A localization device configured to consecutively estimate a location of an own vehicle based on behavior of the own vehicle and configured to correct the estimated location by making reference to a landmark in a vicinity of the own vehicle includes a calculation unit configured to calculate an index related to a self-location based on a displacement error of the own vehicle and a changing unit configured to change a determination criterion for identifying the landmark based on the index.

An estimation includes a dead reckoning unit, a map matching unit, and a parameter correction unit. The dead reckoning unit is configured to estimate a state quantity by dead reckoning based on (i) a dynamics model including a parameter that changes a behavior of the vehicle and (ii) internal information acquired from an inside of the vehicle. The map matching unit is configured to observe the state quantity by map matching based on (i) map information indicative of a traveling environment of the vehicle and (ii) external information acquired from an outside of the vehicle. The parameter correction unit is configured to correct the parameter, which is to be fed back for the dead reckoning, based on an offset amount that is a difference between the state quantity observed by the map matching and the state quantity estimated by the dead reckoning.

Training at the proper level of effort is important for athletes whose objective is to achieve the best results in the least time. In running, for example, pace is often monitored. However, pace alone does not reveal specific issues with regard to running form, efficiency, or technique, much less inform how training should be modified to improve performance or fitness. A sensing system and wearable sensor platform described herein provide real-time feedback to a user/wearer of his power expenditure during an activity. In one example, the system includes an inertial measurement unit (IMU) for acquiring multi-axis motion data at a first sampling rate, and an orientation sensor to acquire orientation data at a second sampling rate that is varied based on the multi-axis motion data.

The present disclosure discloses a method for planning a path of a mobile robot including an odometer and a gyroscope. The method includes causing the mobile robot to move from an initial position to a point Pi or a point P′i, calibrating data of the odometer and/or the gyroscope at the point Pi or the point P′i, and repeating S′1 to step S′2 until arriving at a final target point.

An approach to determining vehicle usage makes use of a sensor that provides a vibration signal associated with the vehicle, and that vibration signal is used to infer usage. Usage can include distance traveled, optionally associated with particular ranges of speed or road type. In a calibration phase, auxiliary measurements, for instance based on GPS signals, are used to determine a relationship between the vibration signal and usage. In a monitoring phase, the determined relationship is used to infer usage from the vibration signal.

Disclosed is a positioning system including: several inertial measurement units; at least one common sensor, providing a measurement of a positioning parameter of a system; for each inertial measurement unit, a navigation filter configured to: a) determine an estimate of the positioning parameter, on the basis of an inertial signal provided by the inertial measurement unit; and to b) correct the estimate, as a function of the measurement and of a correction gain that is determined on the basis of an augmented variance higher than the variance of a measurement noise of a common sensor; and—at least one fusion module determining a mean of the estimates, the mean being not reinjected at the input of the navigation filters. Also disclosed is an associated positioning method.

Dead reckoning correction utilizing patterned light projection is provided herein. An example method can include navigating a drone along a pattern using dead reckoning, the pattern having a plurality of lines, detecting one of the plurality of lines using an optical sensor of the drone, determining when a line of travel of the drone is not aligned with the one of the plurality of lines, and realigning the line of travel of the drone so as to be aligned with the one of the plurality of lines to compensate for drift that occurs during navigation using dead reckoning.

A correction method for a gyro sensor which measures angular velocity of a vehicle about an axis in a vertical direction includes a generation process of performing a process on a difference between a measured azimuth obtained by performing a process on an sensor output, which is an output from the gyro sensor, and a vehicle azimuth estimated by using markers arranged along a traveling road of the vehicle to obtain correction information and a correction process of correcting the measured azimuth obtained by performing the process on the sensor output, which is the output from the gyro sensor, by using the correction information.

A vehicle traveling control method for causing a vehicle to travel along a traveling road where magnetic markers are arrayed is a control method including an azimuth measuring process of performing a process on angular velocity, which is an output of a gyro sensor, and measuring a measured azimuth indicating an orientation of the vehicle, a control process of controlling the vehicle so that the measured azimuth is matched with a target azimuth corresponding to a direction of the traveling road, and a correction process of correcting a degree of control by the control process, in order to bring a lateral shift amount of the vehicle with reference to each of the magnetic markers closer to zero, in accordance with the lateral shift amount.

A method for determining the position and orientation of a vehicle includes constructing, for several instants t.sub.k ranging between instants to.sub.j−1 and to.sub.j, an estimate of the instantaneous value of the physical quantity on the basis of the measurements of an inertial navigation unit; constructing an estimate of the physical quantity for the instant to.sub.j by computing the arithmetic mean of the constructed instantaneous values; computing a deviation between a measurement of the physical quantity obtained on the basis of the measurement of an odometer and an estimate of the physical quantity at the instant to.sub.j; and correcting, as a function of the deviation computed for the instant to.sub.j, estimated positions and orientations of the vehicle, in order to obtain a corrected position and a corrected orientation.