The Design And Implementation Of Intelligent Inspection Robot System Using

Combined Flame Sensors And Infrared Sensors

Fan Zhang1, a, Ming Li1, b, Pengfei Liang1, c, Kaiye Zhang1, c, Yuanqing Chou1, c

1. School of Shanghai Dianji University, P.R.China, 200240

a. princezhangfan@hotmail.com; b. ming.lmhost@gmail.com

Abstract—The article designed and implemented an

intelligent inspection robot system based on the traditional

obstacle avoidance algorithm and multi-sensor technology.

The hardware of this system mainly consists of an infrared

sensor, a flame sensor and three modules called power-supply

module, motion controlling module and sensing module.

Through the combination of multiple sensors, processor and

driving equipment, the system implemented the feature of a

robot in a structured context independent obstacle avoidance,

eventually reaching the high temperature of ignition search

location. The software part of the system used the small-angle

indirect search method, not only to achieve obstacle avoidance

smoothly, but also to prevent the decrease of accuracy in

hazard inspection caused by wide-angle turning. The system

combined the infrared sensor and flame sensor with a simple,

high sensitivity, and flexibility advantages that can successfully

achieve the goal of inspecting hazards intelligently.

Keywords: Flame sensor; Infrared sensor; intelligent robot;

obstacle avoidance

I. INTRODUCTION

With the progress of technology and the development

of human society, there are more automated robots and the

robot industry is developing faster and faster. Many kinds

of highly automated robots have been produced and have

played an indispensable role in industry, agriculture,

manufacturing and many other fields. One example widely

used in automobile manufacturing assembly line is that of

ABB robots, covering welding, material handling, assembly,

finishing and painting, and many other engineering features.

In addition, a variety of excellent agricultural automation

products also reflect the robot's full capabilities, including

the grafting robot, picking robot and timber cleaning robots.

The positive role of the robot is more and more

obvious. One of the most important features is that they can

reach dangerous places that man cannot. 2009 was the first

time that using robot patrol power lines and high voltage of

500 kV way, the robot could walk in the transmission lines

along the ground independently across the barriers and

could record the configuration of the operation of

transmission equipment with cameras, while the data got

sent back to the ground station in real time. Use of robots to

inspect in such an environment means that the efficiency is

more stable, and one can save costs associated with

inspection.

With the constant improvement of robot features as

well as with the use of multiple sensors, robots have

become more intelligent and precise. Along with signal

transmission and processing of sensor technological

advances, the robot has a sensing function, equivalent to the

various functions of human facial features. The robot's

sensors are in prominent use by the French company

Aldebaran Robotics. They spent three years developing a

robot "Nao", which includes the use of multiple sensors,

including pressure sensors, sonar sensors and infrared

sensors. The integrated use of these three sensors allows the

"Nao" to not only detect the route and bypass the obstacles,

but also to return echo information to determine the location

and number around the obstructions. And in the United

Kingdom, the ultrasonic engineering center in the

University of Strathclyde has been trying to use biological

sonar technology in the robot. So we believe that this series

of relevant research will bring next-generation robot

technology an important inspiration.

In addition, many domestic experts and scholars have

developed a lot of research works in the field of inspection

robot. For example, a kind of inspection robot system based

on ultrasonic sensors has been proposed by Liu Yuqin [1].

This system uses two ultrasonic range finders to locate the

position of obstacles, and achieves obstacle avoidance

capabilities to reach the target in a structured environment.

The idea about the application of infrared sensors in

obstacle avoidance system, as put forward by Hou Lichun,[2]

mainly describes the system’s implementation from the

hardware, and simulates the related features successfully.

Bao Xinghe[3]designed a obstacle avoidance robot system

using a non-scanning laser sensor based on a small plane,

and this system combined the robot and higher sensor

technology more perfectly.

Based on the existing basis of sensors and robotics, we

present a robot system which combines the flame sensors

and infrared sensors to find the high-temperature flame in

the environment, and achieves the obstacle avoidance

feature during searching. In this paper, the implementation

process and related operations of this system are described

in detail both from hardware and software.

II. HARDWARE SYSTEM

The design goal of this system is to make robots with

autonomous obstacle avoidance features, while being able

to detect the high-temperature heat source within its reach

and look for the path to the heat source independently.

From the hardware point of view, the system is divided into

three modules, namely sensing and communication module,

motion module and power module. Sensing and

communication module also includes PSD infrared sensors

and flame sensors, one each. The following describes the

specific features and parameters of each module and the

sensors.

A. Sensing And Communication Module

This module is used to receive analog signal from PSD

infrared sensor and transform it into digital signal which the

robot can identify. These signals will be transmitted

between modules through the CAN bus of SIM interface

under the module. This module includes an ARM process

chip which model is LPC2368, crystal is 12M, two CAN

communication interface, a network interface used to

establish communication links between modules and other

devices and an extra A/D port, three expanded I / O

interfaces, one expanded 5V power supply.

B. Motion Module

This module is the driver of the robot, and takes charge

of its movement. This module receives digital signals

returned by sensing module and uses Pulse Width

Modulated (PWM) to drive two DC motors. Module

contains a model for the L298N motor driver chips, an extra

A/D port, three expanded I / O interfaces and one expanded

5V power supply.

C. Power Module

This module is the robot's power supply system. The

use of lithium batteries also ensures continuous and stable

power supply of robots.

D. PSD(Position Sensitive Detector)Infrared Sensor

This sensor measuring range is between 10cm and

80cm, accuracy error is ± 30%, measuring frequency is 100

Hz. Such sensors are particularly sensitive to the location of

the incident light, which means according to the different

position the incident light shines at photosensitive surface

of the device, the PSD will output different electrical

signals.

E. Flame Sensor

This flame sensor will change the strength of the red

light outside into the electric current and converts it to the

signal which the robot can recognize through the A / D port,

to detect the flame signal. In this system we use the

Arduino flame sensor. It can be used to detect the

wavelength range of 760nm ~ 1100nm in the infrared, the

working temperature of -25 degrees Celsius to 85 degrees

Celsius, the probe angle of 60 degrees, in which near

infrared wavelength 940nm, the sensitivity maximum.

III. MAIN CIRCUIT AND UNIT CIRCUIT

A. The Range Acquisition Theory of PSD

PSD ranging uses the optical triangulation

measurement theory, as shown in Figure 1. If the distance

between lens L1 and L2 is b, between the surface of the lens

L2 to the PSD is f (focal length of the lens L2), and the

distance between the spot focused on the surface of PSD

and the center of lens L2 is x, one can measure h = bf / x.

So as long as the values of coordinate x of PSD are

measured, you can measure the distance between the object

under test and the sensor.

Figure 1. the Range Acquisition Theory of PSD

B. The Theory Of A/D Conversion

There are 6 A/D ports in total. The motion module

uses AD4 (P1.30) as the left motor current detection and

AD5 (P1.31) as the right one. Sensing module uses AD0

(P0.23) as infrared PSD samples. As shown in the following

schematic of AD3, each AD range of input voltage signal is

0 ~ 5V, the reference voltage is 2.5V, so we need to use the

LM358 Operational Amplifier to change the 0 ~ 5V analog

signal into a signal for the 0 ~ 2.5V, then put the signals to

the AD port.

Figure 2. the Schematic of AD3

Since the analog voltage is reduced when we input the

value, its full-scale voltage should be set to 2.5V when

calculating. If set conversion resolution is 10 bits, then:

Voltage value=Digital quantity× 2.5/1024

C. The Transmission Of Signals Between Modules

Initialize AD channel 0 , the conversion clock is

1MHZ, ENOB of 10 bits; initialized CAN channel 2, the

baud rate is 1M, AD converted signal sent to the motion

controlling module from the CAN bus on the SIM interface.

D. The Theory Of Motion Controlling

In mobile robots that use DC motors, the drive is very

simple and convenient to operate. As long as both ends of

the motor loads within the rated voltage, you can drive

motor rotation. As shown in Figure 3, the two ends A and B

of the motor M load driving voltage V, when A is positive

and B is negative, the motor clockwise rotation; On the

contrary, counterclockwise rotation of the motor. Therefore,

we can change the direction of motor rotation by changing

the polarity of voltage loaded in the two ends of the motor.

Figure 3. the Relationship between Polarity and Direction

of Motor

The motion of Robot is by controlling the rotation

speed of left and right wheel - the differential mode, that is,

through control of the speed errand of left and right wheel

to make robot move forward and backward to turn. As

shown in Table 1, in addition to a PWM signal, each motor

has a direction signal DIR. PWM signal conditioning

wheels’ speed and DIR signal changes direction of motion.

When the two wheels are moving at the same speed, in the

same direction, the robot goes straight; when they move at

the same rate but in opposite directions, the robot rotates at

two different speeds, in opposite directions, the robot turns

a certain radius.

TABLE I. the Relationship between electrical signal and the

wheel moves

Therefore, the rotation speed and rotation direction of

DC motor are controlled by adjusting the size and polarity

of the voltage loaded on it. So we use "H- bridge motor

driver "to adjust the direction of rotation of DC motor. An

H- bridge is composed of two pairs of switches, each of the

two switches are connected to both ends of A, b in Figure 3.

The same group of synchronous switch turns on or off, and

when a switch on another one turns off. When the level of

input signal is high, one pair of switch turns on and the

voltage polarity of A is positive, B is negative, so that the

motor is transferred. When the level of input signal is low,

the other switch turns on, the voltage polarity of A is

negative, B is positive, so that the motor reversal. The size

of voltage is adjusted by the Pulse Width Modulated

(PWM). As shown in Figure 4,PWM is a kind of periodic

pulse signal, by changing the duty cycle(the ratio of the

time a signal is at high level and the cycle of a signal) to

change the signal pulse width (the time a signal at high

level in a cycle). We can conclude that the average voltage

of the signal is proportional to its pulse width or duty cycle.

Therefore, it is because the motor speed is proportional to

the voltage load on it, we adjust the duty cycle to obtain a

different average output voltage to regulate the motor

speed.

Figure 4. the Pulse Width Modulated Signal(Dashed line

indicates the average voltage,’ ton’ indicates the time a

signal at high level, ‘tperiod’ indicates the cycle of the

signal)

The ARM chip LPC2368 in sensing module produces

a certain cycle of PWM and the motion controlling module

using these signals to drive two DC motors. The left motor

(M1) uses PWM1 [4] of ARM, and the right one (M2) uses

PWM1 [6] of ARM (P1.26) input to the motor driver chip

which model is L298N. Left and right motors are connected

to the P2.13 and P0.11 of ARM, and the direction signal

DIR is divided into a positive one M1_P (or M2_P) and a

negative one M1_N (or M2_N).

Figure 5. DC motor drive circuit

E. The Theory Of Flame Sensor

The flame sensor is an infrared receiving transistor. It

uses the characteristics of infrared rays, which are

particularly sensitive to the flame, to detect the flame using

a special infrared receiving tube, and then turns the

brightness of the flame into undulating level signals to input

to the central processor. At last, the central processor makes

the appropriate treatment according to the changes of these

signals.

The flame sensor named ‘Arduino’ used in this system

is suitable for 5V voltage working environment. As shown

in Figure 6, the negative of transistor connected to an

interface whose voltage is 5V and the positive connected to

ground with a fixed value resistor. At last it connected a

jumper to the positive position of the transistor, and the

other end of the jumper is connected to the signal

transmission port.

Figure 6. the Wiring Diagram of Flame Sensor

IV. SOFTWARE SYSTEM

A. The Inspection Path Of Robot

From figure 7, we can conclude that the inspection

route of robot will be more precise when the angle robot

rotates gets smaller and the distance gets shorter. So ideally,

the turning path is close to an arc.

(a) the idealized path (b) the realistic path

Figure 7. the idealized and the realistic inspection path

B. The Configuration Of Software System

I). The integrated developing environment of ARM:

ADS (ARM Developer Suite) 1.2: This one

supports all the microcontrollers before ARM10,

software debugging and JTAG hardware

simulation debugging. It also supports the

assembly language, C, C++ code and has a high

efficiency in compiling. What’s more, the ADS

have a very strong and complete database.

II). Debugging tools: H-JTAG: This tool supports

most mainstream debugging software like

SDT2.51, ADS1.2, REALVIEW and IAR. Using

H-JTAG, you can debug all the ARM7/ARM9

processors using WIGGLER, SDT-JTAG or the

JTAG which users defined by themselves.

III). FLASH programming software: H-FLASHER: It

uses the DCC to program FLASH in a high speed.

It also uses the automatic calibration, automatic

erase and automatic recovery technology.

IV). Programming software: Visual C++: The

application of C++ language is very common, so

that it is convenient to all the technical staff to

modify and upgrade the system. The VC++

supports object-oriented design methods, and can

use the Microsoft Foundation Classes (MFC).

The software developed by Visual C++ is

stability, portability, and has an advantage that all

the software and hardware is independent from

each other.

V). ISP download software: Flash Magic: It

integrates all the ISP functions for all sorts of

LPC processors, and makes it easy to enter the

ISP, download and modify.

VI). The port debugging tool: Scommtest: This tool

supports the input and output in binary serial data,

and also makes it very convenient to debug ports

of all kinds of external devices with the

multiple-ports setting.

V. ADVANTAGES AND CHARACTERISTICS

A. Compared with other conventional devices such

as limited battery, CCD (Charge-coupled Device)

which is sensitive to the optical position, the PSD

infrared sensor has a high resolution of the

location, high cost performance and responses

fast. It’s especially suitable for the real-time

measurement of positions, displacements and

angles. What’s more, the distance-measuring

system composed by the PSD is non-contact, and

has a large measuring range.

B. The JTAG (Joint Test Action Group) protocol

which most advanced devices now support is

used in the ARM chip. This is an international

standard testing protocol for chip testing, also

commonly used in the realization of ISP

(In-System Programmable) online programming

of flash and other devices. The traditional

producing process is to pre-program on the chip

and then fit it to the motherboard, but because of

the online programming of JTAG we can using

ISP technology to fix device first and then

download the program into the chip. This method

greatly accelerated the progress of the project.

C. Expansion of the system's hardware is very

strong. The expand AD ports on each module can

expand a variety of external devices to facilitate

the realization of other features.

D. The cost of system is low. The external sensors

and other components of the robot are all in small

size so that it’s easy to disassemble and assemble.

And by the SIM port connection between

modules can be readily assembled, carrying and

testing.

VI. CONCLUSION

Robots have become an indispensable tool in various

fields, and the intelligent inspecting robot with a variety of

sensors is the preferred one to find and eliminate sources

instead of using humans in dangerous environments. Based

on the analysis of various types of obstacle-avoidance and

inspecting system, this article designs a system that

combines infrared sensors with flame sensors to find the

fire source. From both hardware and software as described

in detail the principle and the realization of processes and

the final simulated results meet the requirements of the

program. From shown of the path and the data, the system

can realize various features designed.

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