A network system uses Wi-Fi signals or other types of short-range transmissions to determine pickup locations for users receiving services provided via the network system. The network system builds a database of search records mapping pickup locations to signatures of short-range transmission detected by users' client devices when they searched for the pickup locations. By comparing a signature detected by a given user's client device to the signatures in the database, the network system can check for similarities between the short-range transmissions. Responsive to finding a match, the network system predicts that the given user is likely to select a similar pickup location as other users whose client devices detected the signatures corresponding to the match. Accordingly, by leveraging the database, the network system can predict pickup locations without requiring the given user to input a search for a pickup location.

The present disclosure discloses a path planning method and device and a mobile device. The method comprises: collecting environmental information in a viewing angle by a sensor of a mobile device, processing the environmental information by using an SLAM algorithm, and constructing a grid map; dividing the grid map to obtain a plurality of pixel blocks, using an area constituted of pixel blocks not occupied by obstacles as a search area for path planning, and obtaining a processed grid map; determining reference points by using pixel points in the search area, and deploying topological points on the processed grid map according to the reference point determined and constructing a topological map; and calculating an optimal path from a starting point to a preset target point by using a predetermined algorithm according to the topological map constructed. The present disclosure improves path planning efficiency and saves storage resources.

Disclosed are various examples for augmented reality based image protection in enterprise settings. In one example, a managed camera application can generate an artificial reality based camera user interface using image data from a field of view of a camera. An indoor position can be identified using global positioning system (GPS) and indoor positioning data. A sector of the field of view can be identified as a protected image area that depicts a protected or confidential object, and the user interface can be updated to include an AR user interface element that is generated relative to the protected image area that is identified.

A system for usage guidance using wireless communication includes a portable computing device, wherein the portable computing device is designed and configured to wirelessly receive a signal from a wireless signal generator located at an item, parse the first signal for at least a textual element, extract a signal generator class identifier from at least a textual element, identify a remote data structure as a function of the signal generator identifier, retrieve, from the remote data structure, at least an identifier-specific datum, and generate identifier-specific usage guidance as a function of the at least an identifier-specific datum. The system includes a user output component coupled to the portable computing device, wherein the user output component is configured to provide the identifier-specific usage guidance to the user.

An example control system includes a memory and at least one processor to obtain image data from a given region and perform image analysis on the image data to detect a set of objects in the given region. For each object of the set, the example control system may classify each object as being one of multiple predefined classifications of object permanency, including (i) a fixed classification, (ii) a static and fixed classification, and/or (iii) a dynamic classification. The control system may generate at least a first layer of a occupancy map for the given region that depicts each detected object that is of the static and fixed classification and excluding each detected object that is either of the static and unfixed classification or of the dynamic classification.

A system for usage guidance using wireless communication includes a portable computing device, wherein the portable computing device is designed and configured to receive a signal from a first transmitter, parse the signal for at least a textual element, identify, in a first data structure, a first location and a second location of the signal, retrieve, from a second data structure, a usage data, and generate identifier-specific usage guidance as a function of the first location and the second location of the signal and the usage data. The system includes a user output component coupled to the portable computing device, wherein the user output component is configured to provide the identifier-specific usage guidance to a user.

A system and method for measuring three-dimensional (3D) coordinate values of an environment is provided. The system includes a movable base unit a first scanner and a second scanner. One or more processors performing a method that includes causing the first scanner to determine first plurality of coordinate values in a first frame of reference based at least in part on a measurement by at least one sensor. The second scanner determines a second plurality of 3D coordinate values in a second frame of reference as the base unit is moved from a first position to a second position. The determining of the first coordinate values and the second plurality of 3D coordinate values being performed simultaneously. The second plurality of 3D coordinate values are registered in a common frame of reference based on the first plurality of coordinate values.

Centerlines for generating network data of an indoor space can be simplified while the amount of calculation is limited. A centerline simplification unit 240 performs processing of deleting centerlines of passages that are movable regions in an indoor space and processing of correcting centerlines. A determination unit 242 determines whether or not the simplification has ended based on the number of centerlines or the number of vertices connecting the centerlines.

The present disclosure relates to an indoor monocular navigation method based on cross-sensor transfer learning and a system thereof. Determining an preliminary autonomous navigation model according to simulated laser radar data; acquiring actual single-line laser radar data and monocular camera data of the mobile robot simultaneously in an actual environment; determining the heading angle of the mobile robot according to the actual laser radar data; determining a laser radar monocular vision navigation model, according to the generated heading angle of the mobile robot and the monocular camera data at a the same moment and by using a Resnet18 network and a pre-trained YOLO v3 network; determining a heading angle of the mobile robot at the current moment, according to the acquired monocular camera data and by using the laser radar monocular vision navigation model; performing navigation of the mobile robot.

A method of operating a user terminal includes receiving occupancy data for an operating environment responsive to navigation of the operating environment by a mobile robot, and displaying a visual representation of the operating environment based on the occupancy data. The method flintier includes receiving information identifying a plurality of electronic devices that are local to the operating environment and respective operating states thereof, and populating the visual representation of the operating environment with visual indications of respective spatial locations of the electronic devices in the operating environment and status indications of the respective operating states of the electronic devices. Related methods for controlling the electronic devices based on their respective spatial locations and the relative spatial context of the operating environment are also discussed.