1 (課程博士(英文))別紙4Date ofsubmission (month day, yea】')

Jun Mlura

DeP幻'tment ofcoml〕utef science
StudcntlD Numbcl

and lnf01血atlon En曾ineering

へPP11Canl、s n田11e

March 15小,2019

D 113413
SupervlsoTS

Michio okada

KenjiKoide

Abst松d (Dod06
Title ofThesis

Pa'son ldentification and person'S A、入喰reness Estin〕ation for an Attendan{ RobotApprox.80O Wω'ds

Developed countries including Japan afe becoming aged societies, and they sufferffon) a cl)Tonic shortage of cafegivers.1n this decade, robotic caregiving has beenattractin曾 People's attention as a solution for the problen〕 and they are expected tobe deployed in the next decade.

In this tl)esis, we investigate a fobotic attendant system fof Cω、egivin牙.1n tl)isSystem, a fobot f0110ws a peTson and keeps him/her away fron〕 dangeTOUS

Situations.1n case tl)e person is going to be involved in an accident (e.g., bumping
into an obstacle and fa11in牙丘om a step), the fobot pTevents the accident byinteracting witl〕 him/1)ef (e.g., informing tl〕e person of the obstacle). However, if
the robot interacts W北h the P飢'son eveTy time it finds an accident risk, it could beannoying for the person. To be socia11y accepted, the Tobotic attendant systeln bas
to avoid disturbin今 the P田'son as long as l〕e/she is in a safe situation so that it
becomes con)fの'table foT the person. To minimize the Tisk of accidents while
maximizing the comfoTtableness of attendance, we focus on a person's awaTenessBy estilnating the person's awareness of obstacles, the robot can assess theC011ision risk and interact W北h the pa'son only when an accident is Hkely tohappen

F辻St, we pfesent robust person trackin曾 and identification methods. Attendantrobots have to be able to f0110w a speci丘C target pe玲on reliably.1n case th田,e are
Several peTsons, the fobot may lose track of the target person due to occlusion.1nSuch cases,北 is required to identify the target peTson an〕ong surrounding peTsons(i.e., re'identification) to xesume the tfacking and continue to f0ⅡOw tl)e target.＼入7ePropose online learnin牙、based peTson identification methods based on deepConvo]utional neural network、based appearance features and i111Unination

invafiant hei容ht and 曾a北 featufes. They can identify tl)e target peTson robustly in
SeveTe i11Un〕1nation environments. we also propose a weafable device・based

identification lnethod.1n this lnetl)od, we let the taτ牙et person hold a slnaTtphone
and identify hin]./her by lnatchin曾 the foot su,ike tin〕in今S detected by theSmartphone and the ones of surTounding pefsons detected by a laseT ranσe findern〕ounted on the robot. By combining the online leafning・based and weafabledevice、based identification methods, we Tealize a robust and reliable Pers01〕
f0110wing system

Second, we pTopose a system to measure and analyze real persons' attendin号
behavior.1n this system, an observef carTying a 3D LIDAR f0ⅡOws persons to bemeasured while keeping them in tl〕e sensor view.1t a110ws us to measure thebehavior of the peTsons W北hout area and tilne limitations. The system f辻St
Constructs a 3D enVⅡ'onmental map beforel)and and then estimates the sensor
Pose and t王acks suTfoundin今 People online. As a field test, we measured thebehavior of professional caTe曾ivers attendil〕g an eldefly with delnentia in ahospital. A prelin〕inaTy analysis ofthe attendant behavior reveals how they decide
the positioning with respect to the elderly while paying attention to theSurrounding enVⅡ'onment to prevent accidents.
ThⅡ'd, we pTopose methods to estimate a peTson's awareness of the surfoundinσ
enVⅡ'onment.1n the case of person、f0110wing tobots, they cannot obsefve features

Which dⅡ'ectly reaect the P田'son's awaTeness (e.曾., head のientation and gaze). we,thus, propose methods to estilnate a pefson's awaTeness solely froln the person'S
trajectoTy. As a proof、ofconcept, we pfopose a model to estin)ate a person'S
awaTeness of an obstacle in a Cのlid0τ. Then, we extend the n)odelso that 北 Can

handle arbitraTy obstades and envifonmental stfuctures with a deep
Convolutional network.

Fina11y, we present a proposal for the systeln design of an attendant Tobot. Therobot reliably foHows a specific taτ牙et P田'son W北h the proposed pa,son
identification methods, and its bel〕avioT is designed based on the assesslnent ofaccident rlsks with awareness estimation foT safe and con〕fortable attendance.1t

Would be a step towards a socia11y acceptable robotic cm・e今ivinぴ System.