A method to determine the position of a locomotive (100) by having a first device (306) measuring the electromotive force from a propelling motor (105) and calculating the speed; combined with detection of fixed reference points by measuring of the magnetic field generated by permanent magnets (106) at known positions. At regular intervals this information is passed to a second device (108). By use of a pattern recognition algorithm the second device estimates the position and operates the locomotive according to location-based behavior. The first device characterized by having a magnetic field sensor (302) integrated on an ordinary model railroad decoder, which already supports motor measurement and packet transmission. The second device characterized by having a data packet receiver (403) and an Ethernet interface (405) for communication with a command station (109). A microcontroller (402) utilizes a parameterized representation of the model railroad layout to determine the position of the locomotive. From the position proper behavior is determined and corresponding speed commands are sent to the command station. Other methods and embodiments are described and shown.

A method to determine the position of a locomotive (100) by having a first device (306) measuring the electromotive force from a propelling motor (105) and calculating the speed; combined with detection of fixed reference points by measuring of the magnetic field generated by permanent magnets (106) at known positions. At regular intervals this information is passed to a second device (108). By use of a pattern recognition algorithm the second device estimates the position and operates the locomotive according to location-based behavior. The first device characterized by having a magnetic field sensor (302) integrated on an ordinary model railroad decoder, which already supports motor measurement and packet transmission. The second device characterized by having a data packet receiver (403) and an Ethernet interface (405) for communication with a command station (109). A microcontroller (402) utilizes a parameterized representation of the model railroad layout to determine the position of the locomotive. From the position proper behavior is determined and corresponding speed commands are sent to the command station. Other methods and embodiments are described and shown.

In a distance measurement device, a control unit performs a charge distribution process in which in a first period, charge generated in a charge generation region is transferred to a first charge storage region and, in a second period, the charge generated in the charge generation region is transferred to a second charge storage region. The control unit applies an electric potential to a first overflow gate electrode so that a potential energy of a region immediately below the first overflow gate electrode is lower than a potential energy of the charge generation region in the first period, and applies an electric potential to a second overflow gate electrode so that a potential energy of a region immediately below the second overflow gate electrode is lower than a potential energy of the charge generation region in the second period.

A system and method is provided for determining where a vehicle has parked in a parking lot. The method includes determining a geometry for a parking lot; receiving vehicle event data including periodic vehicle event data for vehicle speed and steering angle; tracking a movement of a vehicle using the vehicle event data; and determining where a vehicle has parked using a steering angle to determine a number of turns in the parking lot geometry.

A heavy goods vehicle includes a displacement calculator that calculates a displacement by multiplying an arc length per unit rotation angle of the outer circumference of a specified tire by the first physical quantity, a vehicle position estimator that estimates a vehicle position using the displacement, and a memory that stores a correlation between a second physical quantity corresponding to a loading weight and an arc length per predetermined rotation angle at the outer circumference of the specified tire. The displacement calculator refers to the correlation to calculate a current arc length per unit rotation angle at the outer circumference of the specified tire from the second physical quantity corresponding to the loading weight, and calculates the displacement by multiplying the first physical quantity detected by the rotation amount detector by the current arc length per unit rotation angle.

An odometer comprises a housing having a vehicle mounting device attached thereto. In an embodiment, the vehicle mounting device configured to be connectable to and removable from the non-odometer equipped vehicle. The housing further comprises a doppler radar module disposed in the housing. A processor is disposed in the housing and operatively connected to the doppler radar module and memory. In turn, the memory comprises executable instructions that, when executed by the processor, cause the processor to receive, from the doppler radar module, velocity-indicative data relative to a surface traveled by the non-odometer equipped vehicle. Thereafter, the processor operates to determine a distance traveled by the non-odometer equipped vehicle based on the velocity-indicative data.

A processing device (120) of a tire state detection system (100) is provided with an acceleration data acquisition unit (123) for acquiring the acceleration data detected by an acceleration sensor (111) at every predetermined acquisition interval, an acceleration data extraction unit (125) for extracting the maximum acceleration data indicating at least the maximum acceleration and the intermediate acceleration data indicating the intermediate acceleration excluding the minimum acceleration data indicating the minimum acceleration from 3 or more acceleration data acquired sequentially, and a calculation unit (127) for executing an calculation using the extracted intermediate acceleration data.

A processing device (120) of a tire state detection system (100) is provided with an acceleration data acquisition unit (123) for acquiring the acceleration data detected by an acceleration sensor (111) at every predetermined acquisition interval, an acceleration data extraction unit (125) for extracting the maximum acceleration data indicating at least the maximum acceleration and the intermediate acceleration data indicating the intermediate acceleration excluding the minimum acceleration data indicating the minimum acceleration from 3 or more acceleration data acquired sequentially, and a calculation unit (127) for executing an calculation using the extracted intermediate acceleration data.

A computer-implemented method 1000 of constructing a model of the motion of a mobile device, wherein the method comprises using a sensor of the device to obtain 1002 positional data providing an estimated pose of the mobile device, generating an initial graph 1004 based upon the positional data from the sensor, nodes of which graph provide a series of possible poses of the device, and edges of which graph represent odometry and/or loop closure constraints; processing the graph to estimate 1006 confidence scores for each loop closure by performing pairwise consistency tests between each loop closure and a set of other loop closures; and generating an augmented graph from the initial graph by retaining or deleting 1008 each loop closure based upon the confidence scores.

A computer-implemented method 1000 of constructing a model of the motion of a mobile device, wherein the method comprises using a sensor of the device to obtain 1002 positional data providing an estimated pose of the mobile device, generating an initial graph 1004 based upon the positional data from the sensor, nodes of which graph provide a series of possible poses of the device, and edges of which graph represent odometry and/or loop closure constraints; processing the graph to estimate 1006 confidence scores for each loop closure by performing pairwise consistency tests between each loop closure and a set of other loop closures; and generating an augmented graph from the initial graph by retaining or deleting 1008 each loop closure based upon the confidence scores.