A MULTIROBOT SYSTEM FOR DISTRIBUTED SENSING

Janne Haverinen, Anssi Kemppainen, Janne Kivijakola and Juha Röning

Department of Electrical and Information Engineering, University of Oulu, Finland

Keywords:

Multi-robot system, distributed sensing, laser, range sensing.

Abstract:

This paper presents a modular multirobot system developed for distributed sensing experiments. The mul-

tirobot system is composed of modular small size robots, which have various sensor capabilities including a

color stereo camera system and an infrared based sensor for infrastructure independent relative pose estimation

of robots. The paper describes the current state of the multirobot system introducing the robots, their sensor

capabilites, and some initial experiments conducted with the system. The experiments include a distributed

structured light based 3-D scanning experiment involving two robots, and an experiment where a group of

robots arrange into a spatial formation and measures distributions of light and magnetic ﬁeld of an environ-

ment. The experiments demonstrate how the proposed multirobot system can be used to extract information

from the environment, and how they can cooperatively perform non trivial tasks, like 3-D scanning, which is

a difﬁcult task for a single small size robot due to limitations of current sensing technologies. The distributed

3-D scanning method introduced in this paper demonstrates how multirobot system’s inherent properties, i.e.

spatial distribution and mobility, can be utilized in a novel way. The experiment demonstrates how distributed

measurement devices can be created, in which each robot has an unique role as a part of the device, and in

which the mobility of the robots provides ﬂexibility to the structure of the measurement system.

1 INTRODUCTION

The miniaturization of mobile robots (Floreano and

Mondada, 1998; Caprari et al., 2000; Sibley et al.,

2002; Colot et al., 2004; Mondada et al., 2004) is

rapidly progressing due to developments in electron-

ics and material technology, for example. Multirobot

systems composed of a group of miniaturized robots

can have numerous applications in the future. They

may be a regular sight on space expeditions or they

may operate inside the human body for our well be-

ing. At present, multirobot systems are a rear sight

in real world applications. However, they have al-

ready been used in surveillance applications, military

demonstrations, and in distributed sensing applica-

tions. The distributed sensing is an interesting appli-

cation domain as the multirobot system is inherently

spatially distributed. As this paper shows, the spatial

distribution of robots can be naturally utilized to over-

come problems that the miniaturization of the robots

introduces to the sensing technology in some prob-

lem domains. As an example, we will show how a

multirobot system can be used as a distributed struc-

tured light based scanning device for extracting 3-D

information from an environment. The distributed 3-

D scanning concept is useful in applications where

a group of robots needs to extract objects’ geometri-

cal information in remote locations without a require-

ment that a single robot must carry alone the neces-

sary technology for performing the range measure-

ments (Lee and Song, 2005).

An other experiment, which demonstrates the fea-

sibility of the proposed multirobot system, shows

how robots can be driven into a given spatial for-

mation, and used to automatically perform measure-

ments about illumination and magnetic ﬁeld of the en-

vironment.

This paper brieﬂy introduces the developed mul-

tirobot system and its sensor capabilities. Then, two

experiments are brieﬂy presented in order to demon-

137

Haver inen J., Kemppainen A., Kivijakola J. and Röning J. (2007).

A MULTIROBOT SYSTEM FOR DISTRIBUTED SENSING.

In Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics, pages 137-142

DOI: 10.5220/0001649601370142

 SciTePress

strate how the system can be used in interesting real

world applications. The multirobot system is com-

posed of miniature mobile robots ﬁrst introduced in

(Haverinen et al., 2005). Each robot can have vari-

ous sensor capabilities including a color stereo cam-

era system and an infrared based sensor for relative

pose estimation (Kemppainen et al., 2006). The ex-

periments are conducted by combining these sensor

capabilities (modules) to form both heterogeneous,

and homogeneous teams of robots.

2 THE MULTIROBOT SYSTEM

The presented multirobot system is composed of

modular miniature mobile robots (Haverinen et al.,

2005). One conﬁguration of an individual robot is

shown in Fig. 1. In addition to DC-motor (actuator)

and power modules, the robot in Fig.1 has four other

modules, which are (from top): the IR-location, the

stereo camera, the radio, the environment, and the IR-

proximity modules, respectively. Each of these mod-

ules provide an well deﬁned serial interface for read-

ing or writing data. All modules have an 8-bit low

power 8MHz MCU (ATmega32), which implements

the serial interface for accessing the module services,

and controls the logic of the module.

Each module can have from one to three different

serial interfaces (UART,I2C,SPI). While the UART

interface is mandatory for each module, I2C and SPI

interfaces are optional, and they are used for enhanc-

ing the bus performance. Each module with more

than one interface can be commanded to switch be-

tween interfaces in order to adapt the bus perfor-

mance.

The infrared based location module (Kemppainen

et al., 2006) is used to estimate the relative poses of

robots without external infrastructures such as bea-

cons, WLAN base stations, GPS or landmarks. The

operation principle of the location module is based on

omni directional amplitude modulated infrared trans-

mission and an infrared receiver that utilizes a rotating

beam collector for ﬁnding the direction of the infrared

transmission. The detected modulation frequency at

the receiver identiﬁes the transmitting system. Each

location module has an unique transmission modu-

lation frequency, which gives identity for each robot

having the location unit.

By having the module, the robot can have esti-

mated poses of the surrounding robots within ﬁve me-

ters without any external infrastructure. The infrared

location module is utilized in the experiments where

robots must be driven into speciﬁc formations prior

distributed sensing procedure. The module can also

be utilized to maintain and adapt formations during a

task execution. The infrared location module is used

in all experiments described in this paper. In the 3-

D scanning experiment the location module provides

the necessary information to arrange the robots into

given line formation prior the scanning procedure. In

distributed sensing experiments, the module is used

to setup the initial measurement formation (see Fig.

6), and to maintain the formation during the measure-

ment procedure. Fig. 2 demonstrates how the location

module can be used to estimate the poses of the sur-

rounding robot. In Fig. 2 the robot at (0, 0) estimates

the poses of the two other robots for a short period of

time. Only the (x, y)-coordinates of the located robots

are shown (heading is not plotted). See (Kemppainen

et al., 2006) for more detailed description of the IR-

location module.

motor

IR-proximity

environment

radio

stereo camera

IR-location

power

Figure 1: One conﬁguration of the miniature robot. This

robot has four modules in addition to motor and power mod-

ules. The modules include: the IR-location, the stereo cam-

era, the radio, the environment, and the IR-proximity mod-

ules. The environment module is used to measure acceler-

ations, temperature, ambient lighting, and the direction and

magnitude of the magnetic ﬁeld. The radio module imple-

ments the 868MHz 100kbits radio link for inter robot and

PC communication. The purpose of the motor module is to

control the two DC-motors of the robot. The power module

is responsible of recharging the battery and providing the

power for all modules through the module bus.

3 EXPERIMENTS

The purpose of the presented experiments is to

demonstrate different strategies of using the multi-

robot system for distributed sensing. The ﬁrst ex-

periment shows how a pair of heterogeneous robots

can be used as unique parts of a distributed measure-

ment device, and how system’s inherent mobility can

be utilized to provide a measurement device that has

the necessary ﬂexibility of adapting measurement ge-

ometry to the structure of the environment. The sec-

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138

Figure 2: The infrared location system provides the pose

estimates for two robots. The robot at (0, 0) is locating the

two other robots for a short period of time.

ond experiment shows how a team of homogeneous

robots can create a map of environment by moving in

a given formation and by making point measurements

about ambient lighting and magnetic ﬁeld from loca-

tions found by dedicated infrared location modules.

3.1 Distributed 3-d Scanning

The setup of this experiment consist of two heteroge-

neous robots: one of the robots acts as a laser sheet

projector, and the other as a laser stripe detector. The

projector robot, shown in Fig. 3, has a special laser

module which includes 1mW (class I) laser stripe pro-

jector. The projector provides a vertical sheet of light

that is projected into the environment. The robot that

is acting as a laser stripe detector uses one of the color

CMOS cameras of the stereo camera module loaded

with a program that extracts the projected laser pat-

terns from the surfaces of objects in the camera’s ﬁeld

of view.

The measurement geometry is depicted in Fig. 4.

First, the projector and the detector robots are aligned

into a given line formation in which the laser and the

camera are pointing to the left in regard to the driv-

ing direction. Both robots have now the same head-

ing. In order to have absolute range measurements the

parameters of the measurement geometry has to be

known (Haverinen and Röning, 2000). However, rel-

ative range measurements can be made without know-

ing the exact mutual poses of the two robots. In

our experiments, we have used both machine vision

technique (Heikkilä and Silven, 1997) and the loca-

tion module (Kemppainen et al., 2006) to arrange the

robots into the known initial measurement formation.

The machine vision technique utilizes the know land-

mark pattern mounted on the laser robot (shown in

Fig. 3) in order to estimate the mutual poses of the

robots.

The measurement geometry described in Fig. 4 is

not the only option. The robots can also be arranged

onto a circumference with both optical axis and the

laser sheet pointing to the center of the circle. By

driving along the the circumference with equal veloc-

ities the robots can perform a full scan of an object

that resides inside the circle. Yet another option is

to keep the robots on ﬁxed locations and rotating the

projector robot: in this way the robots can scan a large

area from ﬁxed locations. However, the angular mo-

tion of the projector robot must be known in order to

compute the range image.

In our experiments the scanning procedure starts

after the robots are properly aligned. Both robots are

moving with equal velocities. The camera robot per-

forms the image processing in order to extract the pro-

jected laser patterns reﬂected from the surfaces of ob-

jects. The image coordinates of the laser stripe on the

image plane are locally saved into the camera mod-

ule’s SDRAM. At the end of scanning, the image data

is transferred through the radio link to the host com-

puter (PC), which computes the ﬁnal range image.

Fig. 5 shows examples of range images acquired

by the cooperating robots. The images demonstrate

how cooperating miniature robots can perform a de-

manding measurement task by acting as distributed

parts of the physical measurement device. The co-

operative scanning can have important applications:

a pair of miniature mobile robots can perform a re-

mote 3-D scanning procedure and acquire range data

from selected objects in environments that might be

unreachable by traditional 3-D measurement devices.

The range data gives important information about an

(possible hazardous) environment, objects, and their

geometrical properties. The presented distributed

sensing technique can provide dense range data for

creating 3-D maps of unknown environments with-

out computationally intensive stereo image process-

ing (Rocha et al., 2005), for example. The technique

can also be an alternative for creating data for vision

based 3-D SLAM (Tomono, 2005).

3.2 Cooperative Measurement of

Spatial Data

This experiment demonstrates how heterogeneous

robots can be used to perform a simple distributed

sensing task, and to create a spatial map of point mea-

surements. The experiment also highlights the fea-

sibility of the infrared location module in applica-

tions domains where locations of the robots must be

known. The infrared location system is used to cre-

ate and maintain the measurement formation, while

the robots are making point measurements with the

A MULTIROBOT SYSTEM FOR DISTRIBUTED SENSING

139

Figure 3: The laser robot. The robot consist of the 1mW

laser line projector. This robot also has a landmark pattern

which can be used to estimate the pose of the projector robot

in the detector robot’s coordinate system using the calibrate

camera module and deﬁning its extrinsic parameters in re-

gard to the known landmark pattern (Heikkilä and Silven,

1997). Another technique to estimate the pose is to utilize

the IR-location module.

imageplane

lasersheet

object

camera’sfieldofview

v v

Figure 4: The measurement geometry used in the coopera-

tive scanning experiment. The robots are ﬁrst aligned into a

line formation - both robots having the same heading. The

distance d and the angle α control the measurement reso-

lution and the measurement range. d and α can be adapted

on the basis of the measurement task. During the scanning

procedure, both robots maintain the same velocity v.

scalar sensors of the environment module. The mea-

surements are stored into a grid map with predeﬁned

cell size. The value of each cell is the mean value

of the point measurements made in the corresponding

cell.

Although the experiment is simple, it has impor-

tant applications as it makes possible to automatically

gather spatial scalar data from the area of interest. The

data can then be used to analyze the lighting proper-

20 40 60 80 100

100

150

200

20 40 60 80 100 120 140 160 180 200

100

150

200

20 40 60 80 100 120 140 160 180 200

100

150

200

Figure 5: Range images from three cooperative 3-D scan-

ning experiments. a) range image from arbitrary artiﬁcial

objects (a head statue and some polyhedrons). b) and c)

robots have scanned a person laying on the ﬂoor. These

images demonstrate how, by simple cooperation, a pair of

miniature mobile robots can obtain dense range data from

objects of an environment.

ties of the environment or to visualize how the mag-

netic ﬁeld of the environment behaves due to metallic

structures in the environment, and analyze its proper-

ties over time, for example.

Fig. 6 shows the initial arrangement of the robots

prior the experiment (left): from these locations the

robots are driven into the measurement formation us-

ing the infrared location module (right). While main-

taining the measurement formation, the robots start

moving and doing measurements. The lighting mea-

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140

surements are shown in Fig. 7, and the direction of

the magnetic ﬁeld in each cell in presented in Fig. 8.

The Fig. 8 shows how the direction of the magnetic

ﬁeld varies in the environment due to metallic objects

and structures. If this magnetic ﬁngerprint of the en-

vironment is static it can be used to classify environ-

ments based on previous observations of the ﬁeld on

the same area, for example.

Figure 6: Left: the initial (arbitrary) positions of the robots.

From initial poses the robots are driven into the measure-

ment formation by using the IR location module. Right:

The IR-location system has been utilized to drive the robots

into the given measurement formation. The robot in the

middle acts as a leader and the other two robots as follow-

ers.

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−400

−300

−200

−100

100

200

300

400

500

x [cm]

intensity

y [cm]

100

110

Figure 7: Measured ambient light intensities. The ﬁgure

shows the value, given by the ambient light sensor, for each

cell of the grid.

4 CONCLUSION

This paper presented a multirobot system developed

for distributed sensing experiments and applications.

Each robot has variety of sensors for measuring prop-

erties of an environment. The sensors include a tem-

perature sensor, an ambient light detector, a compass

module, accelerometers, and a color stereo camera

system.

Distributed measurement tasks are naturally

suited for multirobot system as they are inherently

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−400

−300

−200

−100

100

200

300

400

500

x [cm]

y [cm]

heading

Figure 8: Measured directions of the magnetic ﬁeld. The

ﬁgure shows how magnetic ﬁeld varies due to metallic

structures of the environment. The variation (assuming it

being static over time) can be used to classify environments

based on previous observations from the same environment.

spatially distributed. The 3-D scanning experiment

showed how a pair of heterogeneous robots can coop-

erate by acting as parts of a distributed 3-D scanning

device. This observation is particularly important, as

this kind of measurement instrument is otherwise very

difﬁcult to implement for a single miniature mobile

robot. The scanning experiment also demonstrated

how the multirobot system’s spatial distribution and

mobility can be utilized in a novel way to create dis-

tributed measurement devices in which each robot has

an role as a part of the device, and in which the mo-

bility of the robots provides ﬂexibility to the structure

of the measurement system.

The aim of this research is to develop multirobot

systems which help humans to have meaningful infor-

mation from (remote) environments and its objects.

This information is then used to analyze the state of

the environment or to execute multirobot tasks au-

tonomously.

Based on the presented experiments, our purpose

is to go toward more demanding implementations

on which a person can instruct a multirobot system

to measure selected objects of the environment af-

ter which the robots take their positions and cooper-

atively gather information, like range data, about the

objects.

ACKNOWLEDGEMENTS

The authors gratefully acknowledge the support of the

Academy of Finland.

A MULTIROBOT SYSTEM FOR DISTRIBUTED SENSING

141

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