A system and method for processing directional feedback. A free form path is received at a server from a first directional interface utilized by a user. The free form path is converted to directional feedback. The free form path is aligned to available paths communicated by the first directional interface utilizing mapping information to generate the directional feedback. The directional feedback is sent from the server to one or more directional interfaces utilized by one or more users associated with the first directional interface.

The disclosure describes systems (2) of navigating a hazardous environment (8). The system includes personal protective equipment (PPE) (13) and computing device(s) (32) configured to process sensor data from the PPE (13), generate pose data of an agent (10) based on the processed sensor data, and track the pose data as the agent (10) moves through the hazardous environment (8). The PPE (13) may include an inertial measurement device to generate inertial data and a radar device to generate radar data for detecting a presence or arrangement of objects in a visually obscured environment (8). The PPE (13) may include a thermal image capture device to generate thermal image data for detecting and classifying thermal features of the hazardous environment (8). The PPE (13) may include one or more sensors to detect a fiducial marker (21) in a visually obscured environment (8) for identifying features in the visually obscured environment (8). In these ways, the systems (2) may more safely navigate the agent (10) through the hazardous environment (8).

Estimating a difference in height between floors in a building for use in estimating a height or an altitude of one of the floors. A height difference is estimated between a first floor and a second floor based on outdoor temperatures of first and second time periods, an indoor temperature of the first or second time period, and first and second estimated differences in height between the first and second floors that is based on measurements of pressure from mobile devices when the mobile devices were on the first and second floors during the first and second time periods.

A computing device equipped with a camera may be used to assist a person in planning and traversing exit routes for a premises. For example, a user may be able to interact with one or more user interfaces generated by the computing device to determine an exit route for the premises. The user may be able to identify various objects, such as stairs or doors, along the exit route. The user may be able to identify graphical or textual information that can be displayed at certain points along the exit route. After determining the exit route, a data structure for the exit route may be shared with other users and/or be used to assist a user in traversing the exit route. For example, the data structure may be used as a basis for overlaying graphics and/or text on a real-time video display as the user traverses the exit route.

An electronic device may include a magnetic sensor and at least one processor operatively connected with the magnetic sensor, wherein the at least one processor may be configured to: collect a plurality of pieces of path data based on first magnetic data related to a plurality of movements of the electronic device, by using the magnetic sensor; identify a plurality of pieces of second magnetic data, which have at least a predetermined level of mutual similarity, from among the plurality of pieces of path data; determine, to be an intersection area related to the plurality of movements of the electronic device, an area range in which the plurality of pieces of second magnetic data are collected; determine, on the basis of the intersection area, a first space and a second space related to the plurality of movements of the electronic device; and determine, on the basis of the third magnetic data acquired by using the magnetic sensor, the space in which the electronic device is located from among the first space and the second space.

A method and a device for target finding are disclosed. The method for target finding includes collecting user demand information, determining the target according to user demand information, acquiring user position information and position information of the target, generating navigation information according to the position information of the target and the user position information, and outputting the navigation information.

A processor coupled to memory is configured to receive an identification of a geographical location associated with a target specified by a user remote from a vehicle. A machine learning model is utilized to generate a representation of at least a portion of an environment surrounding the vehicle using sensor data from one or more sensors of the vehicle. At least a portion of a path to a target location corresponding to the received geographical location is calculated using the generated representation of the at least portion of the environment surrounding the vehicle. At least one command is provided to automatically navigate the vehicle based on the determined path and updated sensor data from at least a portion of the one or more sensors of the vehicle.

A positioning system and a method based on neural network models are provided. The positioning method includes collecting WI-FI® fingerprint data; configuring a computing device to receive the WI-FI® fingerprint data, and the computing device includes a processor and a database storing positioning map data and a group of neural network models including a global positioning model, a coarse positioning model and a fine positioning model; configuring the processor to input the WI-FI® fingerprint data and perform the following steps: estimating a global coordinate through the global positioning model; obtaining the corresponding coarse positioning model from a corresponding primary sub-region to estimate an estimated coarse coordinate of a current position; estimating a plurality of estimated fine coordinates of the current position from the corresponding fine positioning model; and performing a merging process on the estimated fine coordinates to generate a final coordinate.

A robot that is able to move about an environment determines a wait location in the environment to wait at when not otherwise in use. The wait location may be selected based on various factors including position of objects, next scheduled use, previous usage of the robot, availability of wireless connectivity, user traffic patterns, user presence, visibility of the surrounding environment, and so forth. The robot moves to that location and maintains a pose at that location, such as orienting itself to allow onboard sensors a greatest possible view of the environment. If a wait location is occupied, the robot may move to another wait location.

An own-position estimating device for estimating an own-position of a moving body by matching a feature extracted from an acquired image with a database in which position information and the feature are associated with each other in advance, includes an evaluation result acquiring unit acquiring an evaluation result obtained by evaluating matching eligibility of the feature in the database, and a processing unit processing the database on the basis of the evaluation result acquired by the evaluation result acquiring unit.