Abstract: The invention discloses a multi-threshold segmentation method for medical images based on an improved salp swarm algorithm. A two-dimensional histogram is established by means of a grayscale image of a medical image and a non-local mean image, then a salp swarm algorithm is used to determine thresholds selected by a Kapur entropy-based threshold method, and the salp swarm algorithm is improved and mutated by an individual-linked mutation strategy during the threshold selection process to avoid local optimization, so that the segmentation effect on the medical image is optimized; and the method has the advantages of good robustness and high accuracy.

Abstract: A method includes obtaining signal information based on wireless signals communicated between an electronic device and a target device. The method also includes obtaining motion information based on movement of the electronic device. The method further includes identifying first location information based on the signal information, the first location information indicating whether the target device is within a field of view (FoV) of the electronic device. Additionally, the method includes identifying second location information based on the motion information and the signal information, the second location information indicating whether the target device is within the FoV of the electronic device. The method also includes determining that the target device is within the FoV or outside the FoV of the electronic device based on at least one of the first location information or the second location information.

Abstract: An electronic device includes a first set of sensors configured to generate motion information. The electronic device also includes a second set of sensors configured to receive information from multiple anchors. The electronic device further includes a processor configured to generate a path to drive the electronic device within an area. The processor is configured to receive the motion information. The processor is configured to generate ranging information based on the information that is received. While the electronic device is driven along the path, the processor is configured to identify a location and heading direction within the area of the electronic device based on the motion information. The processor is configured to modify the estimate of location and the heading direction of the electronic device based on the ranging information. The processor is configured to drive within the area according to the path, based on the location and heading direction.

Abstract: A method includes identifying a first anchor of a plurality of anchors as an initiator and identifying multiple second anchors of the plurality of anchors as multiple responders, the plurality of anchors located in a service area to be traversed by a robot. The method also includes sending, to the initiator and the responders via a wireless side-link, ranging information and a command to start ultra-wideband (UWB) ranging. The method also includes receiving, from the initiator via the wireless side-link, pair-wise range measurements representing UWB range measurements between the initiator and the responders. The method also includes generating initial location values for the initiator and the responders based on the pair-wise range measurements and one or more geometric constraints imposed on the initiator and the responders. The method also includes estimating 3D coordinates of the initiator and the responders using the initial location values.

Abstract: A method includes obtaining signal information based on wireless signals received from an external electronic device via a first antenna pair and a second antenna pair. The first and second antenna pairs are aligned along different axes. The signal information includes channel information, range information, a first angle of arrival (AoA) based on the first antenna pair, and a second AoA based on the second antenna pair. The method also includes generating an initial prediction of a presence of the external electronic device relative to a field of view (FoV) of the electronic device. The method further includes performing a smoothing operation on the range information and the first and second AoA, the smoothing operation generating a predicted location of the external electronic device relative to the FoV of the electronic device. Additionally, the method includes generating, based on the smoothing operation, confidence values associated with the predicted location.

Abstract: A method includes obtaining channel information, range information, and angle of arrival (AoA) information based on wireless signals communicated between an electronic device and an external electronic device. The method also includes generating an initial prediction of a presence of the external electronic device relative to a field of view (FoV) of the electronic device based on the channel information and at least one of the range information or the AoA information. The initial prediction includes an indication of whether the external electronic device is within the FoV or outside the FoV of the electronic device. The method further includes performing, using a tracking filter, a smoothing operation on the range information and the AoA information. Additionally, the method includes determining that the external electronic device is within the FoV of the electronic device based on the AoA information, the smoothed AoA information, and the initial prediction.

Abstract: A three-dimensional (3D) printing system is provided. The printing system includes a resin tank assembly with a sliding scraper, an automatic resin dispensing system, sensors configured to measure various aspects of the system, e.g., the volume of resin within the resin tank and/or within the resin dispensing system, a rigid releasable interface between the lift arm and the build platform, a resin heating system, a magnetic interface between the resin tank and the base assembly, a resin tank locking system, and other novel aspects.

Abstract: The present disclosure presents aerial communication systems and methods. One such system comprises an unmanned aerial vehicle platform and a communication component integrated with the unmanned aerial vehicle platform, wherein the communication component is configured to establish an Air to Air (A2A) communication channel with a remote directional antenna that is integrated with a remote unmanned aerial vehicle platform. The system further includes a computing component integrated with the unmanned aerial vehicle platform, wherein the computing component is configured to determine an optimal heading angle for transmission of communication signals from a directional antenna to the remote directional antenna in an unknown communication environment from received signal strength indicator (RSSI) information obtained from the remote directional antenna. Other systems and methods are also disclosed.

Abstract: A method includes, when a handheld device is in motion within a service area to be traversed by a robot: obtaining ultra-wideband (UWB) ranging measurements between the handheld device and multiple anchors located in the service area; and obtaining image data and inertial measurement unit (IMU) data. The method also includes determining a trajectory of motion of the handheld device based on the UWB ranging measurements. The method also includes adjusting the trajectory based on image features obtained from the image data and motion estimates obtained from the IMU data. The method also includes identifying the adjusted trajectory as a boundary of the service area.

Abstract: An electronic device includes a transceiver and a processor. The processor is operably connected to the transceiver. The processor is configured to transmit, via the transceiver, radar signals for activity recognition. The processor is also configured to identify a first set of features and a second set of features from received reflections of the radar signals, the first set of features indicating whether an activity is detected based on power of the received reflections. Based on the first set of features indicating that the activity is detected, the processor is configured to compare one or more of the second set of features to respective thresholds to determine whether a condition is satisfied. After a determination that the condition is satisfied, the processor is configured to perform an action based on a cropped portion of the second set of features.

Abstract: A method includes obtaining signal information based on wireless signals received from an external electronic device via a first antenna pair and a second antenna pair. The first and second antenna pairs are aligned along different axes. The signal information includes channel information, range information, a first angle of arrival (AoA) based on the first antenna pair, and a second AoA based on the second antenna pair. The method also includes generating an initial prediction of a presence of the external electronic device relative to a field of view (FoV) of the electronic device. The method further includes performing a smoothing operation on the range information and the first and second AoA, the smoothing operation generating a predicted location of the external electronic device relative to the FoV of the electronic device. Additionally, the method includes generating, based on the smoothing operation, confidence values associated with the predicted location.

Abstract: A method includes obtaining signal information based on wireless signals communicated between an electronic device and a target device. The method also includes obtaining motion information based on movement of the electronic device. The method further includes identifying first location information based on the motion information and the channel information. Additionally, the method includes identifying second location information based on the orientation of the electronic device and the AoA information. The method also includes determining whether the electronic device is in motion. The method further includes determining whether the target device is within the FoV or outside the FoV of the electronic device based in part on the first location information in response to determining that the electronic device is not in motion or the second location information in response to determining that the electronic device is in motion.

Abstract: A method includes obtaining signal information based on wireless signals communicated between an electronic device and a target device. The method also includes obtaining motion information based on movement of the electronic device. The method further includes identifying first location information based on the signal information, the first location information indicating whether the target device is within a field of view (FoV) of the electronic device. Additionally, the method includes identifying second location information based on the motion information and the signal information, the second location information indicating whether the target device is within the FoV of the electronic device. The method also includes determining that the target device is within the FoV or outside the FoV of the electronic device based on at least one of the first location information or the second location information.

Abstract: A method includes obtaining channel information, range information, and angle of arrival (AoA) information based on wireless signals communicated between an electronic device and an external electronic device. The method also includes generating an initial prediction of a presence of the external electronic device relative to a field of view (FoV) of the electronic device based on the channel information and at least one of the range information or the AoA information. The initial prediction includes an indication of whether the external electronic device is within the FoV or outside the FoV of the electronic device. The method further includes performing, using a tracking filter, a smoothing operation on the range information and the AoA information. Additionally, the method includes determining that the external electronic device is within the FoV of the electronic device based on the AoA information, the smoothed AoA information, and the initial prediction.

Abstract: The present disclosure presents aerial communication systems and methods. One such system comprises an unmanned aerial vehicle platform and a communication component integrated with the unmanned aerial vehicle platform, wherein the communication component is configured to establish an Air to Air (A2A) communication channel with a remote directional antenna that is integrated with a remote unmanned aerial vehicle platform. The system further includes a computing component integrated with the unmanned aerial vehicle platform, wherein the computing component is configured to determine an optimal heading angle for transmission of communication signals from a directional antenna to the remote directional antenna in an unknown communication environment from received signal strength indicator (RSSI) information obtained from the remote directional antenna. Other systems and methods are also disclosed.

Abstract: An electronic device includes a Lidar sensor, a radar sensor, and a processor. The processor is configured to identify one or more objects from Lidar scans. The processor is configured to transmit, via the radar sensor, radar signals for object detection based on reflections of the radar signals received by the radar sensor. While the electronic device travels the area, the processor is configured to generate a first map indicating one or more objects within an area based on the Lidar scans and a second map based on the radar signals. The processor is configured to determine whether the second map indicates a missed object at the portion of the first map that is unoccupied. In response to a determination that the second map indicates the missed object, the processor is configured to modify the first map with the missed object.

Abstract: An electronic device includes a first set of sensors configured to generate motion information. The electronic device also includes a second set of sensors configured to receive information from multiple anchors. The electronic device further includes a processor configured to generate a path to drive the electronic device within an area. The processor is configured to receive the motion information. The processor is configured to generate ranging information based on the information that is received. While the electronic device is driven along the path, the processor is configured to identify a location and heading direction within the area of the electronic device based on the motion information. The processor is configured to modify the estimate of location and the heading direction of the electronic device based on the ranging information. The processor is configured to drive within the area according to the path, based on the location and heading direction.