aim.2009.5229916

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Abstract — this paper describes an unmanned ground vehicle

that can move urban environment. The UGV technology grows

rapidly. Generally UGV is developed for military purpose. Now

a days, many university and research institute research new

UGV technology for commercial use such as transportation

service. This vehicle can drive on the urban environment. The

UGV system consists of four parts such as vehicle control system,

navigation system, obstacle detecting system and arbitration

system. In this research, we used minivan for developing

unmanned ground vehicle. And we explain each system

configuration and event driving that based on extended RDDF.

Through real driving test on the fixed environment, we want to

verify unmanned ground vehicle system

I.

INTRODUCTION

Fig. 1 DARPA Urban Challenge 2007

Recently autonomous driving technology is rapidly

developed. Through unmanned ground vehicle competition,

importance of unmanned vehicle technology is understood

and related technology is expanded. An initial stage,

unmanned ground vehicle and related technology were

Manuscript received February 15, 2009. This work was supported by theMinistry of Knowledge Economy(MKE) and Korea Institute of Industrial

Technology Evaluation and Planning(ITEP) through the Center for Automo

tive Mechatronics Parts(CAMP) at Keimyung University. Development of

Unmanned Ground Vehicles Available of Urban Drive

H.C. Moon is with Unmanned Ground Vehicle Lab of Kookmin

University, Seoul, Korea. (corresponding author to provide phone:

+82-2-943-1994; fax: +82-2-916-0991; e-mail: [email protected]).

J.H. Kim is with Kookmin University, Seoul, Korea. (e-mail:

[email protected])

J. C. Lee is with Keimyung University, Deagu, Korea (e-mail:

[email protected])

D.M. Lee is with The Center for Automotive Mechatronics Parts,

Keimyung University, Deagu, Korea (e-mail: [email protected])

developed to use military purposes[1][2]. But now, these

abilities were used for commercial transportation service. In

this paper, unmanned ground vehicle for urban driving is

developed and verified the vehicle can drive on the urban

road.

II.

SYSTEM CONFIGURATION

For developing unmanned ground vehicle that can drive on

the urban road, minivan used for based vehicle. The vehicle

has enough space and power for installing many systems. Also

the vehicle can transport passengers[3]. Fig. 2 is unmanned

ground vehicle whole system configuration. the UGV isconsist of 4 sub system that are vehicle control system for

control vehicle’s movement, navigation system for get

vehicle’s current position and calculate vehicle’s direction,

obstacle detecting system for detect obstacles on the road and

calculate avoid path and arbitration system for control other

subsystems and generate vehicle control command for vehicle

control system.

Fig. 2 Unmanned Ground Vehicle system configuration

1. Vehicle control system

Vehicle control system is a base system of UGV. This

vehicle can drive urban environment and have enough space

for install many sensors and actuators. In this research, we use

minivan produced by Hyundai motor company. Fig. 3 is

vehicle control system configuration of unmanned ground

vehicle[4].

Vehicle control system has independent power supply

system for sensor, actuator and subsystems. This power

system is isolated from vehicle power system. Generator of

DC 24V and 60Ah is mounted on engine room of the vehicle

and battery of DC 24V 200Ah is mounted on rear of vehicle.

Development of Unmanned Ground Vehicles

available of Urban Drive

HeeChang Moon, JaeCheon Lee, JungHa Kim, and DongMyung Lee, Member, IEEE

2009 IEEE/ASME International Conference on Advanced Intelligent MechatronicsSuntec Convention and Exhibition Center Singapore, July 14-17, 2009

978-1-4244-2853-3/09/$25.00 ©2009 IEEE 786

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Fig. 3 Vehicle control system configuration

This power system can charge itself when engine is going and

have enough capacity when engine is stop.

Vehicle control system used CompactRIO is made by

National Instrument. It has expansion interface ports that

based on FPGA(Field Programmable Gate Array). It offer

various interface module such as RS232 multi port module,

DAQ module for sensor data acquisition and digital

input/output module for control several switches and relays.And E-stop function is expressed using RF data transmitter

and receiver that is shown fig. 4. It was used for emergency

case during vehicle driving. When vehicle’s movement is

unstable, operator push button of transmitter then vehicle

recognize this signal then generate command of vehicle stop.

The vehicle must have this function for safety.

Fig.4 RF transmitter and receiver

2. Navigation system

Navigation system of unmanned ground vehicle is to get

current position of the vehicle using GPS and to generate

global path to objective position. And this system makes

steering angle command for following the generated global path[5]. Fig. 5 is shown navigation system configuration.

GPS is used for get current position of the vehicle. In this

research, navigation system has GPS and DGPS because GPS

has good receiving rate and low position accuracy but DGPS

has good position accuracy and low receiving rate. So

navigation system use two kinds of GPS receiver. In this

research, 18-5Hz of Garmin and SF-2050M of Navcom are

used. Using GPS, vehicle can get vehicle’s current position

and direction of travel when vehicle is moving. If the vehicle

Fig. 5 Navigation system configuration

doesn’t move, it is hard to get direction of travel. So, digital

compass is used for get heading angle of the vehicle against

magnetic north. In this research, C-100 of KVH is used for

navigation system.

3. Obstacle detecting system

For driving stabilization of a vehicle, Obstacle detectingsystem is an essential part in Unmanned Ground Vehicle

system.. It detects most of the obstacles around the vehicle that

are on the front and side of the vehicle[6]. And it make

steering value for obstacle avoidance. The fig. 6 shows the

details of obstacle detecting system configuration.

Fig. 6 Obstacle detecting system configuration

In this research, laser scanners and vision cameras were

chosen for obstacle detecting. We use the LMS291-S05 laser

scanner which is more accurate from SICK Optic Inc. and it is

composed of four positions. Laser scanners was mounted in a

different location (fig. 7), they each have a different scanning

area.

Obstacle detecting system use Vision cameras for line

detecting and obstacle detecting. In this research, we detect a

line on the road way in urban environment and fuse laser

scanner data for indicates into a local map. Follow picture

represents a result of line detecting using though transform.

Vision cameras also detect speed bumps that are met with

everywhere in urban environment. Generally, speed bumps

have same color pattern and frequent color pattern change is

followed by pattern recognition and edge change. It is possibl

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Fig. 7 Mount position of laser scanner and camera

Fig. 8 Obstacle detecting range of laser scanner

Fig. 9 Result of lane detection and local map expression

le for the detecting speed bumps how it compare the number

of edge. Fig.10 represents the results of image processing

process and speed bumps detecting.

Fig. 10 Process and result of speed bump detection

III. DRIVING ALGORITHM

1. Global waypoint driving method

Driving algorithm for UGV using a DGPS unit, multiple GPS

units, encoders and a compass is lateral control. The UGV has

heading vector V, which is calculated using current position

and compass azimuth, and waypoint vector W, between the

current position and WP. The steering angle (β ) is calculated

using a simple trigonometric formula[7].

Fig. 11 calculation of steering angle

The direction of UGV is defined as using rotation and

transpose matrix. If the way point is being on right from

driving direction, UGV is turned the right. The other case,

UGV is turned the left.

The Ex-RDDF includes the WP’s X and Y position and

lateral boundary offset (LBO). The UGV uses the waypoints

from the Ex-RDDF to drive. If the current vehicle position is

found to pass within the LBO, the goal WP is updated to the

next WP in the Ex-RDDF.

Latitude and longitude are changed into X and Y

coordinates. Stop & Go and Steer Angle are event information

used to perform some mission.

cosV W

V W β =

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Fig. 12 Concept of calculating steering direction

2. Local event driving method

The Ex-RDDF consists of seven text messages. The

following figure shows an example of these messages.

Fig. 13 Extended RDDF for event driving

Table 1 Event list for unmanned ground vehicle event driving

IV.

TEST AND RESULT

For driving tests of our unmanned ground vehicle, we

performed at driving test environment where is shown in

Fig.14. We operated driving tests in our college ground,

because unmanned ground vehicle couldn’t be tested on the

real road. The driving course was about 500m, and fixed

obstacles, moving obstacles, a cross line were set up on the

test road. Then, we made an experiment how tests were

driving unmanned ground vehicle.

Before we got this test, we used the eRDDF (extended Route

Data Definition File, table 2 shows an eRDDF list table)

which had been made coordinates about start point, way-point

and finish point. Table Extended RDDF listThe data had been post-processed to test the driving ability

of unmanned ground vehicle to coast through GPS trajectory

as shown in Fig. 15. The vehicle was driven through the

way-points also it had to avoid obstacles. Then, missions that

operated a stop signature, avoidance fixed obstacles, detected

pedestrians completed successfully.

As the result of driving, the vehicle’s driving is stable

because generated path is smooth.

Fig. 14 Test environment at Keimyung Univ.

Table 2 RDDF list of test field

Fig. 16 shows the graph of changed steer angles during

driven on the ground road. A steer command signal of

unmanned ground vehicle was generated by both navigation

and obstacle detection system. A steer command that was

generated by those systems transferred to arbiter system, it

determined according to priority of vehicle state. The green

and red lines represent each steer angle of the obstacle

detection and vehicle control system, the blue line also

represents a steer angle that was responded from arbiter

system. So, we could prove that vehicle was controlled by

other systems.

Navigation system limits maximum speed by various road

conditions. This limited speed is sent to arbitration system

then the system can control vehicle’s speed by vehicle’s state

and other system’s condition. If navigation system make

vehicle speed command at 10km/h and obstacle detecting

system detect obstacle, the arbitration system make decision

to avoid or to stop. Then result of decision is sent to vehicle

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Fig. 15 Test result of vehicle driving

Fig. 16 Steering angle command of arbiter and obstacle

detecting system and steering angle response of vehicle

Fig. 17 Response of vehicle velocity command

control system. Vehicle control system controls vehicle’s

speed. Fig. 17 shows result of vehicle velocity control.

Continuous line is current velocity of the vehicle and dashed

line is vehicle velocity command that made arbitration system.

As the result of velocity control, the vehicle control system

controls vehicle speed by the command. At a pedestrian

crossing and emergency case, the vehicle rapidly stops using

brake actuator. Then the vehicle continuous drives after get

start command.

V.

CONCLUSION

This research presents the opportunity to develop an

unmanned mini-van that was automatic drivable on the urban

environment, and operated a driving test. We had proved it

how unmanned ground vehicle could react against missions in

7Km/h of average speed. Our test could become prohibitive

due to being drivable with another human driven vehicle. So,

we could have operated limitedly.

However, we can prove it that our unmanned ground vehicle

was able to drive successfully in urban environment in this

research.

ACKNOWLEDGEMENT

This work was supported by the Ministry of Knowledge

Economy(MKE) and Korea Institute of Industrial Technology

Evaluation and Planning(ITEP) through the Center for

Automotive Mechatronics Parts(CAMP) at Keimyung

University.

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