ςʔϚύʔΫʹ͓͚Δࣗ཯Ҋ಺ϩϘοτͷ։ൃ˓দຊɹߞฏʢ‫۝‬भେֶʣɼࠓҪɹকਓʢ‫۝‬भେֶʣɼࢁాɹ߂޾ʢ‫۝‬भେֶʣɼՏଜɹߊ޺ʢ‫۝‬भେֶʣɼ૔௺ɹ྄ʢ‫۝‬भେֶʣDevelopment of Autonomous Tour-Guide Robotin a Theme Park˓ Kohei MATSUMOTO (Kyushu University), Masato IMAI (Kyushu University),

Hiroyuki YAMADA (Kyushu University), Akihiro KAWAMURA (Kyushu University),
and Ryo KURAZUME (Kyushu University)
Abstract : In this paper, we describe an autonomous tour-guide robot system in wide area outdoor environments. In thissystem, a tour-guide robot is equipped with a depth camera, a 2D laser distance sensor, and a QZSS receiver for obstacle
detection and positioning. In addition, several sensor systems are installed in the environment for estimating the position ofthe robot. The guide application is also implemented on the Android terminal installed in the robot. We report on the detailsof the developed system and the demonstration experiment.

1.

ॹ‫ݴ‬ۙ೥ɼগࢠߴྸԽ΍஍ํͷաૄԽͳͲͷࣾձ໰୊ʹର͠
ͯɼIoTɼϩϘοτɼਓ޻஌ೳɼϏοάσʔλ౳ͷ৽ͨͳٕज़ΛಋೖʹΑΓɼͦΕΒͷղܾΛ໨ࢦͨ͠ Society 5.0 ͕ఏএ͞Ε͍ͯΔɽಛʹɼϩϘςΟΫε෼໺ʹ͓͍ͯ͸ɼࣗ཯ϩϘοτʹΑΔӡൖɼ‫ܯ‬උɼհ‫Ͳͳޢ‬ͷλεΫͷ୅ସ΍֦ு͕‫ظ‬଴͞Ε͍ͯΔɽ͜ͷΑ͏ͳࣗ཯αʔϏεϩϘοτ͕ਓؒͱ‫ڞ‬ଘ͠ద੾͔ͭ҆શʹಈ࡞͢ΔͨΊʹ͸େྔ͔ͭਖ਼֬ͳ‫ڥ؀‬σʔλ͕ඞཁෆՄܽͰ͋Δɽ͔͠͠ɼ‫಺ڥ؀‬ͷ

Fig. 2: γεςϜͷ֎‫؍‬େྔͳ৘ใͷऔಘ͠ɼ༷ʑͳαʔϏελεΫͷ࣮ߦΛҰ୆ͷϩϘοτͷΈͰߦ͏ͷ͸ࠔ೉Ͱ͋Δɽͦ͜Ͱզʑ͸ɼ‫ڥ؀‬ଆʹଟ਺ͷηϯαΛ෼ࢄ഑ஔ͠ɼͦҊ಺ϩϘοτͷ։ൃΛߦ͍ͬͯΔɽຊߘͰ͸ɼ։ൃͨ͠γͷηϯα͕ूΊͨ‫಺ڥ؀‬ͷ༷ʑͳ৘ใΛ༻͍ͯɼϩϘοτεςϜʹ͍ͭͯड़΂ͨ‫ޙ‬ɼ͜Ε·ͰʹߦͬͨҊ಺࣮‫ͭʹݧ‬ͷೝ஌ೳྗͷ֦ுΛߦ͏‫ڥ؀‬৘ใߏ଄Խʹ͍ͭͯ‫ڀݚ‬Λ͍ͯใࠂ͢Δɽ

ߦ͖ͬͯͨ [1] [2]ɽ‫ڥ؀‬৘ใߏ଄Խ͸ɼෳࡶͳ‫ࣗͰ಺ڥ؀‬཯ϩϘοτ͕ɼ҆શ͔ͭޮ཰తʹ࡞‫ۀ‬Λߦ͏ͨΊʹ͔ܽͤͳ͍΋ͷͰ͋Δɽ

2.

ϋʔυ΢ΣΞߏ੒ຊγεςϜͰ͸ɼϩϘοτϓϥοτϑΥʔϜͱͯ͠ɼ౥৐ՄೳͳҠಈϩϘοτ Loomo Λ༻͍ͨɽ·ͨɼϩϘοτ౥ࡌηϯαͱͯ͠ɼσϓεΧϝϥɼશपϨʔβ‫཭ڑ‬ηϯαɼ͓Αͼ४ఱ௖Ӵ੕ଌҐγεςϜʢQZSSʣड৴‫ػ‬Λ༻͍ɼ‫ڥ؀‬ઃஔηϯαͱͯ͠ɼখ‫ܕ‬ηϯα୺຤ʢP2 -Sen) Λ༻͍ͨɽ։ൃͨ͠ϩϘοτγεςϜͷ֎‫؍‬Λ Fig.2 ʹࣔ͢ɽFig. 1: ‫ڥ؀‬৘ใߏ଄Խͷ֓೦ਤ͜ͷ‫ڥ؀‬৘ใߏ଄Խͷίϯηϓτʹै͍ɼզʑ͸‫ࡏݱ‬ɼ

2.1ࠃ಺ςʔϚύʔΫͱ‫ڞ‬ಉͰɼύʔιφϧϞϏϦςΟϏʔΫϧ (PMV) Loomo Λϕʔεͱͨ͠԰֎޿Ҭ‫͚͓ʹڥ؀‬Δ

LoomoLoomo (Fig.3) (Segway Inc.) ͸౥৐ՄೳͳҠಈϩϘοτͰ͋ΓɼຊγεςϜͷϩϘοτϓϥοτϑΥʔϜͱͯ͠

第19回システムインテグレーション部門講演会（SI2018）（2018年12月13日～15日・大阪）- 2051 -SY0010/18/0000 - 2051 © 2018 SICE༻͍ΔɽLoomo ʹ͸ɼඪ४ͰσϓεΧϝϥ΍ Android ୺຤͕౥ࡌ͞Ε͓ͯΓɼSDK Λ༻͍Δ͜ͱͰɼ͜ΕΒͷηϯα৘ใΛ༻͍ͨɼ༷ʑͳΞϓϦέʔγϣϯ։ൃ͕ՄೳͰ
͋Δɽ

Fig. 6: QZSS Ϟδϡʔϧ

Fig. 3: Loomo

2.2

Fig. 7: ιϑτ΢ΣΞͷߏ੒σϓεΧϝϥϩϘοτ಺ʹ͸σϓεΧϝϥ ReaslSense ZR300 (Intel)(Fig.4) ͕౥ࡌ͞Ε͓ͯΓɼϩϘοτͷલํͷো֐෺Λ‫ݕ‬஌͢ΔͨΊʹ༻͍Δɽ‫ܭ‬ଌՄೳൣғ͸ 0.5m ∼ 3.5m Ͱ͋Δɽ

2.5খ‫ܕ‬ηϯαϙʔϧ P2 -Senզʑ͸͜Ε·Ͱʹɼ‫ݻڥ؀‬ఆηϯαͱͯ͠খ‫ܕ‬ηϯαϙʔϧ P2 -Sen Λ։ൃ͍ͯ͠Δ [6]ɽ͜Ε͸ɼϨʔβϨϯδϑΝΠϯμͱϘʔυ PC Λ಺ଂͨ͠খ‫ܕ‬ηϯα୺຤Ͱ͋Δɽ

2.3શपϨʔβ‫཭ڑ‬ηϯαͳ͓ɼ‫ޙ‬ड़͢Δ࣮‫Ͱݧ‬͸ P2 -Sen ͸༻͍͍ͯͳ͍͕ɼࠓ‫ޙ‬ࠓճ࢖༻ͨ͠શपϨʔβ‫཭ڑ‬ηϯα͸ LDS-01 (ROBO-ςʔϚύʔΫͰͷ࣮‫ͰͲͳݧ‬͸ར༻Λ༧ఆ͍ͯ͠ΔɽTIS) (Fig.5) Ͱ͋ΓɼϩϘοτͷपғ 360 ౓ͷো֐෺Λ‫ݕ‬஌͢ΔͨΊʹ༻͍Δɽ‫ܭ‬ଌՄೳൣғ͸ 0.12m ∼ 3.5m Ͱ͋Δɽ

3.

ιϑτ΢ΣΞߏ੒ιϑτ΢ΣΞ͸େ͖͘෼͚ͯࣗ཯Ҡಈιϑτ΢ΣΞͱҊ಺ΞϓϦέʔγϣϯ͕͋Γɼ͜ͷ͏ͪࣗ཯Ҡಈιϑτ΢ΣΞ͸ɼࣗ‫ݾ‬Ґஔਪఆɼ‫ܦ‬࿏ੜ੒ɼো֐෺‫ݕ‬஌͔Βߏ੒͞ΕΔɽιϑτ΢ΣΞͷߏ੒Λ Fig.7 ʹࣔ͢ɽ

Fig. 4: RealSense ZR300

3.1

Fig. 5: LDS-01ࣗ‫ݾ‬Ґஔਪఆࣗ‫ݾ‬ҐஔਪఆͰ͸ɼQZSS ΍ P2 -Sen ͔Βऔಘͨ͠ϩϘοτͷҐஔɼ͓ΑͼंྠΤϯίʔμ͔Βಘͨ଎౓৘ใΛ֦ுΧϧϚϯϑΟϧλͰ౷߹͍ͯ͠Δɽͳ͓ɼQZSS ͸‫ݱ‬ঢ়Ͱ

2.4४ఱ௖Ӵ੕ଌҐγεςϜ (QZSS)͸ෆ҆ఆͰ͋Γɼ‫ޙ‬ड़͢Δ࣮‫Ͱݧ‬͸ɼ‫ʹڥ؀‬༧Ίઃஔͨ͠४ఱ௖Ӵ੕ଌҐγεςϜ͸ɼ४ఱ௖‫ي‬ಓͷӴ੕͕ओମͱΞΫςΟϒϏʔίϯ΋ซ༻ͯ͠ҐஔಉఆΛߦ͍ͬͯΔ [6]ɽͳͬͯߏ੒͞ΕΔɼ೔ຊͷӴ੕ଌҐγεςϜͰ͋Δɽ४ఱ௖‫ي‬ಓӴ੕Ͱ GPS Ӵ੕Λิ͏͜ͱͰɼ‫ࠩޡ‬վળ΍҆ఆͷͨΊʹඞཁͳɼ8 ‫ػ‬Ҏ্ͷӴ੕ʹΑΔଌҐ͕‫ظ‬଴Ͱ͖Δɽ

3.2ো֐෺‫ݕ‬஌Ͱ͸ɼσϓεΧϝϥ‫ͼٴ‬શपϨʔβ‫཭ڑ‬ηϯ͜ΕʹΑͬͯϚϧνύεͳͲʹΑΔ‫ࠩޡ‬Λܰ‫͖Ͱݮ‬ɼΑΓߴਫ਼౓Ͱ҆ఆͨ͠Ӵ੕ଌҐ͕ՄೳͰ͋Δɽো֐෺‫ݕ‬஌αͰऔಘͨ͠σʔλΛɼ஍ਤ্ͷίετͱͯ͠༻͍Δ͜ͱͰࣗ཯ҠಈγεςϜ΁൓ө͢Δɽ·ͨɼিಥճආͷͨΊʹ

- 2052 -ϩϘοτͷҰఆൣғ಺ʹো֐෺͕͋Δ৔߹͸ͦͷ৔Ͱఀࢭ͢Δɽ

3.3‫ܦ‬࿏ੜ੒‫ܦ‬࿏ੜ੒Ͱ͸ɼॳΊʹμΠΫετϥ๏Λ༻͍ͯ໨ඪҐஔ·Ͱͷ࠷୹ύεʢάϩʔόϧύεʣΛੜ੒͢Δɽͦͷ‫ޙ‬ɼ࣮ࡍʹϩϘοτ͕૸ߦ͢Δࡍʹ͸ɼDynamic Window

Approach (DWA) [5] Λ༻͍ͯɼো֐෺Λආ͚ͳ͕ΒҠಈ͢Δ࠷దύεʢϩʔΧϧύεʣΛੜ੒͢Δɽ

3.4Ҋ಺ΞϓϦέʔγϣϯҊ಺ΞϓϦέʔγϣϯ͸ Loomo ಺ͷ Android ୺຤ʹ࣮૷͓ͯ͠ΓɼϢʔβͷϦΫΤετʹԠͯࣗ͡཯Ҡಈιϑτ΢ΣΞʹ໨త஍৘ใΛૹ৴͠ɼ໨త஍ʹ౸ୡ࣍ୈɼԻ੠ʹ
ΑΔࢪઃͷઆ໌Λߦ͏ɽ

4.

࣮‫ݧ‬‫۝‬भେֶҏ౎ΩϟϯύεͷҰ۠ؒʹ͓͍ͯɼҊ಺࣮‫ݧ‬Λ
1 ∼ ⃝5 ·ͰͷϙΠϯ
ߦͬͨɽFig.8 ʹ‫ڥ؀‬ͷ஍ਤΛࣔ͢ɽ⃝τΛҠಈ͠ɼ֤ϙΠϯτͰࢪઃͷઆ໌Λߦ͏ɼ֤ϙΠϯτ

Fig. 8: ࣮‫ڥ؀ݧ‬1 ɿҊ಺։࢝஍఺ɼ⃝2 ɿཧ‫ܥ‬ਤॻ‫ؗ‬ɼ⃝
3 ɿϕ͸ͦΕͧΕɼ⃝
4 ɿ΢Τετ 2 ߸‫ؗ‬ɼ⃝
5 ɿҊ಺ऴྃ
ϯνɾ‫ܜٳ‬εϖʔεɼ⃝஍఺ͱͯ͠Ҋ಺Λߦ͏ɽҊ಺࣮‫ݧ‬ͷ༷ࢠΛ Fig.9 ʹࣔ͢ɽ5.

݁‫ݴ‬ຊߘͰ͸ɼ͜Ε·Ͱʹ։ൃͨࣗ͠཯Ҋ಺ϩϘοτγεςϜͷɼϋʔυ΢ΣΞߏ੒ɼιϑτ΢ΣΞߏ੒ͱɼҊ಺࣮‫ݧ‬ʹ͍ͭͯड़΂ͨɽ࣮‫Ͱݧ‬͸։ൃͨ͠ϩϘοτγεςϜ͕ɼ໨త஍·ͰҠಈ͠ɼͦΕͧΕͷ৔ॴͰࢪઃ౳ʹ͍ͭͯͷઆ໌Λߦ͏͜ͱ͕ՄೳͰ͋Δ͜ͱΛ֬ೝͨ͠ɽࠓ‫ޙ‬ɼςʔϚύʔΫͰͷ࣮‫ݧ‬Λߦ͏༧ఆͰ͋Δɽ

Fig. 9: Ҋ಺࣮‫ݧ‬- 2053 -ࢀߟจ‫ݙ‬[1] Ryo Kurazume, Yoonseok Pyo, Kazuto Nakashima,Tokuo Tsuji, and Akihiro Kawamura, “Feasibility
study of IoRT platform “Big Sensor Box”,”IEEEInternational Conference on Robotics and Automation (ICRA2017), pp.3664-3671, 2017.
[2] Yoonseok Pyo, Kouhei Nakashima, Shunya Kuwahata, Ryo Kurazume, Tokuo Tsuji, Ken’ichi Morooka, and Tsutomu Hasegawa, “Service Robot
System with an Informationally Structured Environment,”Robotics and Autonomous Systems,
Vol.74, No.Part A, pp.148-165, 2015.
[3] Rudolph Triebel et al., “SPENCER: A sociallyaware service robot for passenger guidance andhelp in busy airports,” Springer Tracts in Advanced
Robotics, 113, pp.607-622, 2016 .
[4] Thomas Moore, and Daniel Stouch, “A GeneralizedExtended Kalman Filter Implementation for theRobot Operating System,” Intelligent Autonomous
Systems 13, pp.335348, 2016.
[5] Fox Dieter, Burgard Wolfram, and Thrun Sebastian, “The dynamic window approach to collision
avoidance,” IEEE Robotics and Automation Magazine, pp.2333, 1997.
[6] ࠓҪ কਓ, ฏদ ஌थ, ࢁా ߂޾, Տଜ ߊ޺, ૔௺ ྄,“ύʔιφϧϞϏϦςΟͷͨΊͷ৘ใߏ଄Խ‫ڥ؀‬ͷߏஙͱςʔϚύʔΫͰͷ༠ಋ࣮‫ݧ‬,” ೔ຊ‫ػ‬ցֶձϩϘςΟΫεϝΧτϩχΫεߨԋձ 2018, pp.2A2-D07,2018.6.2-5- 2054 -