138 results about "Pedestrian navigation" patented technology

A wearable augmented reality computing apparatus with a display screen, a reflective device, a computing device and a head mounted harness to contain these components. The display device and reflective device are configured such that a user can see the reflection from the display device superimposed on the view of reality. An embodiment uses a switchable mirror as the reflective device. One usage of the apparatus is for vehicle or pedestrian navigation. The portable display and general purpose computing device can be combined in a device such as a smartphone. Additional components consist of orientation sensors and non-handheld input devices.

The motion of a pedestrian is evaluated by determining at least one position of at least one identified portion of the pedestrian, projecting the positions(s) on at least one plane, and deriving the motion from the position(s) projected on the at least one plane. Typically the position(s) are determined in three-dimensions, e.g. of the feet. It is possible to project on two different planes to provide three-dimensional navigation information.

The invention discloses a pedestrian navigation device based on an inertial sensor. The pedestrian navigation device comprises a microprocessor, a three-axis acceleration sensor, a three-axis gyroscope, a three-axis magnetometer and a wireless communication module, wherein the three-axis acceleration sensor, the three-axis gyroscope, the three-axis magnetometer and the wireless communication module are respectively connected with the microprocessor; the microprocessor is used for receiving data collected by the three-axis acceleration sensor, the three-axis gyroscope and the three-axis magnetometer and uploading the data to a PC (Personal Computer) through the wireless communication module. The invention further discloses a pedestrian navigation method based on the pedestrian navigation device. The pedestrian navigation method comprises a step stage detection algorithm, a foot and body orientation estimation algorithm and an extended Kalman filter algorithm. The complexity of calculation is greatly reduced while the accuracy is guaranteed, and a condition that the requirement of timeliness can be met is guaranteed without consuming a large amount of hardware power consumption in a practical environment.

The present invention discloses an auto building method and system of a Wi-Fi position fingerprint map. The method comprises the steps of acquiring crowdsourcing data, building the Wi-Fi position fingerprint map by using a pedestrian navigation reckoning method and a machine learning method, and screening according to an indoor map to obtain Wi-Fi strength information with a position tag; and using the Wi-Fi strength information with the position tag as a training sample of a Gaussian process, so as to obtain a function relationship between the signal strength and the position information, resolving a super parameter in the Gaussian process, and predicting according to the super parameter so as to obtain Wi-Fi strength information of a poor constraint area of the indoor map. Regression is performed by using the Gaussian process, the Wi-Fi position fingerprint of a wide area is predicted based on the Wi-Fi position fingerprint information of a high constraint area of the map, so that the Wi-Fi position fingerprint map of the whole indoor area is built automatically.

Methods, systems and apparatuses for enhanced Microelectromechanical (MEMS)-based navigation in a mobile device are disclosed. In an embodiment, a method includes receiving navigation data from one or more navigation sensors on board the mobile device. The method may also include calculating, using a processing device, position, velocity, and attitude (PVA) values in response to the navigation data using an Inertial Navigation System (INS) mechanization. Additionally, the method may include calculating, using the processing device, Pedestrian Dead Reckoning (PDR) values in response to the navigation data. Also, the method may include determining, using the processing device, one or more navigation values in response to a combination of the PVA values calculated by the INS mechanization and the PDR values.

The present invention discloses a method of planning a pedestrian navigation route, and the method is applied to a pedestrian navigation device. The pedestrian navigation device includes a map database having a pedestrian road data and a driving route data of at least one public transportation means. In the method, when the pedestrian navigation device is planning a pedestrian navigation route, the pedestrian navigation device reads start position information and end position information, plans a pedestrian road and a driving route of different public transportation means between a start position and an end position according to a pedestrian road data and a driving route data, and then compiles the same into a pedestrian navigation route. The invention allows a pedestrian to reach an end position (or destination) selectively by walking along the planned pedestrian road or taking a ride of the selected public transportation means.

The invention discloses a wearable autonomous navigation system for a pedestrian and a navigation method thereof. The wearable autonomous navigation system comprises five sensor modules and one comprehensive processing module, wherein the five sensor modules are arranged on the head, arms and feet of the pedestrian respectively; each sensor module comprises a first microcontroller, and an inertial measurement unit, a magnetic sensor, a gas pressure sensor and a first Bluetooth unit which are connected with the first microcontroller respectively; the inertial measurement unit comprises a triaxial accelerometer and a triaxial gyroscope; comprehensive processing module comprises a second microcontroller, and a wireless communication unit, a visual sensor, a satellite receiver, a second Bluetooth unit and a display unit which are connected with the second microcontroller respectively. The five sensor modules acquire a variety of navigation information and transmit the navigation information to the comprehensive processing module, and the variety of navigation information are fused to solve out a navigation result. Based on distributed wearable multi-point information acquisition, data fusion and data filtering are performed according to an inertial navigation method and other navigation methods, so that the pedestrian navigation performance is improved.

The invention discloses an indoor pedestrian navigation-oriented AHRS/UWB (attitude and heading reference system/ultra-wideband) seamless integrated navigation method. The method comprises the following steps: dividing the overall navigation method into a training stage and a prediction stage; adopting a difference value between the position and speed information collected by an AHRS and the position and speed information collected by a UWB as observed quantity of a main data fusion filter under the condition that a UWB signal is normal, and predicting the optimal position, speed and attitude error at the current moment; once the UWB signal is unlocked, conveying the position, speed and attitude information output in the AHRS into an artificial intelligence algorithm as prediction input; through the built mapping relationship, predicting an observation vector of the unlocked main data fusion filter, and ensuring normal working of the main data fusion filter, so that seamless navigation of an overall navigation system is ensured.

The invention relates to a method for programming a pedestrian navigation path, which is applied to a pedestrian navigation device. A map database of the pedestrian navigation device at least comprises walking road data and running route data of at least one public transportation tool. The method comprises that when the pedestrian navigation device is used for programming the pedestrian navigation path, the pedestrian navigation device reads the information of an initial point and an end point, and the method programs running routes of walking roads and various public transportation tools between the initial point and the end point according to the walking road data and the running route data to edit the pedestrian navigation path. The method solves the problem that the prior navigation device programs the pedestrian navigation path only by the walking roads, and achieves the aim that a pedestrian reaches the end point by selectively walking on the walking roads or taking the public transportation tools.

The invention discloses a magnetic course resolving method for indoor pedestrian navigation based on an improved complementary filter. Parameters of a complementary filter are designed in a view of a time domain; an improved complementary filter algorithm model is established; a pedestrian movement mode identification algorithm model is established; and two-dimensional elliptical calibration of a magnetic sensor is utilized for resolving a magnetic course angle of an indoor pedestrian in real time. A low-precision consumer-grade MEMS sensor chip is adopted for ensuring high accuracy of indoor and outdoor course angle and is high in practicability. The MEMS sensor chip is installed in a non-fixed connection manner, is high in installation flexibility, and is not limited by the use environment. The MEMS sensor chip is suitable for a wide scene, is simple and convenient in use method, and ensures high-precision output in a short time.

The invention discloses a pedestrian navigation method based on inertia, magnetic heading and zero-speed correction, which comprises the following steps: (1) measuring linear motion information and angular motion information of a pedestrian by adopting an inertia measurement element, and resolving to obtain attitude, speed and position information of the pedestrian; calculating the three-axis magnetic component measured by a magnetometer to obtain the heading information of the pedestrian; and (2) obtaining a zero-speed state in a walking process through a zero-speed interval detection algorithm, updating an observed quantity of a speed error in the state, establishing a Kalman filtering equation to carry out error correction on pedestrian navigation output in combination with the observedquantity of a course angle error, and finally completing output of corresponding navigation information. Therefore, the magnetic heading angle is calculated by utilizing the three-axis magnetic induction data, and the defects of an inertial navigation system are overcome. In the process, a zero-speed interval is judged by utilizing measurement data of an inertia measurement element, a system error model and a Kalman filtering equation are established, a proper observed quantity is selected, and a state error is estimated.

The invention discloses a pedestrian navigation path planning method and a system thereof. The invention is characterized by based on an electronic map with the pedestrian private facilities, the received initial position and the destination, making a plan of the navigation path by coordinating with the navigation path of the pedestrian private facilities on the road such as zebra crossing, overline bridge or underpasses and combining the electronic map, thereby enabling a user to correctly arrive the destination under the condition of according with the safe and traffic regulation. Additionally, in an embodiment, when the pedestrian position is close to the pedestrian private facilities, a prompt message is send out to remind the pedestrian of walking on the safer pedestrian private facilities to go across the road.

The invention discloses an indoor pedestrian navigation method based on a self-backtracking algorithm. A pedestrian being navigated wears an MEMS sensor. The navigation method comprises the followingsteps: carrying out pedestrian dead reckoning according to an MEMS gyroscope and an MEMS accelerometer to obtain pedestrian walking information during a period of time; carrying out straight line detection on the walking information in the period of time to judge whether the walking route of the pedestrian in the period of time is a straight line; if determining that the pedestrian walks in a straight line, constructing pseudo observed quantity according to heading angle information; carrying out navigation error detection and correction compensation through a forward and backward adaptive kalman filtering algorithm; and outputting a pedestrian indoor navigation and positioning result. By fully exploring the gait characteristics of the pedestrian when walking, the method carries out navigation error estimation and compensation on pedestrian position and attitude information by utilizing walking constraint conditions, thereby realizing a purpose of improving position and posture determination accuracy of the indoor pedestrian navigation scheme based on the motion sensor.

The invention provides an indoor pedestrian navigation attitude estimation method based on a foot-worn inertia measurement unit. The method comprises the following steps: firstly mounting an inertia measurement unit on the foot of the pedestrian, initializing an initial attitude of an inertia measurement unit under a navigation coordinate system, and then judging whether the pedestrian is in a static state according to the output of the inertia sensor; when the pedestrian is in the non-static state, performing attitude updating by adopting the strap-down inertial navigation algorithm, recursing to obtain the current attitude; when the pedestrian is in the static state, constructing a dynamic model, accelerometer output and gravity relation construction measurement model according to the strap-down inertia navigation algorithm attitude updating equation, and updating the current attitude through a Kalman filter under a quaternion frame. The observed quantity is estimated by utilizing the measurement construction attitude of the accelerometer at the static moment, the precise attitude information can be obtained by executing data fusion through the Kalman filter under the quaternionframe, and the technical effect of providing the precise attitude information is provided.

The invention discloses a self-adaptive zero velocity update pedestrian navigation method based on a MEMS sensor. By analyzing gait during people multidirectional movement, based on output of the MEMSsensor under different motion modals, a zero velocity update discrimination algorithm combines with strapdown inertial navigation resolving for correcting information radiated with time of speed position resolved by correction resolution; a self-adaptive zero velocity correction model is established according to practical motion characteristic of pedestrians, and zero velocity discrimination threshold can be changed with real time. The method better solve the radiation problem of speed position of different pedestrians under different motion modals under pure inertia resolving, and self-adaptability and reliability of pedestrian navigation positioning during people multidirectional movement is increased.