Several embodiments of the invention provide for a system and processes for joint entity and object tracking using RFID and a detection network. The use of RFID and a detection network allows for the efficient detection, tracking, and recording of an entity path. Various embodiments of the invention allow the system to track the paths of entities through a space and to monitor the entities' interactions with objects in the space. In addition to tracking entities' paths, the system of some embodiments associates each entity with various objects that each entity interacts with, and uses targeted reads of the associated objects to distinguish and verify the paths associated with each entity. The paths and interactions of the entities with objects in the space are then recorded and analyzed to provide insight about the different entities and about their interactions within the space.

Techniques for predictive user assistance are described. A mobile device can learn movement patterns of the mobile device. The mobile device can construct a state model that is an abstraction of locations where the mobile device stayed for sufficient amount of time. The state model can include states representing the locations, and transitions representing movement of the mobile device between the locations. The mobile device can use the state model, a current location of the mobile device, and a current time to determine a predicted future location of the mobile device at a given future time. Based on the predicted location and the given future time, the mobile device can predict what assistance a user of the mobile device may request. The mobile device can then provide the assistance to the user before the given future time.

A position estimation method for indoor positioning includes filtering an initial position estimate that includes a corresponding covariance that reflects the quality of the geometry of the reference points and a previous initial position estimate that includes a corresponding covariance that reflects the quality of the geometry of the reference points by a Kalman filter to generate an updated previous position estimate, analyzing the updated previous position estimate to determine if the value is outside of a range, and constraining the updated previous position estimate based on the value being outside of the range.

A method of setting up a tracking system of the type including a plurality of spaced-apart stationary nodes for tracking mobile nodes within a tracking environment, the method including using an independent localisation system to determine respective locations of at least a subset of the stationary nodes within the tracking environment.

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.

According to one aspect, a method includes detecting at a vehicle which includes an ultra-wideband (UWB) communications system, a presence of a first device, and pairing the vehicle and the first device, wherein pairing the vehicle and the first device causes the vehicle and the first device to communicate using UWB communications. The method also includes exchanging information between the vehicle and the first device using the UWB communications after the vehicle and the first device are paired, and performing an action using the vehicle, wherein the action is based on the information.

Fault detection for real-time visual-inertial odometry motion tracking. A fault detection system allows immediate detection of error when the motion of a device cannot be accurately determined. The system includes subdetectors that operate independently and in parallel to a main system on a device to determine if a condition exists which results in a main system error. Each subdetector covers a phase of a six-degrees of freedom (6DOF) estimation. If any of the subdetectors detect an error, a fault is output to the main system to indicate a motion tracking failure.

The present disclosure discloses an intelligent device navigation method and navigation system. The method comprises the following. Construct a plurality of antennas on a network card in the intelligent device into a linear antenna array. By using the linear antenna array, acquire channel state information of a wireless signal, and estimate an angle of arrival (AoA) and a time of flight (ToF) between the wireless signal transmitting device and the intelligent device. Measure inertial parameters of the intelligent device. Perform data fusion of the AoAs, the ToFs and the inertial parameters to estimate a state variable of the intelligent device. Adjust a motion state of the intelligent device with reference to the state variable, thereby achieving autonomous navigation of the intelligent device. The disclosure can estimate the state of the intelligent device by using wireless signals ubiquitous in the surrounding environment in a GPS unreliable environment.

A centralized cooperative positioning method includes: caching measurements of nodes in multiple time slices up to the current time slice; calculating location information of the nodes in the multiple time slices to obtain trajectory of the nodes in the multiple time slices; performing initial state estimations of the nodes based on measurements of a single time slice; and using the initial state estimations as initial solution values, performing the joint time-space processing on the measurements of the nodes in the multiple time slices based on trajectory constraints, to obtain a state estimation of each node at the current time slice, in which the state estimation includes an estimated value of a location of the node.

A non-transitory computer-readable recording medium stores therein a program that causes a computer to execute a process. The process includes calculating, for each of a plurality of grids through which a track of a specific vessel passes, an angle of approach and an angle of exit of the track, respectively; extracting a grid for which the angle of approach and the angle of exit conform to a determining condition set for each of the grids based on the determining condition; and determining whether the specific vessel has taken an avoidance behavior based on a relative distance from another vessel corresponding to a position of the specific vessel in a track in the extracted grid.