MODULAR ULTRASONIC SENSOR PLATFORM FOR MOBILE ROBOT

Imen Maâlej1, Mohamed Ouali2 and Nabil Derbel3

1University of Sfax, ENIS, Research Unit on Intelligent Control, design & Optimisation of complex Systems (ICOS), e-mail: imenmaalej@hotmail.fr

2Computer & Embedded Systems (CES), e-mail: mohamed.Ouali@enis.rnu.tn 3Research Unit on Intelligent Control, design & Optimisation of complex Systems (ICOS), e-mail: nabil.derbel@ieee.org

ABSTRACT The ultrasonic sensor is the most replied sensor in mobile robot to get environmental information and avoid obstacles. In fact, this type of sensors offers satisfactory results with affordable cost. However, one sensor is insufficient for a better perception of the environment. In this paper we opt for the conception of an ultrasonic sensor network to extract as much information as possible for measuring the distance between the robot and the obstacle. The algorithm for distance calculation is based on the measurement of the time of flight for the ultrasonic wave. The experimental results show a good performance of the conceived system for the distinction between different shapes of obstacles. Index Terms— ultrasonic sensor network, time of flight, shapes of obstacles.

1. INTRODUCTION The major problem that may be encountered in the mobile robot application is the conduct of the robot which requires a good knowledge of its surroundings. Several types of sensors are proposed to get a better perception of the environment. The ultrasonic sensors are extensively used over infra-red sensor and laser sensor since its measurement principle is simple and its hardware implementation is easy. However, they have several problems such as the wide beam angle, the specular reflection, the slow propagation velocity, the cross talk phenomenon and the environmental effects (temperature, wind, pressure). In recent studies in fusing ultrasonic sensor data, Choset and al. [1] proposed fusing multiple ultrasonic sensor data while a mobile robot moves. Wijik and al. [2] proposed improving a grid map of the environment by triangulating multiple ultrasonic sensor data. Ohya and al.[3] used vision and ultrasonic sensing for obstacle avoidance: the vision for the stationary obstacles and ultrasound to avoid obstacles in motion. Tardos and al.[4] proposed a technique for perceptual grouping to identify some elements constructing the environment such as corners and lines by combining data from the sonar. Kuc and Borenstein [5] proposed using two sensors to know the difference between a flat surface and a corner. Peremans and al. [6] used three ultrasonic sensors to differentiate the corner from the plan. Joen and Kim [7] also use three sensors to distinguish the plan from the corner and then they built a map of this environment. Barshan and al. [8] applied neural networks to differentiate between different forms of obstacles: plane, corner, edges, cylindrical shapes etc. The aim of this paper is to develop an ultrasonic sensor network for obstacle detection and to experimental

evaluate algorithms for differentiation between some geometrical shapes of the target. The paper is structured as follows: In the second section we present the ultrasonic sensor. The third section presents the proposed ultrasonic sensor network. Experiments and results are shown in the fourth section. The last section concludes with a brief summary and some remarks.

2. ULTRASONIC SENSOR 2.1. Measurement technique The technique of distance measurement is based on measuring the elapsed time between emission of the wave and reception of the echo. This technique is called: The time of flight measurement. The propagation of the ultrasonic wave is done at the sound speed in the air (340 m/sec). By applying a voltage at the terminal of the transmitter, the piezoelectric effect causes the appearance of a frequency and the emission of an ultrasonic wave. When this wave strikes an object, it will be reflected and detected by the receiver. The time between transmission and reception of the wave will be calculated by the microprocessor. 2.2. Physical characteristics An ultrasonic sensor is characterized by its emitted frequency, the opening of the cone of diffraction and the shape of the ultrasound beam. The figure below (figure1) has a typical shape of the ultrasound beam. The affective operation angle of the transducers is about 30fl. The measurement will be more accurate in the central cone of 30° and will be less accurate on the other sides. This operation area provides better perception of the obstacles.

Figure 1. Ultrasound beam

The ultrasonic sensor has an area called ‘dead zone’ (figure2) which corresponds to the minimum distance that should be exist between the detected object and the sensor to work properly.

Figure 2. Measurement area of the ultrasonic sensor

3. ULTRASONIC SENSOR NETWORK

3.1. Description of the ultrasonic sensor network

Because of the lack of sensory information coming from a single ultrasonic, the idea was to develop an ultrasonic sensor network. This network has a modular design to get flexibility in its operations. The figure below (figure 3) shows the sensor network architecture proposed. This network is managed by a programmable microcontroller which several separated ultrasonic modules are connected to it. Each module should have the capability of receiving the order of emission from the microcontroller, the emission of the ultrasonic signal, the reception of the echo and its transmission to the microcontroller. The first problem coming from using sensor network is the cross talk the phenomenon. Cross talk is the interference between two signals outcoming from two transmitters. It’s difficult to avoid crosstalk in practical environment. Borenstein [9] proposed avoiding cross-talk by controlling patterns. Cour-Harbou [10] took advantage of the technology of

spread spectrum. As a strategy, we chose to turn on sensor alternately. It’s a simple method and inexpensive.

Figure 3. Architecture of the proposed platform

3.2. Principle of distance measurement

The basic principle of distance measurement is presented in figure 4.

Figure 4. Operation of an ultrasonic module

The microcontroller delivers a signal with low amplitude. This signal will be amplified by an operational amplifier of voltage above the transmitter. Then, the transmitter sends an ultrasonic wave. When the wave hits an obstacle, an echo is detected at the receiver. The receiver is followed by an amplifier (to amplify the received signal) and a trigger of the analog signal to a TTL signal. Therefore, the microcontroller can calculate the distance measured. This calculation is based on the time of flight of the wave. 3.3. Hardware conception 3.3.1. Microcontroller block This block is the main block which manages the network (figure5). The microcontroller used is PIC16F877. This module is designed to manage nine sensors. The PIC16F877 used operates at a frequency of 20 Mhz. Connectors have been placed to allow access to all input/output of the microcontroller.

Figure 5. PIC 16F877 microcontroller module 3.3.2. Transmission and reception block Each ultrasonic module (figure 6) should have the capability of receiving the order from the microcontroller, the emission of the ultrasonic signal, the receiving of the echo and its transmission to the microcontroller.

Figure 6.Ultrasonic transmitting and receiving module

3.3.3. Serial communication block The communication between the platform and the PC is made by a serial link using the RS232 norm. This norm uses +12V and -12V while the processor of the main

module uses TTL signals (0V and 5V). Therefore, to communicate with the PC, we need an adaptation module (figure7). The signal conversion circuit used is MAX232.

Figure 7. Adaptation module

3.4. Software conception 3.4.1. Algorithm for distance measurement At the first, eight cycles of 40 KHz ultrasonic wave will be sent. After the deactivation of the transmitter, we wait for the return of the echo signal. Two cases are possible: - If the echo signal is received at the input of the microcontroller, the value of the measured distance will be calculated and sent to the PC through the serial communication. - If the echo signal is not received, a timer out is launched to indicate the absence of the obstacle. When this cycle is terminated, it will be repeated for the next module. 3.4.2. Simulation on ISIS To perform a first validation of the developed program, we opted to simulate its operation before proceeding to practical implementation. We chose ISIS as simulator (figure 8). It was essential to design a model for two parts before simulating developed program: - The first part is to create a block that simulates the time of flight (TOF): The spread of the signal outputting from the PIC, its reflection by an obstacle and the return of the echo at the input of the PIC. - The second part concerns the serial transmission which provides communication between the PIC and the PC. The first part is developed by inserting four microcontrollers. Each microcontroller executes a program to:

1. Receive 8 cycles sent by the main microcontroller. 2. Wait for a time period equivalent to the TOF (path,

reflection, return). 3. Regenerate 8 cycles to the main microcontroller as a

signal echo. The second part is provided by the serial communication and display tool called ‘Virtual Terminal’. This component can be connected to the PIC through RX and TX terminals. It enables the display of the data transmitted by the PIC and gives the ability to send data to the PIC.

Figure 8. Simulation on ISIS

4. EXPERIMENTS AND RESULTS

The algorithm performance for obstacle location depends on the target shape. The adopted experiences are based on the placement of four aligned and juxtaposed ultrasonic modules. The distance between the receiver and the transmitter of two adjacent modules is 2cm (figure 9 ). The experiences will be done for linear forms and cylindrical shapes and will use two types of algorithms: the first uses one transceiver each time and the second activates the receivers of all modules.

Figure 9. Arrangement of ultrasonic sensors

In order to exploit the data result from the sensors, we used the Visual basic environment to develop an application for tacking measurement and its registry in an Excel file. So, we construct a database for future use.

4.1. First experience: detection by one transceiver It consists of sending an ultrasonic signal and its reception by the transducers of the same module. The operation of four sensors is done by polling: the four measurements are done one after the other. The results of this first experiment are detailed in table1 Table 1. Results of the first experiment

Position Shape E1R1 E2R2 E3R3 E4R4 Without

translation Linear 43 43 43 43

Cylindrical 78 68 65 68 Translation

of 1 cm Linear 43 43 43 43

Cylindrical 73 68 65 69 Translation

of 2 cm Linear 43 43 43 43

Cylindrical 69 67 67 71 A graphical representation of each measure is shown in figure10.

Figure 10. Graphical representation with 4 measurements

points

To acquire a most number of points to draw the contour of the obstacle, the idea was to take three successive measurements of each sensor (the system is fixed then translated by 1 cm and finally translated by 2 cm) A graphical representation that includes 12 points of measurement is shown in figure 11

Figure 11. Graphical representation with 12 measurement points

According to the results, two interpretations can be extracted: - For the linear form: The four measurements are sufficient to detect the linear form - For the cylindrical shape: The curvature of the

cylindrical shape is not visible enough in case of four sensors. To avoid this problem, we plotted the outline after translating the system to get 12 measurement points. The obtained results are closer to the reality.

This experiment shows the importance and the utility of increasing the number of sensors in order to represent correctly the contour of the obstacle.

4.2. Second experience: detection by a transmitter and four receivers

It consists of sending an ultrasonic signal from a transmitter and receiving it by 4 receivers. The table 2 presents the results of the second experiment

Table 2. Results of the second experiment

R1 R2 R3 R4 1st

measure E1

linear form

43 43 43 43

cylindrical shape

74 69 67 73

2nd measure

E2

linear form

43 43 43 43

cylindrical shape

69 68 71 79

3rd measure

E4

linear form

43 43 43 43

cylindrical shape

67 71 76 81

4th measure

E4

linear form

43 43 43 43

cylindrical shape

73 79 81 89

This experience provides 16 points of measurement (4 measurements for each transmitter). Assuming that the reflection is done in the middle between emitter and receiver, the figure 12 presents the position of each measured point.

Figure 12. Model of the second experiment

A graphical representation of this second experiment is shown in figure 13

Figure 13. Graphical representation with 16 measurement points

According to the results, two interpretations can be extracted: - For the linear form: according to the graphical representation with 16 points of measurement, there are several points which are identical. Therefore, it’s sufficient to have a number of points less than 16 points - For the cylindrical shape: according to the figure 13

and the table 2, we note that there was a redundancy of some points. These redundancies are shown in figure 12. As new proposed model, only 7 measurement points are useful to represent the detected contour. The choice to eliminate the point of redundancy requires the achievement of more experiments ( possible combinations of experiments)

Figure 14 shows two examples of experiments after eliminating the following points of redundancy: Example 1: E2R1, E1R3, E3R1, E3R2, E4R1, E1R4, E2R4, E4R2, E3R4 Example 2: E1R2, E2R2, E3R1, E2R3, E3R2, E1R4, E3R3, E4R2, E4R3

Figure 14. graphical representation with 7 measurement points

By showing the results of this new model, the measure with 7 points is satisfactory. However, the choice to

eliminate the redundancy needs the realization of more experience.

5. CONCLUSION

This paper proposed a sensing method that classified the target surface as a plane or a cylinder. The proposed sensing system consists of using 4 sets of ultrasonic aligned sensors. Two types of experiments are used: the first is based on one emitter and one receiver. The result for this experiment is the necessity of having more measurement points for cylindrical shape. The second activates four receivers. This method offers more measurement points with presence of redundancy: 7 measurement points from 16 are useful. Simulation and experimental results verify the effectiveness of the proposed platform and its applicability to an actual robot system. Further experiments and an excessive number of ultrasonic sensors are required for map building purposes.

6. REFERENCES

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