4‑4

4 Innovation Projects Innovation Initiatives

Utilization of Robotics Technology
in the Tokyo 2020 Games
NAKANO Tomohiro TODA Takahiro MORIDAIRA Tomohisa
NAKAYAMA Takahiro INAGAKI Yuji KUWABARA Takeshi

Various projects were implemented for the Olympic and Paralympic Games Tokyo 2020 to realize the Gamesʼ vision of“the most innovative Games in history bringing positive change to the world” This article introduces the various
initiatives implemented by Toyota Motor Corporation in the “utilization of robotics technology” which is a part of theseprojects
Keywords：Tokyo 2020 Games Autonomous mobility Remote control Communication network

1．Introduction
The Tokyo 2020 Robot Project Working Group wasestablished by TOCOG

(

)

(

)

Planning for spectator support using the
Human Support Robot (HSR)

Toyota Motor Corporation

Field Sport Support Robot (FSR) to support
competitions

Panasonic Corporation and experts to communicate to
the world how robots will accompany people and be11

helpful in various situations at the Olympic and

The T‑TR1 and the T‑TR2 are telepresence robots

Paralympic Games Tokyo 2020 (hereinafter referred tothat project images of a person from a remote location

as “Tokyo 2020 Games”) This article introduces thethat are realistic enough to make that person appear

technical outline of each projectright in front of you The robots combine communication

Torch Relay Project by T‑TR1 and T‑TR2

devices such as a camera microphone display and()

Torch relay project by telepresence robots (T‑TR1 and T‑TR2)

your own alter ego from a remote location The concept()

is to provide an opportunity for those who cannot comeTokyo 2020 mascot robot (MR) to support
spectators

speakers with a mobility platform to move around as

to the venue or those with a special interest in the event
to participate virtually and communicate with eachother As a specific project we aimed to connect the

NAKANO Tomohiro
Frontier Research Center TOYOTA Motor Corporation
E‑mail tomohiro̲nakano@mail toyota co jp
TODA Takahiro
Frontier Research Center TOYOTA Motor Corporation
MORIDAIRA Tomohisa
Frontier Research Center TOYOTA Motor Corporation
NAKAYAMA Takahiro
Frontier Research Center TOYOTA Motor Corporation
INAGAKI Yuji
Frontier Research Center TOYOTA Motor Corporation
KUWABARA Takeshi
CV Management Div TOYOTA Motor Corporation

torch in the torch relay as if the runners who could not

The Journal of The Institute of Electronics Information and Communication Engineers Vol 105 No 8 Supplement pp 220‑231 August 2022

(T‑HR3) and to provide a new way to enjoy the Games© 2022 The Institute of Electronics Information and Communication Engineers

220

participate in the event at the site were there
12

MR‑based Spectator Support Project

The basic concept of this project was to achieve
realistic remote spectating by utilizing the technology
cultivated through the development of a humanoid robot
without mobility restrictions

This is based on the

THE JOURNAL OF THE INSTITUTE OF ELECTRONICS INFORMATION AND COMMUNICATION ENGINEERS

“school collaboration spectating program” that would
provide opportunities for all public and private schools inTokyo wishing to watch the Games at the venues
On the other hand some children are not eligible forthe spectating program due to mobility restrictions suchas severe disabilities or illnesses We aimed to provide
these children with the opportunity to feel the atmosphere of the venues through robotics technology
During the reexamination of the event planning due tothe postponement of the Games by one year we had anin‑depth discussion about what MR could do to make thechildren smile who are restricted in many aspects such

Figure 1

as school events due to the coronavirus disease 2019

Spectator Support by HSR(COVID‑19) As a result we made significant changes
in the MR specifications aiming to significantly improve
the quality of the user experience such as having theGames mascots “Miraitowa” and “Someity” pop out fromthe digital world in a realistic size and dance with thechildren()

Static display in the athletesʼ village()

Seats‑for‑future‑stars project (venues ⇔ special‑needs schools)

13

Spectator Support Project by HSR

Figure 2

The HSR spectator support project was designed toCompetition Support by FSR (©2021‑International
Olympic Committee‑All Rights Reserved)

provide a stress‑free spectator experience for wheelchair spectators at the National Stadium The project
combines the robotʼs autonomous motion technology

make the games run more smoothlywith human remote‑control technology to guide the

The system consists of a Lidar cameras batteries

robot from the entrance to its seat collect trash takeand other components with an autonomous driving

commemorative photos

mode

and solve other problems

a person‑following modea mode to avoid(Figure 1) The robot is characterized by its ability tocollisions with objects a manual driving mode and an

operate in large areas where many people pass by andemergency stop modethe fact that multiple robots combining autonomous

For the Tokyo 2020 Games the following two points

operation and remote control can operate simultane-

were emphasized in the development and operation ofously

the system

14

Competition Support Project by FSR①

quickly as possible

The FSR was developed as a robot to assist thethrowing and rugby sevens while working close topeople (Figure 2) In the track and field events FSR

To return objects that are thrown to athletes as②

To reduce the distance for the officials by even asingle step

used AI and robotics technologies to carry andautonomously transport the objects that were thrown

2．Communication Infrastructure

and recovered by officials thereby helping to reduce
recovery time and reduce the physical burden of theofficials and in the rugby sevens the FSR autonomously

21

Overall Overview

In the robot projects () () and () mentioneddelivered and dropped the ball by a mechanism at theabove it was necessary to operate the robot from acenter of the field immediately before kick‑off to help

remote location via a communication network so with

Special Issue : Technology and Innovation in the Olympic and Paralympic Games Tokyo 2020221

Figure 3

Figure 4

Complete Overview

Overview of Communication Infrastructure Technology in the T‑TR1/T‑TR2 Project

the cooperation of the NTT Group we built a dedicatednetwork using a closed area optical network andcommercial 5G mobile network services

22

OverviewofCommunication

Infrastructure

Technology in T‑TR1 and T‑TR2 Planning

In places

The plan to remotely control a robot on the wheelchair

where commercial 5G mobile network services werefrom a hospital in Aichi Prefecture to run as aunavailable we used a 4 9 GHz band wireless accesstorchbearer was realized by connecting the operator

system (JRC JRL‑849AP2/E) in combination with aside o a bandwidth‑guaranteed optical fiber line and the

local radio (Figure 3) Project () used LTE mobile

robot side to a commercial 5G mobile network Video

network service and a 169 MHz band radio developed foraudio and control data were communicated using an

this competition as local wireless communication

external connection service that supports the WebRTC

222

THE JOURNAL OF THE INSTITUTE OF ELECTRONICS INFORMATION AND COMMUNICATION ENGINEERS

Figure 5

Overview of Communication Infrastructure Technology for the MR Project

Figure 6

Overview of Communication Infrastructure Technology in the HSR Project

protocol via a security gateway (Figure 4) A 5G/LTEside to the robots to realize remote control

gateway terminal (IDY IR‑730B) for small embedded

A compact 5G communication modem (TELIT FN

products was built into the robot to ensure high

980 m) and a dedicated antenna were installed in thereliability in high‑temperature environments An accessrobotspoint for the 4 9 GHz wireless access system was also
installed as a backup line on the Toyota Motor
Corporation Head Office Factory side24

OverviewofCommunication

Infrastructure

Technology in the HSR Project
The robots at the National Stadium from Aichi

23

OverviewofCommunication

Infrastructure

Technology in MR Project
Remote viewing using robots was realized by connect-

Prefecture (Toyota Motor Corporation Head Office) andTokyo (Toyota Motor Corporation Kudan Office) wereremotely controlled by connecting the venues with aing schools/hospitals in Tokyo to the Games venues

bandwidth‑guaranteed optical line

connecting the control devices at the schools/hospitals

Stadium the necessary number of access points for theusing closed optical fiber lines and connecting the robots

4 9 GHz wireless access system was installed to coverinstalled at the Games venues using commercial 5G

the entire area within the robot moving area of the 1F

mobile networks (Figure 5) Video data from the robot

concourse (Figure 6) In addition due to the decision tocamera were sent from the Games venues to the school

make the entire stadium spectator‑free due to theside and control commands were sent from the school

declaration of a state of emergency as part of theSpecial Issue : Technology and Innovation in the Olympic and Paralympic Games Tokyo 2020

In the National

223

COVID‑19 infection control measures a small LTE

Although the number of high‑speed large‑capacity

gateway terminal (IDY IR‑720B) was built into theand low‑latency means of communication will increase

robot and usedwith the evolution of communication technology we

The WebRTC protocol was used for bi‑directional

believe that further innovation is required to stabilize thecommunication for video audio robot control sensor

remote operation of robots and we plan to promote

information etc

research and development for the same

25

OverviewofCommunication

Infrastructure

Technology in the FSR Project

3．Key Technological Elements of Each Robot

We used the proprietary 169 MHz radio system for

31

robot control and emergency stop This radio system311

could operate 10 units/ch and four radios on the control
side and four radios on the robot side were all operated

Key Technologies in T‑TR1 and T‑TR2
Development to Enhance the Sensation ofBeing in Remote Locations

A system was constructed to enable a user to operatea robot using the wheelchair usually used by the user

on the same frequency and used jointly

The system configuration is shown in Figure 7 The
26

Summary of Communication Infrastructure

wheelchair speed is identified by outputting parallel

we built a dedicated closed network

values from the left and right encoders positioned on theconsidering security aspects and the communication

chassis are converted to angular values by an interface

necessary for remote control/operation

emergency(I/F) device and input to the Portal‑PC at the remoteof the robots were successfully and securely

location via the Web USB protocol The client application

This timestoprunning on the Portal‑PC generates straight movement

operateda dedicated closed network was con-and turning commands based on the values obtained bystructed considering security and the communication

the I/F device A TWILIO API is used to transmit thesenecessary for remote control/maneuvering and emer-

commands to the robots via the internet

This time

gency stop of the robot was successfully and securely

Next on the robot side the robot application runningon the Upper‑PC for communication mounted on theoperated
However since the line quality of the communication

upper part of the main unit obtains these command

there was a lack ofvalues which are converted to Robot Operating System

consideration for fluctuations on the robot system side

2 (ROS2) Topic via the WebSocket protocol andwhich posed some problems with stable operationtransmitted to the Lower‑PC for mobility control

network fluctuates constantly

Figure 7224

System Configuration for Wheelchair Operation

THE JOURNAL OF THE INSTITUTE OF ELECTRONICS INFORMATION AND COMMUNICATION ENGINEERS

Figure 8

System Configuration to Enhance the Impression That a Person in a Far‑away Location Is Present

mounted on the lower part of the main unit Lower‑PC

the top of the robot at the front and rear The images

then converts the command values to the CAN Openfrom the front‑facing camera are shown on the rear‑

protocol and transmits the values to the motor amplifier

facing display while the images from the rear‑facing

With the above hardware and software configuration
we could confirm that the robot can move forward andturn via the internet

Howevercamera are shown on the front‑facing display
The remote side also had two cameras installed

when confirming

Portal Cam1 and Portal Cam2 to capture images of theoperations using the actual robot it was found thatfront and rear sides of the remote user The Portal‑PC

delicate control of the robot using only the remoterecognizes and extracts the user from the images

Portal‑PC was difficult due to delays in internet

obtained from Portal Cam1 and Portal Cam2 based oncommunication the responsiveness of the motor ampli-

the Background Matting method (1) to improve thefier the condition of the road surface and other factors

accuracy of compositing the image of the remote user

As a resultwith the background image

control from a remote location wasrestricted to movement in a straight line only If the

The images displayed on the robot are captured by the

robot strays off course a safety operator close to thetwo cameras mounted on the robot via the GStreamer

robot will override the remote control with a signal fromframework to the upper‑PC At the same time thethe 920 MHz wireless controllers to correct the robotʼs

images of the front and rear of the user captured by the

position

Portal Cam1 and Portal Cam2 cameras on the remoteside are acquired via the internet On the front display of

312

Development to Enhance the Impression that a

the robot the image behind the robot is cropped andPerson in a Remote Location is Present

used as the background image for the front display andWe have developed a system that composites images

the front view of the user at the remote site is

obtained from the cameras mounted on the robot withcomposited and displayed On the rear display theimages of the remote user to effectively project theimage in front of the robot is cropped and used as the

remote user onto the robot and enhance the impression

background image for the rear display and the backthat the remote user is present In particular since theview of the user is composited and displayed

T‑TR2 is equipped with displays on the front and rearsides of the robot by synthesizing images of the remote

32

Key Technologies in MR

user with images obtained from the robot cameras we

321

aimed to create the impression as if the user were

In the new model we aimed to significantly improve

Emotional and Facial Expressions

running in the torch relay The system configuration is

the physical expressiveness and the quality of appear-

shown in Figure 8

ance of the mascots (Figure 9) while maintaining the

The displays are mounted on the front and rear

mascotsʼ lovability Each arm and leg has 6 degrees of

surfaces of the robot and two cameras are mounted on

freedom enabling a variety of bipedal walking andSpecial Issue : Technology and Innovation in the Olympic and Paralympic Games Tokyo 2020

225

Figure 9

Figure 10

Figure 11

Soft Skin of MR (©2021‑International Olympic
Committee‑All Rights Reserved)

Figure 12

MR Maneuvering (©2021‑International Olympic Committee‑All Rights Reserved)

Appearance of MR (©2021‑International Olympic
Committee‑All Rights Reserved)

Various Emotional Expressions by Stationary Display(©2021‑International Olympic Committee‑All Rights
Reserved)

piece which enables various movements even in areas
where three degrees of freedom are concentrated such

dancing steps For further improvement of expressive-as the hip joint and a wide range of motion while

ness we increased the number of joints on the waist andmaintaining the outlines of “Miraitowa” and “Someity”

neck and the mascotsʼ height was increased by only

In addition superior high‑performance polyester fabric

about 5 cm despite adding a total of 8 degrees ofis used as soft skin over the entire body covering thefreedom

joints to achieve a realistic appearance (Figure 11)

In addition to physical expressions with a wide range

The use of soft shells and soft skins not only improvesof DOFs the mascot robots also feature emotional

the appearance of the robots but also allows for aexpressions by animating the eyes (Figure 10)

maximum range of motion of the joints despite the

The eye area is designed to be prominent on the
robotʼs face with high curvature Flexible OLED displays

extremely short leg length

resulting in the robots

having a high level of physical expressivenessare bent into a two‑dimensional curved surface andmounted on the robotʼs face to display natural eye

322

expressions A thin acrylic lens protects the display

In pursuit of realistic motion for the mascot robots asurface with a two‑dimensional curved inner surface

special remote‑control method was adopted where theand a three‑dimensional curved outer surface

robot reflects the operatorʼs movements in real‑timeIn

Remote Control System

addition to the excellent color reproduction of the(Figure 12)

display the curved surface provides a wide viewing

position and posture of the upper body based on theangle to enhance the visibility of emotional eye

position and posture information from the VR equipment

expressions(11 tracker devices including the headset) worn by theThis control application converts the

The exterior uses a soft shell made of Agilus30 a

operator handling the differences in physicality (sizerubber‑like material fabricated by a 3D printer The

and joint range of motion) between a human and thehardness of the soft shell varies depending on the part ofrobot Furthermore the position and posture commands

the body with the hard and soft parts molded as a single

are corrected according to the robot shape to prevent

226

THE JOURNAL OF THE INSTITUTE OF ELECTRONICS INFORMATION AND COMMUNICATION ENGINEERS

Figure 13

Conversion Process from Human Motion to Robot Motion

Figure 14

System Configuration for Self‑position Estimation

self‑interference and transmitted to the robot side as a

Lidar face a problem in that the accuracy of self‑position

target command (Figure 13)

estimation is significantly reduced in a dynamic environ-

The robot autonomously performs feedback control toment where many people pass by For this reason we

maintain its balance while following the instructed joint

developed a method for stable self‑position estimation byposition and posture information in real‑timepointing the camera to the ceilingThe

operator can intuitively operate the robot as if they werewhich is lesssusceptible to dynamic objects (Figure 14)

controlling it from within since the operator receives

Self‑position estimation is performed by mapping theaudiovisual information recorded by the robotʼs onboard

feature points obtained from the images of the stereo

camera and microphone that is reproduced through thecamera pointed at the ceiling to a map which is a set ofhead‑mounted display In addition the headsetʼs eye

feature points The odometry calculated by combining

tracker acquires information on the operatorʼs pupil

the outputs of the HSR wheel encoder and IMU is fused

movement and eye‑opening and closing

which iswith an extended Kalman filter and output as the final

reflected in the robotʼs eye animation in real time Whenself‑position The following improvements were madethe robot spots a person it first follows the person withregarding feature point‑based Visual SLAM (2)its eyes and then turns to face the person enablingnatural interaction

These remote‑control functions()

To eliminate the influence of dynamic objects

allow the operator to act as a performer and control thesuch as people during mapping the self‑position

mascot robot

estimation results from 2D Lidar are highly
accurate in static environments and were input as

33

Key Technologies in HSR

331

Mobility Technology

General autonomous mobility algorithms using 2D

reference values for the optimization process()

Maps created at different times were synthesized to cope with changes in lighting due to time

Special Issue : Technology and Innovation in the Olympic and Paralympic Games Tokyo 2020

227

variations Combinations satisfying the criteria

and carriage using a mouse or device connected to a PC

for self‑location estimation performance were

for remote control (Figure 18)

selected and synthesized from test data multiple
times
(

)

The remote‑control screen features an autonomous
movement function and a 3D view When moving along a

To improve the recovery rate when self‑

predetermined route the robot moves autonomously byposition estimation fails only a certain area from

specifying a destination

the map was used for matching centered on the

movement within the concourse of the National Stadium

self‑position immediately before the failure

On the other hand the game controller is used toThis function is used for

maneuver the robot around the wheelchair spectator
A map of the actual National Stadium is shown inseats

The 3D view displays a composite of static

Figure 15 The blue dots in the figure are feature points

structures such as pillars and dynamic information suchobtained from the ceiling stereo camera Figure 16

as surrounding obstacles and people recognized by theshows the relationship between the movement locus androbot (Figure 19) The robot uses a wide‑angle camera

the self‑position estimation error and Figure 17 shows amounted on the robot while maneuvering to see

histogram of the estimation error The root mean square

wheelchair spectators and a 3D view to grasp obstacles

error (RMSE) of the self‑position estimation wasin the vicinity The viewpoint in the 3D view can be

0 084 m and the 3σ range of the error was 0 19 m

freely moved allowing the user to zoom in to see

indicating that a highly accurate self‑position estimation

obstacles near the robot in detail or to see thewas achieved

approximate location of obstacles using zoom out(Figure 20)332

Remote Control System

The remote operator controls the robotʼs head arm

The robot is equipped with the following safety
features to prevent collisions with people due toerroneous operation allowing the robot to be remotely
controlled with peace of mind ① An imitation function

Figure 15

Map Created by VSLAM

Figure 17

Figure 16

228

Relationship between Movement Trajectory andEstimation error

Histogram of Estimation Error

Figure 18

Remote Control System

THE JOURNAL OF THE INSTITUTE OF ELECTRONICS INFORMATION AND COMMUNICATION ENGINEERS

Figure 21

34

Lidar

Key Technologies in FSRThis section introduces “Autonomous driving” andFigure 19

Control Screen Used by the Remote Operator“Person‑following” from among the five modes of“Autonomous driving” “Collision avoidance” “Person‑
following” “Manual driving” and “Emergency stop”
341

Autonomous Driving

At the return position the official working with the
FSR covers the touchless switch at the top of the FSR byhand to activate autonomous driving mode
In autonomous driving mode information about the
distance travelled obtained from the vehicle speed
sensors installed at the rear wheels information about
the location of the FSR obtained by comparison between
a prepared map of the Competition Venue and the shapeof the Competition Venue measured by lidar during FSR
operation and Real Time Kinematic-Global Navigation
Satellite System (RTK-GNSS) information are combined
to estimate the position of the FSR and guide it to thetarget destination
The New National Stadiumthe venue for thethrowing events at the Tokyo 2020 Games

has amaximum distance of approximately 130 meters between the walls of the competition field Therefore the
FSR was equipped with a 200‑meter‑class Lidar toensure reliable measurements (Figure 21)
Vehicle speed sensors of the hall integrated circuit(IC) type are attached to the FSR rear differential joint
Figure 20

3D View of Obstacles in the Vicinity

cups These sensors are synchronized with the tire
rotation to output four pulses per rotation The FSR
speed is calculated from the sensor information on boththat automatically adjusts the direction of movement so

the left and right wheels to improve accuracy and realizethat the robot follows the shape of the obstacle This

fail‑safe operation

function is mainly effective for static obstacles ② A

The FSR is capable of nine degree‑of‑freedom (DOF)

virtual bumper function automatically stops the robot

acceleration

before physical contact with an obstacle that thesensor installed on the vehicle control interface board

imitation function cannot avoid This function is mainly“Moab” kept in the rear ECU box

effective for dynamic obstacles

This function utilizes an acceleration

The Moab board is the most important control board

Special Issue : Technology and Innovation in the Olympic and Paralympic Games Tokyo 2020229

Figure 22

Vehicle Control Interface Board “Moab”

Figure 24

Boundary Box Formed by AI

created by the horizontal Lidar beam in the horizontal
angle region defined by the boundary box is used as the
distance to the competition official

The processdescribed above is carried out for each frame and the
FSR is controlled to remain at a distance of three metersfrom the competition official (Figure 24)
By combining a web camera with AI and Lidar we
Figure 23

Heat Map Created by AI Analysis

could realize the following function with compact andagile processingin the FSR since it connects the drive control steering

4．Conclusion

and autonomous driving systems It was designed toemphasize reliability and features a simple microcom-

The Robot WG was able to carry out its plans albeit

puter and input/output (I/O) devices To prevent thewith some modifications in scale and content in the face

FSR from rolling over when steered the Moab boardof repeated adversities including the first‑ever post-

also incorporates an algorithm restricting the maximum

ponement of the Games due to the COVID‑19 criticalsteering angle following the vehicle speed (Figure 22)

public opinion and the fact that the Games were held

In autonomous driving mode the FSR operates along

without spectators

This was due not only to thea pre‑set route The driving route was studied using AI

members of the Robotics WG but also to the support anddeveloped by Toyota Motor East Japan Inc A heat map

cooperation of the Organising Committee and Gamesof the positions of the competition officials and camera

volunteers and we must thank all of them for theircrews was created using AI analysis of images taken byefforts

fixed‑point cameras Based on this heat map the routes

The participation and cooperation of the volunteerof the FSR were designed to avoid interaction withstaff members in all of the planning sites resulted frompeople as far as possible (Figure 23)

their shared desire to enliven the Games and make themeven better We believe that we were able to realize a

342

Person‑following

In person‑following mode the FSR uses AI to drive on
the field behind a event official

project filled with smiles because we could look forward
together
Again a large‑scale demonstration event cannot be

The FSR is equipped with a commercially available

accomplished by an individual It can only be realized

C930 web camera manufactured by Logicool Co Ltd In

with the cooperation of all parties involved so finding as

this mode the AI recognizes a competition official frommany people as possible to work together is desirable

RGB images obtained by the camera and creates a

What we feel is necessary for this is to recognize theboundary The target angle to the competition official isdiversity of ideas (tolerance and respect) to remember

calculated using the center point of the boundary box

the spirit of cooperation (mutual aid) and to remember

Next the point closest to the FSR from a point groupthe spirit of gratitude and consideration Finally we

230

THE JOURNAL OF THE INSTITUTE OF ELECTRONICS INFORMATION AND COMMUNICATION ENGINEERS

would like to thank everyone involved for theirunderstanding cooperation and guidance in progressing with this grand project Thank you very much
References()

S. Sengupta, V. Jayaram, B. Curless, S. Seitz, and I. K-Shlizerman,“Background matting : The world is your green screen,” Proc. IEEE
Conf. Computer Vision and Pattern Recognition (CVPR) 2020, pp.
2288-2297, Seattle, USA, 2020.
( ) R. Mur-Artal and J.D. Tardos, “ORB-SLAM2 : An open-source SLAM
system for monocular, stereo and RGB-D cameras,” IEEE Trans.
Robotics 2017, pp. 1-8, 2017.
(Accepted March 18 2022 ; Revised April 4 2022)

NAKANO Tomohiro
He graduated from Nagoya University in2001 completed the masterʼs course at thesame university in 2003 and joined Toyota
Motor Corporation in the same year He wasengaged in analytical work related to next‑
generation battery materials Currently heworks in the Socio‑informatics ResearchGroup R Frontier Department where he isengaged in research on solutions to life issues
necessary for citizens to enjoy happiness insocial activities
TODA Takahiro
He graduated from the University of Mie in1999 completed a masterʼs course at the same
university in 2001 and joined Fujitsu Computer
Technology Limited in the same year He joined
Toyota Motor Corporation in 2009 where he
was engaged in the development of partner
robots Currently belongs to the Connected
Advanced Development Department He iscurrently engaged in the development of next‑
generation vehicle cockpits

NAKAYAMA Takahiro
He received his B S M S and Ph D
degrees in electronic engineering from Tohoku
University Sendai Japan in 1998 2000 and2003 respectively From 2003 to 2007 he was a
Research Associate at New Industry Creation
Hatchery Center (NICHe) Tohoku University
where he researched algorithms circuits andsystems for image compression transmission
and recognition In 2007 he joined Toyota
Motor Corporation Aichi Japan He is currently engaged in research and development of
telepresence robot systems Dr Nakayama is amember of the IEEE Signal Processing Society
and the IEEE Circuits and Systems Society
INAGAKI Yuji
He graduated from the Faculty of Engineering Faculty of Engineering Department ofElectronics in 1991 and joined Toyota Motor
Corporation in the same year Since then hehas been engaged in product design andproduction technology development of in‑vehicle electronic components Currently heworks at the Robotics Research Unit R
Frontier Department Toyota Motor Corporation He is engaged in research and development to realize remote service by robots using
next‑generation communication technology
KUWABARA Takeshi
He graduated from Keio University in 1992
completed the masterʼs course at Keio University in 1994 and joined Toyota Motor Corporation in the same year He was in charge ofchassis design mid‑to‑long‑term R&D strategy planning Toyota Motor Europe and FSR
development leader Currently he is engagedin overall technical development at Toyota
Auto Body Co Ltd

MORIDAIRA Tomohisa
He graduated from the Tokyo Institute ofTechnology in 1996 completed the masterʼscourse at the same university in 1998 andjoined Sony Corporation in the same year He
joined Toyota Motor Corporation in 2008
where he was engaged in humanoid robot
development Currently he is engaged in thedevelopment of avatar robots and remote‑control systems as a manager of Dynamic
Robotics G R Frontier Department㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇㍇

Special Issue : Technology and Innovation in the Olympic and Paralympic Games Tokyo 2020231