abstract: The motion data monitoring method includes: collecting, by an electronic device, an angular velocity signal and an acceleration signal of a user; obtaining, by the electronic device, a waveform feature of the angular velocity signal based on the angular velocity signal, and obtaining a waveform feature of the acceleration signal based on the acceleration signal; determining, by the electronic device, a gait feature of the user according to the waveform feature of the angular velocity signal and the waveform feature of the acceleration signal, where the gait feature includes a duration of flight from off-ground of a foot of the user to touching of the ground; and determining, by the electronic device, motion data according to the gait feature, where the motion data includes a jump height.

Abstract: A method includes: collecting an original signal in a specified time interval, and performing combined acceleration processing on the original signal to obtain a combined acceleration signal; performing state processing on the combined acceleration signal to obtain a motion time interval, and extracting a plurality of feature groups from the combined acceleration signal according to a preset motion rule; and performing screening on the plurality of feature groups to obtain a first feature group, extracting a median value from the first feature group, and obtaining a stride frequency in the specified time interval based on the median value and a collection frequency, and obtaining a quantity of steps through calculation based on the motion time interval and the stride frequency.

Abstract: Examples described herein provide a radio frequency circuit. The radio frequency circuit includes a controller; a parameter estimator circuit; a capture circuit; and a pre-distorter circuit. The pre-distorter generally includes one or more nonlinear filter circuits and configurable hardware circuitry. Each of the one or more the nonlinear filter circuits includes: adder(s); multiplier(s); and memories coupled to at least one of the adder(s) and the multiplier(s); where the configurable hardware circuitry is configured to distort one or more input signals by directing the one or more input signals along a path through the one or more adders, the one or more multipliers, and the one or more memories and by distorting the one or input signals using the nonlinear parameters stored in the one or more memories as the one or more input signals travels the path.

Abstract: A camera control method includes obtaining a first instruction input by a user, where the first instruction is used to play a movement tutorial in a first application in a terminal device, and controlling, in response to the first instruction, a camera to start and pop up from the terminal device and to obtain an image including a user movement after the camera pops up from the terminal device, where the user movement is a movement made by the user by imitating the movement tutorial.

Abstract: Embodiments of this application provide a target user locking method and an electronic device, and relate to the field of electronic devices. The method provided in this application may be applied to an artificial intelligence (artificial intelligence, AI) fitness scenario, and can ensure accuracy of locking a target user. The electronic device may recognize the target user and track the target user in a fitness process by using a method such as recognizing a user feature, recognizing the user with reference to data collected by a wearable device worn by the user, or recognizing a motion mode of the user.

Abstract: A method includes collecting an original signal in a specified time interval, performing combined acceleration processing on the original signal to obtain a combined acceleration signal, combining n data points of the combined acceleration signal into one data segment, extracting a feature point of the data segment, transforming feature points of all data segments into a feature point signal, analyzing the feature point signal to obtain a stable stage and a fluctuation stage of the feature point signal, performing interference period elimination on the feature point signal with the stable stage and the fluctuation stage according to a specified motion rule to obtain a second feature point signal, and counting a quantity of wave crests of the second feature point signal, where the quantity of wave crests is a quantity of steps.

Abstract: A method includes calculating, based on a first coordinate transformation matrix and a measured value of a gyroscope that corresponds to the ith sampling moment, a second coordinate transformation matrix corresponding to the ith sampling moment, where the first coordinate transformation matrix is a constant matrix, the first coordinate transformation matrix is a coordinate transformation matrix between a sensor coordinate system and a foot coordinate system, the second coordinate transformation matrix is a coordinate transformation matrix between the foot coordinate system and a ground coordinate system, and i is an integer greater than 0, and calculating, based on the first coordinate transformation matrix and the second coordinate transformation matrix corresponding to the ith sampling moment, an attitude matrix corresponding to the ith sampling moment, where the attitude matrix is a coordinate transformation matrix between the sensor coordinate system and the ground coordinate system.

Abstract: A method for calculating a tread frequency of a bicycle includes obtaining a first state of an acceleration signal in a first time window, determining a feature point set from the acceleration signal when the first state includes a riding state, where time distribution of a feature point in the feature point set meets a preset periodic distribution condition, and amplitude meets a physical rule, determining that the first state is the riding state when a feature point subset in the feature point set meets a preset reasonableness condition, and calculating, based on the feature point subset, a quantity of circles and a tread frequency that are in the first time window.

Abstract: Described examples provide for digital communication circuits and systems that implement digital pre-distortion (DPD). In an example, a system includes a DPD circuit configured to compensate an input signal for distortions resulting from an amplifier. The DPD circuit includes an infinite impulse response (IIR) filter configured to implement a transfer function. The IIR filter includes a selection circuit configured to selectively output a selected parameter. The transfer function is based on the selected parameter.