METHOD AND SYSTEM FOR CREATING INDOOR ENVIRONMENT MAP

• US 20100121488A1
• Filed: 01/22/2010
• Published: 05/13/2010
• Est. Priority Date: 07/23/2007
• Status: Active Grant

• Current Assignee: Electronics and Telecommunications Research Institute
• Original Assignee: Electronics and Telecommunications Research Institute
• Inventors: Na, Sang Ik, Han, Kyu Seo, Yu, Won Pil, LEE, Yu-Cheol
• Granted Patent: US 9,310,807 B2
• Time in Patent Office: Days
• US Class Current: 700/245
• CPC Class Codes: G01C 21/383 Indoor data
• CPC Class Codes: G01C 21/3844 Data obtained from position sensors only, e.g. from inertial navigation
• CPC Class Codes: G01C 21/3881 Tile-based structures
• CPC Class Codes: G05D 1/0231 using optical position detecting means position-fixing by using electromagnetic waves other than radio waves, e.g. optical position detecting means G01S5/16
• CPC Class Codes: G05D 1/024 in combination with a laser lasers per se H01S
• CPC Class Codes: G05D 1/0272 comprising means for registering the travel distance, e.g. revolutions of wheels measuring distance traversed on the ground by vehicles, e.g. using odometers G01C22/00
• CPC Class Codes: G05D 1/0274 using mapping information stored in a memory device navigation using map-matching G01C21/30

Abstract

A method of creating an indoor environment map includes acquiring encoded position information by detecting revolutions of wheels when a mobile unit travels using encoders to predict a position of the mobile unit based on the encoded position information, acquiring a measured distance from the mobile unit to an object existing in a surrounding environment using the distance measuring sensor, predicting a position of the mobile unit to be moved, estimating a distance from the mobile unit to the object at the predicted position of the mobile unit, determining whether the estimated distance is matched with the measured distance, correcting the predicted position of the mobile unit to estimate a position of the mobile unit to be moved by the matching of the predicted position with the measured position, and creating the indoor environment map using the corrected position and the measured distance.

Claims

1. A method of creating an indoor environment map using a mobile unit designed to freely travel by employing a plurality of wheels, the mobile unit having a distance measuring sensor and a plurality of encoders mounted to the corresponding wheels, the method comprising:

acquiring encoded position information by detecting revolutions of the wheels using the encoders to predict a position of the mobile unit based on the encoded position information when the mobile unit travels;

acquiring a measured distance from the mobile unit to an object existing in a surrounding environment using the distance measuring sensor;

predicting a position of the mobile unit to be moved;

estimating a distance from the mobile unit to the object at the predicted position of the mobile unit;

determining whether or not the estimated distance is matched with the measured distance;

correcting the predicted position of the mobile unit to estimate a position of the mobile unit to be moved by the matching of the predicted position with the measured position; and

creating the indoor environment map using the corrected position and the measured distance.

2. The method of claim 1, further comprising synchronizing the predicted position and the measured distance.

3. The method of claim 1, wherein the predicted position are obtained by applying an expanded Kalman filter employing a grid map based on the measured position and the measured distance, wherein the grid map has an estimation detecting grid denoting a position of the object existing in surrounding environment.

4. The method of claim 3, wherein the estimated distance is obtained from the estimation of i-th information from the distance measuring sensor, and a position of the estimation detecting grid, T(k), of the object detected by the i-th information is defined by Equation

T(k)={(x_ti(k),y_ti(k))},

where x_ti(k) and y_ti(k) are an X-axis position and a Y-axis position, respectively, of the object in terms of global coordinate that is detected by the i-th information of the distance measuring sensor.

5. The method of claim 4, wherein, when the distance measuring sensor projects an i-th beam, a measurement model of an estimation detecting grid where a nearest closest object exists is defined by the Equation

h_i(X(k),T(k))=√

{square root over ((x_s(k)−

x_ti(k))²+(y_s(k)−

y_ti(k))²)}{square root over ((x_s(k)−

x_ti(k))²+(y_s(k)−

y_ti(k))²)}{square root over ((x_s(k)−

x_ti(k))²+(y_s(k)−

y_ti(k))²)}{square root over ((x_s(k)−

x_ti(k))²+(y_s(k)−

y_ti(k))²)}

where h_i(X(k),T(k)) is an estimated distance of the i-th beam from the distance measuring sensor;

x_s(k) and y_s(k) represent an X-position and a Y-position of the distance measuring sensor, respectively, in terms of the global coordinate; and

x_ti(k) and y_ti(k) are estimated X-axis and Y-axis positions of an estimated object, respectively, in terms of global coordinate.

6. The method of claim 5, wherein the i-th information estimated by using the measurement model is defined by the Equation

{circumflex over (z)}_i(k+1|k)=h_i({circumflex over (X)}(k+1|k),T(k+1))

where ({circumflex over (z)}_i(k+1k) is an estimated distance of the i-th beam from the sensing unit at a (k+1)-th predicted position of the mobile object, {circumflex over (X)}(k+1|k) is the (k+1)-th predicted position of the mobile object at the k-th position of the mobile object, and T(k+1) is a position of the object detected by the i-th information of the distance measuring sensor at the (k+1)-th predicted position of the mobile object.

7. The method of claim 1, wherein the indoor map comprises a grid map in which the surrounding environment is divided into several grids and probability is assigned to each grid where the object exists.

8. The method of claim 1, further comprising moving the mobile unit to a position corresponding to the measured distance to create the indoor environment map using the moved position and the measured distance, if the predicted position is not matched with the measured position in determining whether the estimated distance is matched with the measured distance.

9. A system for creating an indoor map comprising:

a mobile unit having wheels to freely travel indoors for acquiring a measured distance from the mobile unit to an object existing in a surrounding environment and for acquiring a measured position of the mobile unit when the mobile unit travels;

a position prediction unit for predicting a position of the mobile unit to be moved;

distance estimation unit for estimating a distance from the mobile unit to the object at the predicted position;

a matching determining unit for determining whether or not the estimated distance is matched with the measured distance to estimate a position of the mobile unit to be moved;

a position correcting unit for correcting the predicted position of the mobile unit if it is determined that the predicted position is matched with the measured position; and

a map creating unit for creating the environment indoor map according to the corrected position and the measured distance.

10. The system of claim 9, wherein the mobile unit comprises:

a distance measuring sensor mounted on the mobile unit to measure the distance from the mobile unit to the object to produce the measured distance; and

encoders mounted to the corresponding wheels, respectively, for detecting revolutions of the wheels to produce encoded signals representing the measured position.

11. The system of claim 9, further comprising:

a synchronizer for synchronizing the measured position and the measured distance.

12. The system of claim 9, wherein the position estimation unit employs an expanded Kalman filter to estimate the position of the mobile unit.

13. The system of claim 9, wherein the indoor environment map comprises a grid map in which the surrounding environment is divided into several grids in the form of chessboard and probability is assigned to each grid where the object exists.

14. A method of creating an indoor environment map using a mobile unit designed to freely travel by employing a plurality of wheels, the mobile unit having a distance measuring sensor and a plurality of encoders mounted to the corresponding wheels, the method comprising:

acquiring encoded position information by detecting revolutions of the wheels using the encoders to predict a position of the mobile unit based on the encoded position information when the mobile unit travels;

acquiring a measured distance from the mobile unit to an object existing in a surrounding environment using the distance measuring sensor;

correcting the predicted position by moving the mobile unit to a position corresponding to the measured distance; and

creating the indoor environment map using the corrected position and the measured distance.

15. The method of claim 14, wherein said creating the indoor environment map includes coupling maps created through the use of the distance information at a k-th step and a (k+1)-th step using two points matched between the maps to create the indoor environment map.

16. The method of claim 15, wherein the position of the mobile object at the (k+1)-th step is obtained from the position ([X_k,Y_k,θ

_k] a of the mobile object at the k-th step using the following Equations

$\begin{array}{c}{X}_{k+1}=X_k+\left(x_{k+1}-x_k\right),\\ Y_{k+1}=Y_k+\left(y_{k+1}-y_k\right),<br><br>\mathrm{and}\\ {\mathrm{\theta <br><br>}}_{k+1}={\mathrm{\theta <br><br>}}_k+\left({\tan }^{-1}<br><br>\frac{y_{k+1}^{\mathrm{\prime <br><br>}}-y_{k+1}}{x_{k+1}^{\mathrm{\prime <br><br>}}-x_{k+1}}-{\tan }^{-1}<br><br>\frac{y_k^{\mathrm{\prime <br><br>}}-y_k}{x_k^{\mathrm{\prime <br><br>}}-x_k}\right)\end{array}$

where (x_k,y_k) and (x′

_k,y′

_k) are positions at the two points among the k-th distance information of the mobile object, (x_k+1,y_k+1,θ

_k+1) and (x′

_k+1,y′

_k+1) are the (k+1) -th distance information to be matched with (x_k,y_k) and (x′

_k,y′

_k), X_k, Y_k,θ

_k is the position of the mobile object at the k step, and X_k+1,Y_k+1,θ

_k+1 represents the position of the mobile object at the (k+1)-th step.