"©2008 IEEE. Personal use of this material is permitted. However, permission toreprint/republish this material for advertising or promotional purposes or for
creating new collective works for resale or redistribution to servers or lists, or toreuse any copyrighted component of this work in other works must be obtained
from the IEEE."

Proceedings of the 2008 IEEE
International Workshop on Safety, Security and Rescue Robotics
Sendai, Japan, October 2008

Validat'ion of Simulated Robots wvith Rea'i'sticall
Modeled3 Ditensions an Mas s in uS Si.
__-

T-

-

-w~- -r -*Shogo Okamoto, Kensuke Kurose, Satoshi Saga, Kazunori Olino and Satoshi Tadokoro
Tohoku University, Sendai, Japan{okamoto, kurose, ohno, tadokoro} @rm.is.tohoku.ac.jp, saga@fractal.is.tohoku.ac.jp

Abstract -In the case of simulators of mobile robots, it isnecessary to clarify the similarity between actual and simulated robots
in order to improve the efficiency and transparency of simulators
as research tools. Because of its real-time performance, USARSim [1] has been popularly used in studies involving human-robot
interactions. However, since USARSim uses approximations andabbreviations in its physical computations, there are some doubts
over its computational accuracy.

regard to the traversing abilities, the sizes of the obstacles
that are traversed rather than the dynamics of the robots arecomass of the simulated robots are accurately modeled and thephysical parameters are not. First, the authors have assumed
that the ability of the response robots to traverse around simple
obstacles significantly depends on the dimensions and masswithusin the sim edion s
ofsthe s Hen e, byby using
the simulated robots withof the robots. Hnce,
accurately modeled dimensions and mass, we can determine
the capabilities of the actual robots. Second, measuring thephysical parameters of the real robots takes time and also ishigh in cost. Finally, the approximations and abbreviations

The objective of this study is to compare the actual and simulated
robots in order to investigate whether the simulated environments
can be used as a training tool. The authors modeled two types of
response robots -IRS Soryu [2] and Kenaf [3]- and compared theabilities of the simulated robots and the actual robots in navigating
obstacles such as steps and trenches. The dimensions such as heights,
widths and lengths and total mass of the real robots were accurately
modeled in the simulation and the other physical parameters wereof the physical computations in USARSim are significant.
Some physical parameters such as kinetic friction and static
friction coefficients are not configurable. Even if the configurable parameters are accurately reproduced in the simulator,
the dynamic interactions between the robots and the virtualassigned default values. It was observed that the maximum error in
the sizes of the traversable objects was 18 % of the body length of
the robot. It was also found out that the angular velocities of therobots were significantly different for the real and simulated robots.
The conclusion is that a training system can be built based on
USARSim when the simulated environments involve simple obstacles
because there are not significant discrepancies between the basic
traversing abilities of the actual robots and those of the simulated
robots. However, in terms of the dynamic motions of the robots theoperators need further trainings using the real robots.

environments are not expected to match those of the real robots
in an actual environment.
B. USARSim and Related Stadies about Validation

Keywords: USARSin, IRS Soryu, Kenaf, Response Robot

Rescae Robot

USARSim is used as a 3D simulator in this study. A
3D simulator was chosen on the basis of its applications.
The simulators with high physical fidelity and small time
steps of computation are qualitatively different from real-time
simulators, which can handle multiple robots and large areas
simultaneously. Real-time simulators are suitable for the training tools. There exist several 3D simulators for robots such asOpen Dynamics Engine and Microsoft Robotic Studio [4]. In
order to impart effective training in the teleoperation of the
response robots it is necessary for the simulator to have realtime abilities, high-quality images, easy handling of multiple
robots, easily developable large environments, and extended
connections to other software, if required. USARSim satisfies
all these conditions. In addition, USARSim has also beenutilized in the RoboCup Rescue Virtual Robots Competition[5] and it has been used in several studies on mobile robots.
The biggest concern about USARSim is its computation accuracyz. ThS iS because it uses approximations of the phytsicalcomputations to maintain real-time performance and becauseof its lnondisclLosure of proprietary parts of the physics elngilne.
It is necessary to validate both the simulated robot models and

I. INTRODUCTION
3D simulators play an important role in the development
and training of mobile robots. In particular, simulators serve as
good tools for training first responders in the teleoperation of
response robots used in disaster management. First responders
can practice maneuvering the robots in various virtual disaster environments rather than in actual environments, which
reduces the risk as well as the cost of testing.
The authors have employed the USARSim, which is a
3D simulator, for training operators who conduct search andrescue tasks in confined spaces such as underground cities
during NBC terrorism activities or during natural disasters.
A. Research Objectives
This study investigates the performanlce of USARSima inl
andsimnulating respolnse robots iln order to test its efficielncy dT:transparency as a research and training tool. We compare thetraversing abilities of real robots and simulated robots thathave the same dimensions and mass as the actual robots. With
978-1-4244-2032-2/08/$25.00 ©)2008 IEEE.

dcomparedi
There are three major reasons why the dimensions and total77

the physical accuracy of the simulator in order to ensure its
reliability as a training and research tool.
Several researches have validated the computation accuracyof USARSim. Carpin et al. evaluated the images provided by
the simulator by taking into account the distance of the robot
from the target objects and the lighting conditions [6]. Wanget al. compared the consistency in the performances of realand simulated range finders [7].
USARSim has also been validated in HRI (human-robot
interaction) researches. For example, it was experimentallyconfirmed that the metrics of HRI such as the task duration andthe number of command inputs were almost identical in tasks
performed by operators with real and those performed withsimulated robots in similar environments built in the simulator[6-8]. Thus, these studies validated the use of USARSim
for HRI researches as well as the accuracy of the simulated
sensors.

of the robots. The metrics from the Response Robots Pocket
Guide [14] are suitable for this study. The guide proposes for
instance, random step fields, stairs, slopes, and steps as metrics
of traversing abilities of the robots.
The authors evaluate the traversing abilities for possible
obstacles in underground cities. In the event of an NBC
terrorism attack on an underground city, stairs and sign boards
are considered to be step-like obstacles, while drains behaveas trench-like obstacles. Therefore, the authors measure thetraversing abilities of the robots for steps and trenches. It
is difficult to simulate piles of rubble or fragile ground in
USARSim and hence the authors have assumed that theenvironment does not include them.

II. ROBOT MODELS IN USARSIM
The authors have simulated two types of response robots,
simulate robots have been tested in some previous studies. IRS Soryu[2] and Kenaf[3], and compared them with the acrobots. Both robots are highly adaptable and can transform
Greggio et al. modeled a humanoid in USARSim and com- tual
theirmechanisms to surmount obstacles that have a greaterpared its performance with that of a real robot with respect height than them. It is necessary for operators to undergoyto some features such as walking trajectories [9]. One of tig in overcominggthe methods to ensure that the behavior of simulated robotss raiingostals
while manu o aresembles that of the real robots, is tuning of the physicalparameters of the simulated robots by repeated tests and A Physics Engine of USARSim
constant observation of the behaviors of the robots [10][11].
A physics engine called Karma is installed on USARSim.
In the above mentioned studies, the researchers designed thesimulated robots by tuning the parameters, and they also In the simulator, physical computations are performed forpresented discussion on the similarities between the real and objects designated as Karma objects. The other objects arereferred to as static objects, i.e., objects which do not move.
simulated robots.
This study focuses on how similar the traversing abilities Physical phenomena such as collisions, inertia, and rotation areof simulated robots are to those of real robots when the computed for Karma objects. Mechanical impedances between
simulated robots have been modeled by ignoring the physical the Karma objects are also taken into consideration during theparameters but ensuring that both of the dimensions and the computations. The configurable physical parameters are mass,
total mass are equal to those of the actual robots. Hence, this the spring coefficient, the viscosity between two connectedstudy is different from the other related studies, although the objects, the restitution coefficient, the inertia tensor, the center
authors have the same motivation as in the previous studies in of mass, etc. In USARSim, mass is treated as a concentrated
validating USARSim and utilizing it for HRI studies and in load. Details on how the parameters are computed in the engine are not provided. However, according to the experienced
teleoperation training.
Currently most robots realized in USARSim are modeled model creators, the friction parameter known as KFrictiorn
with the correct dimensions; however, the other physical needs to be carefully tuned [.0][1 1]. KFriction is a kindparameters are likely to have some default values. This may of the friction coefficients and considered to serve as thebe because many researchers have utilized USARSim for HRI static and kinetic friction coefficients. Two types of fiction
studies and not for studying the dynamics of robots. In the parameters are applied to tires in USARSim. They are named
case of these robots, it is helpful to clarify the similarities and TireRollFriction and TireLateralFrictiosn and they are
discrepancies between the real robots and simulated robots that friction parameters for rolling direction and lateral directionof the tires respectively.
have the same dimensions and total mass as the real robots.
In the real robots used in this study, in order to increase
C. Evaluation Methods
the traction between the tracks and the ground, tread lugs are
Common metrics for mobile robots include the performance crafted on to the belts of the two robots as shown in figs.
measurements for navigation tasks, perception of environments 1 and 4. The authors have used a sufficiently high value ofand the states of robots, managements of multiple robots, and KFriction in order to ensure that the tires of the robots do
so on [1L2]. The test arenas of NIST evaluate the integrated lnot slip. The other physical parameters are lnot specificallyabilities of the operators along with those of the robots based designed and use default values. It should be nloted that theon the numuber of the searched victimas and the accuracy of the most practical method to design other physical paramneters is toreported positiolns of the victimus alnd so oln [5] [13]. HEowever, tunle the parameters by repeated tests and conlstant observation
the aima of this study is to evaluate the traversing abilities of the behaviors of the robots in USARSim [9] [11].
78360 mm'°35.5t~~~~~~~~~~~~~~ r=045m~~=

Fig. 3. Track of simulated IRS Soryu

Fig. 1. IRS Soryu

Fig. 2. Simulated IRS Soryu

cities. Its entire torso is covered with two independently driven
tracks that prevents it from being stuck on obstacles. Four
independent flipper arms are installed on it, and rolling themenables it to overcome the obstacles. Kenaf won the mobility
challenge in the Rescue Robots 2007 league. It is battery
powered and does not have tethers.
Kenaf is 20 kg and the dimensions are 570 mm x 180 mm(height) x 430 mm (width). The traversing abilities of Kenaf
are tested in the next section.
2) Simulated Kenaf: Fig. 5 illustrates Kenaf as simulated
in USARSim. The tracks are emulated as tire arrays. The
flipper arms are implemented using the Track class used in
the case of the simulated IRS Soryu. In order to emulate
the tracks of Kenaf, which cover the entire body, the tires
are arranged on the body, as depicted in fig. 6. The spaces
between the large tires are filled with small tires for imitating
the mechanism of the tracks that exert distributed driving
forces. The dimensions and the total mass of the simulated
Kenaf are the same as those of the real Kenaf. Fig. 6 shows
the dimensions of each part. The center of mass was located
15 mm behind the center of the torso, similar to the real
Kenaf. The friction parameters of the tires are configured as(TireRollFrictioTI, TireLateralFriction) = (1.3, 1.0) for
enhancing the traction. These parameters are much smaller
than those of the simulated IRS Soryu. This is because in caseof the simulated Kenaf with friction parameters higher thanthose set above, apparently unreal behaviors are observed.
III. EVALUATION EXPERIMENT

B. IRS Soryu and Simulated IRS Soryu
1) IRS Soryu: IRS Soryu is a serpentine robot that is used
for search and rescue at narrow spaces, as shown in fig.
1. The robot consists of three cars. Each car has a motor
and two tracks, one each on its left and right side. The
cars are connected by two axially connected actuated joints.
By controlling the positions of the three cars, the robot cansurmount the objects that are higher than it.
The dimensions of the IRS Soryu are 1210 mm x 122 mm(height) x 145 mm (width), and its weight is 10 kg. It isbattery-powered. The robot has a tether for communicatingwith the operator and providing high-quality camera images.
Its maximum speed is 370 mm/s, the maximum step heightthat it can ascend is 483 mm, the maximal trench width ofcrossing is 590 mm, and the minimum turning radius is 410
mm.

2) Simulated IRS Soryua Fig. 2 shows an IRS Soryu simulated in USARSim. It has the same dimensions and total massas the actual robot. The front and rear cars are 3 kg each andthe center car is 4 kg. The centers of mass are located in thecenter of each car. The joints between the cars are modeled
as two axial hinges. Their maximal angles are ±w/4. The
maximal speed is 370 mins, which is the same as that of thereal robot.
USARSim does not have a virtual equivalent of the rubber
belt. Therefore, in USARSim, instead of the belt, a tire array
IRS Soryu also
the simulated
simulated IRSSoryuals
as a belt. Hence
HEence, theis emaployedisemployedasabelt.
has tracks comprising an array of two large tires and eightsmall tires, as shown in fig. 3. The small tires in the arraydo not interfere with each other. The angular velocities of thelarge and small tires are adjusted so that the equation

did0 = d202

In this section, the authors compare the traversing abilitiesof the actual robots with those of the simulated robots. The
metrics of the abilities are the maximal step heights andtrench widths that can be overcome by the robots. Figs. 7
and 8 schematically illustrate the robot traversing a step anda trench, respectively. In addition, in the case of IRS Soryu,(1)is equalized. In (1), dl, d2 are the diameters, and di, d2 are
the angular velocities of the large and small tires, respectively. These belt-like arrays of tires are implemented bycreating track objects from a Track class, which is a built-inclass of USARSim. The friction parameters of the tires are(Tir*RoliFriction, TireLateralFriction)=(10.0, 10.0).

These values are higher than the default values 1.0 so thatthe tires do not slip on the floor.__AX^

C. Kenaf anxd Simulazted Kenaf
1) Kenaf: Kelnaf is a response robot, shown iln fig. 4, which
is designed to function in confined spaces such as undergroundFig. 4. Kenlat

79

Fig. 5. Simulated Kenlat

TABLE II
COMPARISON OF THE TRAVERSIN( ABILITIES OF REAL AND SIMULATED

35nmm

i), 5

115mm

30

720mmu470mm_,

Real Soryu
Simulated Soryn
w';i

;|~0

430m

IRS S )RYU
Obstacle Type [mm]Step Height Trench Width Turning Radius
483
590
410
475
600
409
--

to complete the crossing. After all the trials were complete, theFig. 6.

authors trained him to cross the trenches, and he succeeded in

Tire arrays and their corresponding dimensions for the simulated

clearing the 600-mm wide trench. The disparity in the successrates was expected to have occurred because of the differences
the abilities of the operators. The authors consider that the
EXPERIMENTAL RESULTS t:)F THE SIMULATED IRS SORYU: SUCC~ESS IMin
simulated
IRS Soryu is fully capable of crossing a 600-mm
wd
rnh
RATES IN ASCENDIN(: STEPS ANt) CRt)SSINti TRENCHES
wide trench.
Trench Width [mm]The turning radius of the simulated robot was measured by
Step Height [mm]Participant 425 4O 475 00 5l.0 575 600 625
the following method. When the pitch angles and yaw angles
A
1.0
1.0
1.0
0
1.0
1.0
0.8
0
of the two joints between the three cars were maximally bent,
B
I.O i.O l.O0i.O 1.0 .0o 00
1.0 i1.000
1.0 I1.0 1.0conly one of the two tracks of each of the cars was in contact
with the ground. With this stance, the simulated robot was
the minimum turning radii of the simulated and real robots are able to turn in a very tight circle. The smallest radius of the. . ~~~circle drawnL from the cenLter of mass was 409 mm. This value
also compared. In the case of Kenaf, the positions and posturesof the real robot are sensed by a motion capture amera and was not affected by the speed of turning when the speed was
between 46-137.5 mm/s. However, for the speeds above 150
mm/s, the trajectories were shaky and not smooth and it wasdifficult to regard them as circles.
A. Evaluation of Simulated IRS Soryu
Table II summarizes the navigation performances of the
In order to investigate the performance of the simulated
realand simulated IRS Soryu robots. The maximal heights
IRS
three experiened participants were asked to takeofthesteps ascended by the real and simulated robots werepart in the experiments. They were asked to operate the robot
and make it ascend steps with heights ranging from 425-500 483 and 475 mm, respectively The difference between thesemm and cross trenches with widths ranging from 550-625 two values was 8 mm, which was smaller than the interval
mm. Trials for each obstacle were repeated five times. The of the tested steps, which was 25 mm. The maximal trench
simulated robot was placed to face the obstacles. The operators widths crossed by the real and simulated robots were 590 andoperated the robots using a bird's-eye view and were allowed 600 mm, respectively. These two values were also within theinterval of the tested trenches, which was also 25 mm. The
to change their viewpoints during the experiment,
minimalturning radius of the simulated IRS Soryu was 409
Table I shows the success rates of the experiments. In theThevalue was close to 410 mm which was the minimal*~~~~~~~~~~mm.
case of the simulated IRS Soryu, the maximal height of therr_radiusof the actual robot.
.
1
I~~~~~~~~~turlningascendable step was 475 mm. In the experiments that required
navigation of steps, all the participants showed similar success
B. Evazluationl of Simulalted Kenazf
rates. This was attributed to the fact that the obstacle wassimple and the differences in operating skills had no impact
In order to analyze the abilities of the real and simulatedon the results. Also, there was no time limit set for the trials, Kenaf robot, an experienced operator manually operated theand the participants could keep on making attempts until the robots and surmounted the obstacles. The heights of the tested
robot successfully climbed the steps. Therefore, no disparity steps were 50-350 mm, and the widths of the trenches were
was observed in the success rates.
100-400 mm. Two different conditions were used during theOn the other hand, in the experiments that involved trenches, ascension of the steps. The first was the condition in which thethere was a disparity in the success rates with respect to the operator did not activate the flipper arms and the robot traveled
trenches that were 600 mm in width. Participant C was not able forward at a speed of 100 min/s, The other was the conditionin which the operator activated the flipper arms to climb steps.
In the case where the operator did not use the flippers, they
were kept perpendicular along the Yaw axis. Both conditions_ miillustrated in figs. 9 and 10. In crossing the trenches, the~~~~~~~~~~~are,Xt
Step heightflipper arms were nlot utilized and the robot was driven at 100
Trnh withm ns. Each experimLental conditionl was attemupted only once.
Fig 7. Schemlatic view of a robot Fig. 8 Schemlatic view of a robot
The participalnt had a bird's-eye view durilng the operatioln of
the real and simrulated robots.
ascending a step
crsigatenc
Kenaf

EPRMNAFTAE

Soryu*

80

Simulated
Kenaf

M

Kenaf

Time
Fig. 11.

Successive pictures of the real and simulated Kenaf robots when they are crossing a 350-mm-wide trench at a constant speed of 100 mm/s
0.44 s

3.95 s

30

12

12

8

20

N4

o10

Ra

0

Real Kenaf-Sim. Kenaf
0

4

8

12

Fig. 13. Trajectory of the centers of mass of the real and simulated Kenafrobots on the x-z plane during ascension of a 100-mm-high step

Fig. 12. Transition in pitch angles of real and simulated Kenaf during
ascension of a-100-mm-high step

The experimental results are summarized in table III. The
table shows the success or failure of each trial. Both thereal and simulated Kenaf robots could ascend steps with amaximum height of 100 mm when their flipper arms were notutilized. On the other hand, when the arms were activated,the maximum height of the steps ascended by the two Kenafrobots was 300 mm. Inr the experimnent with the trenches, thewaswithsimulated Kerlaf was able to crossdo so. This co

widtrche,mm, while the real Kenaf was unable to do so. This caused

a disparity in the results. The authors now explain the reason
for this disparity.

Successive pictures of the real and simulated Kenaf robots
in motion when they were crossing a trench with a widthof 350 mm at a velocity of 100 minIs are shown in fig.
11. From the second and the last two pictures, it can beobserved that the real Kenaf could not cross the trench andfell down. In contrast, the simulated Kenaf did not fall down

and successfully crossed the trench. The pitching motion of

the simulated Kenaf was observed to be less than than thatof the real Kenaf. In particular, the angular velocity of the..v
pitch..
8x<

Kenaf~~~~~~~0-Simulated
06
X [mm]

Time [s]rsimulatedKenaf ablemm.Intoe ceroienc

02

ea

X X

_

Fig. 9. Kenaf ascelndin:g astep wheln Fig. 10. Kesnaf ascenldisng a step
thle flippers are activatedu
whlen thle flippers are perpendilcularsimulated Kenaf along its pitch axis was much less than thatof the real robot when the front part of the simulated robot
fell to the ground.
Fig. 12 shows the change in the pitch angles of the real andsimulated robots when both the robots climbed 100-mm-highn. hstpwihhefperaminaepndclroiin.Ite
the pitch angles increased as the robots came in contact
figure,with the step and then climbed over it. The transition of thepitch angle
g of the real Kenaf was relativelyy smooth whereasof the simulated Kenaf showed a zigzag motion. The~~~~~~~~~thatauthors observed the videos and assumed that this behaviorof the pitch angles was because the lugs among the tires
forming the tracks of the simulated robot got stuck on theedge of the steps. As a result, the pitch angle of the simulated
Kenaf took longer to reach its maximum value than the actual
Kenaf. After reaching the maximum value, the pitch angle of
the actual Kenaf dropped sharply to 0° because the torso of the
car that was inclined in the air landed on the ground. The pitch
angle of the simulated Kenaf also reduced to 0 after reachingits maximal value. However, the inclination of the simulated
Kenaf took 3.95 s to return to 00. This was much longer thanthe 0.44 s taken by the actual Kenaf. Therefore, during thefree-fall of the robots, the transitions in the pitch angles were~~~~significantly differenlt for the real and simLulated Kenaf robots.
~~~~Thesame trelnd was observed iln the case of a step with aheight of 50 mm. Table IV shows the comparison between
the real and simulated Kenlaf robots about the pelriods whenl
the inclinedl torso was iLn free fall andt thLe dilfference between
81TABLE III
RESULTS OF THE EXPERIMENTS IN NAVIGATION OF OBSTACLES BY REAL AND SIMULATED KENAF. S AND F STAND FOR SUCCESS AND FAILURE,
RESlECTIVELY
Obstacle Type [mm]Trench Width
Step Height
Without Flippers
With Flippers
100 200 300 350
100 200 300 350 400
50 10050
Real Kenaf
SFFS F11N
S
S
S
S
S
S
F
S S
F
Simulated Kenaf
S
S
S
F
S
S
S
S
F

TABLE IV

robots. The results indicate that the simulated robots can beCt)MPARIStON BETWEEN THE RESULTS tOF THE REAL AND SIMULATED

used for training for the environments with simple obstacles.

KENAF: TIME PERIOt)S UNTIL THE ROBOTS FELL Dt)WN ANT) MAXIMALP1ITCH ANGIES WHEN R01 OTS CLIMB1ED STEPIS

Step Height [mm]Real Kenaf
Simulated Kenaf
Relative Error [/c]Fall-down Period [s]
50
100
0.38
1.86
389

ACKNOWLEDGEMENT

This research was performed as a part of the NEDO Projectfor Strategic Development of Advanced Robotics Elemental
Technologies, High-speed Search Robot Systems in Confined

Max. Pitch Angle [deg]
50
100

0.44

10.9

3.95

14.7

798

35

24.1

28.5

Sacs

Spaces.
REFERENCES[1] S. Carpin, M. Lewis, J. Wang, S. Balakirsky and C. Scrapper, USARSim:the maximal pitch angles during the ascension of the steps.
The trajectories of the robots on the x-z plane when the
robots climbed a 100-mm-high step are shown in fig 13. It

a Robot Simulator for Research and Education

Proc. the 2007 IEEE

International Conference on Robotics and Automation, pp. 1400-1405

2007[2] S. Tadokoro, Special Project on Development of Advanced Robots for
Disaster Response (DDT Project), Proc. the 2005 IEEE Workshop on
Advanced Robotics and its Social Impacts, pp. 66-72, 2005
[3] T. Yoshida, E. Koyanagi, S. Tadokoro, K. Yoshida, K. Nagatani, K.

was observed that the trajectory of the real Kenaf was smooth,while that of the simulated Kenaf was in a zigzag form becauseof the same reason described above. The maximal disparity
between the two trajectories along the z axis was 29.0 mm.

Ohno, T. Tsubouchi, S. Maeyama, I. Noda, 0. Takizawa and Y. Hada,

A High Mobility 6-crawler Mobile Robot 'Kenaf', Proc. the 4the International Workshop on Synthetic Simulation and Robotics to Mitigate
Earthquake Disaster, p. 38, 2007[4] J. Craighead, R. Murphy, J. Burke and B. Goldiez, A Survey ofCommercial & Open Source Unmanned Vehicle Simulators, Proc. the2007 IEEE International Conference on Robotics and Automation, pp.

C. Conclusion of Experiments
The authors compared the maximal heights of the steps that
could be ascended and the maximal widths of the trenches

that could be crossed by real anld simaulated IRS Soryu and852-857, 2007
Kenaf. The difference in the sizes of the obstacles that could [5] S. Balakirsky, C. Scrapper and S. Carpin, The Evolution of Performance
Metrics in the RoboCup Rescue Virtual Robot Competition, Proc. thebe navigated by the real and simulated robots was maximally
2007 Workshop on Performance Metrics for Intelligent Systems, pp.
1100 mm, which was 18 % of the diLmensions of the Kenaf.
991-96, 2007
The authors also observed that with respect to the pitch angle[6] s. Carpin, T. Stoyanov, Y Nevatia, M. Lewis and J. Wang, Quantitative
Assessiments of USARSim Accuracy, Proc. the 2006 Workshop onof the robots, the time taken for the inclination to return to 00
Performance Metrics for Intelligent Systems, pp. 11I1-118, 2006
included an relative error of 800 W.
[7] J. Wang, M. Lewis S. Hughes and M. Koes, Validating USARSim for
Use in HRI Research, Proc. the Human Factors and Ergonomics Society
The authors suggest that the ability of the robots to traverse
Annual Meeting, pp. 457-461, 2005
simple obstacles depended on the dimensions and structures [8] 49th
G. Polverari, D. Calisi, A. Farinelli and D. Nardi, Development of anof the robots. Hence, the siLzes of the surmounlLtable obstacles
Autonomous Rescue Robot Within the USARSim 3D Virtual Environwere similar for both the real and simulated robots. However,
ment, RoboCup 2006: Robot Soccer World Cup X, Berlin, Springer,
pp.491-498, 2007
a comparison of the behaviors of the real and simulated robots
Greggio, G. Silvestri, S. Antonello, E. Menegatti and E. Pagello,
along the temporal axis reveald
diversities, Thelre- d[9] AN. 3D
alolng the temuporal axis lrevealed siglnifiLcalnt
Model of a Humanoid for USARSim Simulator, Proc. First
fore, as expected, the dynamics of the actual and simulated
Workshop on Humanoid Soccer Robots, pp. 17-24, 2006
and C. Scrapper, Robot Simulation Physics
robots were not similar. This situation can be improved by [10] C. Pepper, S. Balakirsky
Proc. the 2007 Workshop on Performance Metrics forthe inertaoValidation,
adjusting the inertia tensors or the locations ofajusting
the distributed
Intelligent Systems, pp. 97-104, 2007
s

t

t

s

[ 1] B. K. Taylor, S. Balakirsky, E. Messina, and R. D. Quinn, Design andValidation of a Whegs Robot in USARSim, Proc. the 2007 Workshop
on Performance Metrics for Intelligent Systems, pp. 105-112, 2007[12] A. Steinfield, T. Fong, D. Kaber, M. Lewis, J. Scholtz, A. Schultz andmass.

IV. CONCLUSION

The authors developed two types robots in USARSim andcompared their traversing abilities with those of the actual
robots. The simulated robots were developed with dimensions
and total maasses that were equivalenlt to those of the actual
robots. Their performnalnces were tested iln traversilng obstacles
such suchas
as stepsan
trenches. Ass aresuta esult of
test, tetep antrnchs.
o tet,
he simulated
lLmlatd
robots with realistically modeled dimensions and total mass in
USARSim exhibited a performance similar to that of the real

M. Goodrich, Common Metrics for Hum-nan-Robot Interaction, Proc. the
1st ACM SIGCHI/SIGART Conference on Huimnan-Robot Interaction,[[131 pp33-40,2006
A. Jacoff, E. Messina, B. A. Weiss, S. Tadokoro and Y. Nakagawa, Test
Arelnas anLd PerformanLce Metrics for Urbanl Search anld Rescue Robots,
Proc. the 2003 IEEE/RSJ InternationalL Conference on IntellLigent Robots
anLd Systemns,
pp. 3396-3403,
2003 Ver. 2008.1L, http://www.isd.
[14[L4]Response
Pocket Guide,
RobotsDel .nist .gov/US&R Robot Standards/Rohotguide2 008.
pdf

82