Calibration of vehicle odometer readings by sidewalk curb and

(a)

(b)

Figure. 4.1 Two proposed principles to judge if the vehicle arrives at the next node in the navigation process. (a) According to the distance between the vehicle position and the next node position. (b) According to the distance between the next node position and the position of the projection of the vehicle on the vector connecting the current node and the next node.

Landmark Detection

Figure 4.2 Proposed node-based navigation process

As mentioned in Chapter 3, the odometer readings provide three values Px, Py, and Pth for the vehicle to know its position (Px, Py) and moving direction Pth. Unfortunately, all of them become imprecise owing to incremental mechanic errors after the vehicle navigates for a period of time. In this section, we describe the proposed schemes to calibrate the odometer readings. The process of odometer reading calibration is illustrated in Figure 4.3. At first, we use recorded curb line segment information to calibrate the orientation reading Pth of the odometer. Second, by the recoded hydrant and light pole positions, we use the proposed hydrant and light pole detection method to obtain its position and then calibrate the position readings (Px, Py) of the vehicle. The reason why we have to combine a hydrant or light pole position with the curb information is that in the odometer reading calibration method we propose in this study, we have to calibrate the orientation odometer reading in advance using the detected curb line before the computed position of the hydrant and light pole can be used to localize the vehicle position.

(A) Odometer calibration by the hydrant and the sidewalk curb line

Two different positions of the vehicle at two nodes in the navigation path and the relation between the vehicle, the curb, and the hydrant are illustrated in Figure 4.4. The calibration process consists of two steps. Firstly, after adjusting the vehicle to the direction specified by the current odometer readings, we detect the nearby straight curb line segment seen in the omni-image, and obtain the slope angle with respect to the vehicle. From the learned navigation path, we can obtain the recorded slope angle of the curb line, and then analyze the two different slope angles to estimate the correct direction of the vehicle. Second, we conduct the vehicle to detect the hydrant and obtain its location. According to the recorded hydrant position from the learned navigation path, we use the correct vehicle orientation to compute

the correct vehicle position by the relation between the hydrant position and the vehicle position in the GCS as shown in Figure 4.5. We describe the proposed method to calibrate the odometer readings in detail in the following algorithm.

Hydrant landmark

Figure 4.3 Proposed odometer reading calibration process.

Hydrant

V(PX, PY, Pth) GCS

adj

Recorded Vehicle Position Current Vehicle Position

V (PX, PY, Pth)

Figure 4.4 A recoded vehicle position V and the current vehicle position V in the GCS.

(a) (b) Figure. 4.5 Hydrant detection for vehicle localization at position L. (a) At coordinates (lx, ly) in VCS.

(b) At coordinates (Cx, Cy) in GCS.

Algorithm 4.1 Odometer readings calibration by a hydrant and a curb line segment.

Input: a recoded vehicle pose VL (Px, PY, Pth), a recorded slope angle θ of the curb line, a recorded hydrant position Lrecord, and the odometer readings of the vehicle pose.

Output: None.

Step.

Step 1. Turn the vehicle to the recorded direction Pth, conduct the curb line detection process described in Chapter 6, and compute the slope angle θ of the curb line relative to the vehicle direction.

Step 2. Compute an adjustment angle θadj by the following equation:

adj = ′ –  (4.1)

and modify the orientation odometer reading to be θadj which is then taken as the correct vehicle orientation Pth′.

Step 3. Detect the hydrant and compute its position at Lccs in the CCS (using the method described in Chapter 5); and by the coordinate transformation between the CCS and the VCS as described in Equation (3.6) with Lccs in the CCS as input, compute the landmark position LVCS and describe it with coordinates (lx, ly) in the VCS.

Step 4. From the learned navigation path, obtain the recorded landmark position Lrecord

at coordinates (Cx, Cy) in the GCS, and use the calibrated orientation Pth′ to compute the current vehicle position (Xcali, Ycali) in the GCS by the following equations:

Step 5. Replace imprecise position readings of the odometer, (PX′, PY′), by the computed vehicle position (Xcali, Ycali).

(B) Odometer calibration by the light pole and the sidewalk curb line

The process for calibration by the light pole and the sidewalk curb is similar to the above-mentioned method for odometer calibration by a hydrant and a sidewalk curb line segment. First, we detect and localize a nearby curb line segment for the purpose to calibrate the orientation reading in a similar way as described previously at a node V1 in the learned path. Next, we conduct a slight difference task, i.e., we navigate the vehicle a step further to another node V2, which is a location recoded in the navigation path with a light pole nearby, in order to detect the light pole at a closer location. The process is shown in Figure 4.4. It is noted that here the mechanical error of the orientation reading is assumed slight after the movement of the vehicle from node V1 to node V2. Then, after detecting and localizing the light pole position, we use the same method to compute the current vehicle position and modify the position odometer as that used for the calibration work using the hydrant described previously.

4.2.3 Dynamic exposure adjustment for different