UWB and lidar assisted indoor mapping and exploration method

Abstract

The invention relates to a UWB (Ultra Wide Band) and LIDAR based environment mapping, exploration and positioning method for indoor environments. More particularly, the invention relates to an exploration and mapping method tor positioning and mapping an environment in which an autonomous vehicle or a human carrier with a UWB module and a LIDAR module enters for the first time. It relates to a method for precise positioning in long tunnels or cave-dike areas with UWB units left at certain intervals while the autonomous vehicle or human carrier is travelling in a confined space (e.g. a cave), while at the same time mapping its position with a LIDAR.

Description

[0001] UWB AND LIDAR ASSISTED INDOOR MAPPING AND EXPLORATION METHOD

[0002] Technical Field

[0003] The invention relates to a UWB (Ultra Wide Band) and LIDAR based environment mapping, exploration and positioning method for indoor environments.

[0004] More particularly, the invention relates to an exploration and mapping method for positioning and mapping an autonomous vehicle or transporter equipped with a UWB module and LIDAR in an environment entered by a human for the first time. It relates to a method in which the autonomous vehicle or human transporter, while travelling In a confined space (for example, a cave), performs precise positioning in long tunnels or cave-like areas with UWB units left at certain intervals, while simultaneously mapping its position with LIDAR

[0005] Prior Art

[0006] In current use, inertial measurements and LIDAR sensors are used for simultaneous mapping and positioning with particle filtering Simultaneous mapping and positioning using inertial measurements and LIDAR sensors with panicle filtering requires high memory usage. In addition, if the LIDAR bea cannot detect the corner points (due to low resolution), the algorithm precision and accuracy rate decrease significantly. During two-dimensional mapping, the distances measured by LIDAR are inconsistent due to the LIDAR orientation, making position measurement and mapping difficult.

[0007] In addition, there are applications where landmarks are identified with electro- optical cameras and positioning is performed by tracking these points and at the same time combining them with inertial measurements and blind navigation. Electro-optical cameras are light-sensitive systems whose performance varies according to the ambient lighting, require high processing power and cannot perform positioning and mapping in stationary situations,

[0008] CN i 146743 M A discloses a method for mapping the indoor environment using UWB and LIDAR (SLAM).

[0009] CN115077519A discloses a method for mapping the indoor environment using LIDAR (SLAM).

[0010] During two-dimensional mapping, there is a need to develop a method in which the inconsistencies in the distances measured by LIDAR due to LIDAR orientation are eliminated and thus location measurement and mapping become easier and more accurate.

[0011] Objectives and Brief Description of the Invention

[0012] The object of the present invention is to develop a method that enables the correction of the errors arising from two and three dimensional measurements in LIDAR measurements and positioning problems caused by the inability to capture corner points with the precise position estimation provided by UWB units.

[0013] Thanks to the inventive method, it will be possible to correct the errors in LIDAR measurements and positioning problems caused by the failure to capture corner points with the precise position estimation provided by UWB units.

[0014] Detailed Description of the Invention

[0015] A system utilizing the method for achieving the object of the present invention is shown in the attached figures. Figure I . A schematic view of a system utilizing the inventive method

[0016] Figure 2: A schematic view of the elements on the mapping device used in the inventive method.

[0017] Figure 3. Flow diagram of the inventive method.

[0018] 5 Figure 4. Flow diagram of the sensor fusion in the inventive method.

[0019] The parts in the figures are numbered individually, and the corresponding descriptions are given below.

[0020] 1. UWB positioning anchors

[0021] 2. Mapping device

[0022] P 3. LIDAR coverage area

[0023] 4 Distance and angle measurement with UWB positioning anchors

[0024] 5. UWB positioning unit

[0025] 6. LIDAR

[0026] 7. Inertial measurement unit

[0027] 5 8 Accompanying computer

[0028] 9. Route followed for exploration

[0029] The inventive method comprises,

[0030] Placing the first UWB positioning anchor (1) at the entrance to the indoor space,

[0031] 0 ■- Performing distance and angle measurements (4) within the range of the

[0032] UWB positioning anchor (1 ) with the UWB positioning unit (5) on the mapping device (2), measuring the environment by performing 360° distance measurements with LIDAR (6), collecting data with inertial measurement unit (7 ),

[0033] 5 ■- Processing of this data on the accompanying computer (8), Converting the collected data into position data by means of Kalman blind navigation filter, particle filter and kinematic equations,

[0034] Grouping these three position data as binary combinations in the accompanying computer (8), - Giving binary combinations as input to Kalman filters separately,

[0035] Calculating the covariance values of the binary combination results obtained from Kal n filters,

[0036] - Predicting that the data produced by all sensor subsystems are healthy, if the covariance values of the results of each binary combination are low, - Predicting the information produced by the sensor subsystem discrete in the input of the Kalman filter with low covariance is inaccurate, if the covariance of other filters other than one filter is high,

[0037] - Positioning the second UWB positioning anchor (1) within line of sight of the first UWB positioning anchor (1), when moving out of range (line of sight) of the first UWB positioning anchor ( 1 ),

[0038] Performing distance and angle measurements (4) within the range of the second UWB positioning anchor ( I ) with the UWB positioning unit (5), measuring the environment with LIDAR (6), collecting data with inertial measurement unit (7) and continuing mapping. The invention is a method utilizing a mapping device (2) carried by an autonomous vehicle or a human. It has been developed for the purpose of mapping an unknown environment. The mapping device (2) to be used in the inventive method comprises a UWB positioning unit (5), a LIDAR (6), an inertial measurement unit (7) and an accompanying computer (8). The method according to the invention starts to operate when the mapping device (2) and the first fixed UWB positioning anchor (1) are placed and powered. As long as there is communication between the UWB positioning anchor (1) and the UWB positioning unit (5) on the mapping device (2), distance and angle measurement (4) can be performed with the UWB unit. As long as this condition is not broken, the mapping device (2) knows its position accurately and takes measurements from the LIDAR (6), inertial measurement unit (7) and UWB positioning unit (5) to map the environment.

[0039] The communication between the UWB positioning anchor (1) and the UWB positioning unit (5) on the mapping device (2) is interrupted because the UWB positioning anchor (t ) moves out of the line of sight when travelling through the cave. In this case, the mapping device (2) searches for a place to position the new UWB positioning anchor (1) and places and operates the second UWB positioning anchor (1) so that the fixed UWB positioning anchors (1 ) are within line of sight of each other. In this process, LIDAR (6) and inertial measurement units (7) are used for positioning. It develops a strategy to determine a route using the area within the LIDAR coverage area (3) and the area mapped so far.

[0040] The mapping process continues when the communication between the UWB positioning anchor fl) and the UWB positioning unit (5) on the mapping device (2) is re-established.

[0041] The mapping process is performed by transmitting the distance measurements from the 360° circumference of the LIDAR (6), the measurements of the UWB positioning unit (5) and the measurements of the inertial measurement unit (7) to the accompanying computer (8) In the accompanying computer (8), these 3 measurements are processed by particle filter and Kalman filters. 360° distance measurement i s performed with 2D LIDAR (6). The 360° distance measurement is achieved by rotating the LIDAR (6) around its axis continuously by an encoder motor and measuring the distance from all directions. The errors caused by the encoder resolution of the LIDAR (6) are eliminated by the positioning information provided by the UWB unit (5). - If the covariance of each filter is low, the data produced by all sensor subsystems are healthy.

[0042] - If the covariance of other filters other than one filter is high, the information produced by the sensor subsystem di cretised in the input of the Kalman filter with low covariance is incorrect and should be removed from the system.

[0043] The sensor health result is used to select the sensor source to be used for verification If all sensor units are healthy, the weighted average of the results of all sensor systems will be used as the verification source. If a faulty sensor is detected, this sensor data is removed from the system and the other sensor data is used as validation data.

Claims

CLAIMS1. An UWB and LIDAR based environment mapping, exploration and positioning method for indoor environments; characterized by it comprises,Placing the first UWB positioning anchor (1) at the entrance to the indoor space,- Performing distance and angle measurements (4) within the range of the UWB positioning anchor (1 ) with the UWB positioning unit (5) on the mapping device (2), measuring the environment by performing 360 distance measurements with LIDAR (6), collecting data with inertial measurement milt (7),- Processing of this data on the accompanying computer (8), Converting the collected data into position data by means of Kalman blind navigation filter, particle filter and kinematic equations,Grouping these three position data as binary combinations in the accompanying computer (8),Giving binary combinations as input to Kalman filters separately, Calculating the covariance values of the binary combination results obtained from Kal n filters.Predicting that the data produced by all sensor subsystems are healthy, if the covariance values of the results of each binary combination are low;Predicting the information produced by the sensor subsystem discrete in the input of the Kalman filter with low covariance is inaccurate, if the covariance of other filters other than one filter is high,- Positioning the second UWB positioning anchor (1) withm line of sight of the first UWB positioning anchor (1), when moving out of range (line of sight) of the first UWB positioning anchor (I),Performing distance and angle measurements (4) within the range of the second UWB positioning anchor (1 ) with the UWB positioning unit (5),measuring the environment with LIDAR (6), collecting data with inertial measurement unit (7) and continuing mapping.

2. A method according to claim 1 , characterized by, the inertial measurement unit (7) comprises a combination of an accelerometer, a rotation meter and a magnetic field meter, and further comprising the step of converting the inertial measurements into position Information using a Kalman filter modelled for blind navigation3. A method according to claim 1, characterized by it comprises the step of continuously rotating the LIDAR (6) around its axis by an encoder motor to measure distance in al I directions, generating a point cloud from the di stance measurements taken from 360 circumference, and processing the point cloud by a particle filter to convert it into position data.

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