Principle of Navigation

6.2.1 Learning Strategy

The navigation paths in an indoor environment are usually composed of some straight lines which are connected by turning points. Before navigation, the vehicle has to learn the parameters of Width, Directionturn, Directiondetect, and Distancedetect of the environment. For a straight line of a path in the indoor environment, if it is a hallway with two walls at both the left and the right sides, then the value Width is set equal to the width of the hallway. But if the straight path only has one wall at the left or the right side, then Width is set equal to double the distance between the vehicle and the wall. An illustration is shown in Figure 6.2. For a turning point of the path, if the vehicle needs to turn to the right at the turning point, then we set Directionturn = right, and if the vehicle needs to turn to the left, we set Directionturn = left.

Width

(a)

1 Width×2

(b)

Figure 6.2 An illustration of the parameter of Width. (a) The hallway with two walls.

(b) The hallway only has one wall.

Additionally, the vehicle has to know the conditions of turning points. Turning points are usually located at the end of a wall or a hallway. The distance values caught from the ultrasonic sensors will vary to large values at the position of the end of a wall. The parameter Directiondetect is used to save the direction where the environment has caused such a kind of large-value variation and the vehicle can detect such variations to find out turning points. If a turning point is located at the end of the left wall, then we set Directiondetect = left; otherwise, we set Directiondetect = right.

Moreover, we set Directiondetect = left or right to mean that the turning point is located at the end of the left or the right wall, respectively. If the turning point is located at the end of the hallway, it means that there is something stopping the hallway. In that case, we set Directiondetect = front. The last parameter needs to learn is Distancedetect which is the distance between the turning point and the start position of the end of the wall in the environment. An illustration is shown in Figure 6.3.

6.2.2 Navigation Strategy

After learning the navigation path in the environment, the vehicle can navigate along the learned path by analyzing the sequential signals acquired by the ultrasonic

sensors. The vehicle has two missions, one to navigate along the middle line of the hallway, and the other to keep the direction of navigation parallel to the hallway.

Turning Point Distancedetect

(a)

Turning Point

Distance_detect

(b)

Turning Point Distancedetect

(c)

Turning Point Distancedetect

(d)

Figure 6.3 An illustration of the parameter of Directiondetect (a) Directiondetect = left.

(b) Directiondetect = right. (c) Directiondetect = left + right. (d) Directiondetect

= front.

We begin a navigation session at a start position in the hallway, and let it go forward by a fixed speed Speed. From the ultrasonic sensors, the system retrieves distance information Di which includes the left and the right distances (Di,L, Di,R) at time i, and analyzes n sets of data, Di-n, Di-n+1, …, Di, before time i. The vehicle needs to adjust its direction in four situations. When the vehicle moves close to the wall at the left side gradually, the system could find out the fact that the left distance of the vehicle is reducing or that the right distance of the vehicle is growing. Then, if the vehicle is close enough to the left wall, that is, if the right distance of the vehicle

exceeds half of the width of the hallway, then the vehicle turns an angle θlittle to the right, that is, the vehicle turns when the following conditions are met:

, 1,

On the other hand, when the vehicle moves close to the wall at the right side gradually, the system could find out the fact that the right distance of the vehicle is reducing or that the left distance of the vehicle is growing. Then, if the vehicle is close enough to the right wall, that is, if the left distance of vehicle exceeds half of the width of the hallway, the vehicle turns an angle θlittle to the left, that is, the vehicle does so if

for every k between i − n and i. An illustration of the situation of adjusting the direction of the vehicle is shown in Figure 6.4. An illustration of navigation in a hallway is shown in Figure 6.5.

It is seems superfluously if we both consider Eq. (6.1) and (6.2), but it is necessary. The walls in environments are not completely planar and the sensor could get some noise, so we need to consider the data from both sides of the wall. Eq. (6.4)

and (6.5) are for use to handle the same situation as above.

Figure 6.4 An illustration of the situation of adjusting the direction of the vehicle. (a) The vehicle should turn an angle to the right (b) The vehicle should turn an angle to the left

Left distance > half width of hallway

Figure 6.5 An illustration of navigation in a hallway.

For detection of a turning point, we have learned the parameters of the direction to detect Directiondetect and the distance to detect Distancedetect in the learning stage. If the parameter Directiondetect is left or right, the system calculates the times N to detect the changes of the environment by:

detect

And it also detects the changes of Directiondetect, and if the times reach N, then the vehicle arrives the turning point and turns to Directionturn. If the parameter Directiondetect is front, then the vehicle will keep detecting the front distance until the distance is smaller then Distancedetect. Then we consider that the vehicle has arrived at the turning point and command the vehicle to turn to the direction Directionturn.