Method, systems, and computer-readable media containing instructions which, when executed by a computing device, cause it to receive data from an inertial measurement unit, including GPS data, velocity data, and bearing data, receive data from a digital magnetic compass, including bearing data, receive data from a Doppler sensor, including velocity data and distance data, determining whether GPS location data is in consensus with a previous derived multi-source reckoning system location, determining a consensus distance value from a weighted average of data from the inertial measurement unit and the Doppler sensor, determine a consensus heading value from a weighted average of data from the inertial measurement unit and the digital magnetic compass, determine a consensus geolocation value from a weighted average of data from the inertial measurement unit and the previous derived multi-source reckoning system location, and determine a derived multi-source reckoning system location.

A system and method for providing localization, including, during a training phase: obtaining a training dataset of accelerations, angular velocities, and known locations over time of vehicles moving in a defined area; and training a machine learning model to provide location estimation in the defined area based on the accelerations and angular velocities using the training dataset; and during runtime phase: obtaining runtime accelerations and angular velocities overtime of a vehicle moving in the defined area; and using the trained model to obtain current location of the vehicle based on the runtime acceleration and angular velocities.

A method for identifying a static phase of a vehicle involves a first step of detecting the static phase without using measurements of a satellite geolocation unit, this first detection step involving checking that a first set of one or more conditions is satisfied, checking, repeatedly, that a second set of one or more conditions is satisfied, then so long as the second set of conditions is satisfied, executing a second step of detecting the static phase from the measurements of the satellite geolocation unit, so long as the second set of conditions is not satisfied, executing the first detection step and inhibiting the execution of the second detection step.

A method for identifying a static phase of a vehicle involves a first step of detecting the static phase without using measurements of a satellite geolocation unit, this first detection step involving checking that a first set of one or more conditions is satisfied, checking, repeatedly, that a second set of one or more conditions is satisfied, then so long as the second set of conditions is satisfied, executing a second step of detecting the static phase from the measurements of the satellite geolocation unit, so long as the second set of conditions is not satisfied, executing the first detection step and inhibiting the execution of the second detection step.

In one embodiment, method performed by an autonomous driving vehicle (ADV) that determines, within a driving space, a plurality of routes from a current location of the ADV to a desired location. The method determines, for each route of the plurality of routes, an objective function to control the ADV autonomously along the route and, for each of the objective functions, performs Differential Dynamic Programming (DDP) optimization in view of a set of constraints to produce a path trajectory. The method determines whether at least one of the path trajectories satisfies each constraint and, in response to a path trajectory satisfying each of the constraints, selects the path trajectory for navigating the ADV from the current location to the desired location.

An image capturing apparatus comprising: an image capturing unit; a sound collecting unit; a detecting unit for detecting sound pressure level of a voice sound collected by the sound collecting unit, a recognizing unit for recognizing that a voice sound collected by the sound collecting unit is an instruction for shooting by the image capturing unit; and a control unit, wherein the control unit controls the image capturing unit to shoot in response that the detecting unit detects sound pressure level of a voice sound collected by the sound collecting unit is larger than a predetermined sound pressure level, and that the recognizing unit recognizes the voice sound as an instruction for shooting by the image capturing unit.

A method and apparatus for improving a dead reckoning estimate of a mobile unit is described. When an accurate position cannot be determined for a mobile unit, for example if GPS is unavailable, a dead reckoning estimate can be improved when two or more mobile units share their position estimates and the shared position estimates are used with either the range between the two units or knowledge that the units are within a threshold distance of each other to refine the position estimate of at least one unit.

A method and apparatus for improving a dead reckoning estimate of a mobile unit is described. When an accurate position cannot be determined for a mobile unit, for example if GPS is unavailable, a dead reckoning estimate can be improved when two or more mobile units share their position estimates and the shared position estimates are used with either the range between the two units or knowledge that the units are within a threshold distance of each other to refine the position estimate of at least one unit.

The present disclosure relates to augmented reality, virtual reality, mixed reality, and extended reality systems, and more specifically, to systems and methods for a visual positioning system.

The present disclosure relates to augmented reality, virtual reality, mixed reality, and extended reality systems, and more specifically, to systems and methods for a visual positioning system.