ᚑくᄢቇℂᎿቇ⎇ⓥႎ๔
J. Fac. Sci. Tech., Seikei Univ.
Vol.46 No.2 (2009) pp.23-29⋥ㅴォ࿁⿛ⴕဳ᝹㒰ࡠࡏ࠶࠻ߩ᝹ᒁ૞ᬺല₸ߩ੍᷹ዊᣇ ඳਯ 㧘㠽Ძ ᣿ 㧞㧘ᳯᴛ ᣽♿ 㧟㧘㥱⮮ 㓶᮸ 㧠㧘⑔ᧄ ⵨੺ 㧠Forecasting Task Efficiency of an “Air Hockey” Type Sweeping Algorithm
for Robot Cleaners
Hiroyuki OGATA㧖1, Akira TORIGE㧖2, Akinori EZAWA㧖3, Yuki SAITO㧖4, Yusuke FUKUMOTO㧖4ABSTRACT㧦 This paper addresses to sweeping algorithms that mainly utilize sensory information, andare often used in domestic cleaning robots. In general, the algorithms adopted in such robots seem to benot very effective. To develop a more effective algorithm, a technique that can objectively compare theefficiencies is required. However, the efficiencies of algorithms may vary with environmental conditions.
Consequently, we consider estimating them by evaluating under some conditions, and then deduce
efficiencies in other conditions from them. In this paper, we investigate a method to forecast theefficiency of a sweeping algorithm given the environmental conditions like area map or sensory
information in the initial stage of task.
Keywords㧦sweeping task, motion planning, robot cleaner, coverage algorithm, sensor-based method
㧔Received August 28, 2009㧕 ᐥ㕙᝹㒰૞ᬺߦ↪޿ࠄࠇࠆ㧘޿ࠊࠁࠆ᝹㒰ࡠࡏ࠶࠻ߦ㧝㧚ߪߓ߼ߦߪᬺോ↪ߣኅᐸ↪ߩ㧞ߟߩ↪ㅜ߇޽ࠆ߇㧘ߘࠇࠄߩ㑆ߢ ࡠࡏ࠶࠻߇૞ᬺࠍⴕ߁਄ߢ㧘േ૞ߩ↢ᚑߪ㊀ⷐߢ޽ࠆ‫ޕ‬ⷐ᳞ߐࠇࠆࠬࡍ࠶ࠢߪ⇣ߥࠆ㧔⴫㧝㧕‫ޕ‬ᧄ⎇ⓥߢߪߘߩਛߢ߽᝹ᒁേ૞㧘ߣࠅࠊߌᐥ㕙᝹㒰૞ᬺ
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ႎࠍၮߦ⚻〝ࠍ᳿ቯߒߡ޿ߊ߽ߩߢ޽ࠆ‫ߪߢߎߎޕ‬㧘࠮ߦᲧߴߡዉ౉ࠦࠬ࠻߿▤ℂࠦࠬ࠻߇ഀ㜞ߢ߽⸵ኈߐࠇࠆࡦࠨᖱႎߦߪ㧘⚻ㆊᤨ㑆ߥߤ㧘ౝㇱ࠮ࡦࠨ߆ࠄᓧࠄࠇࠆߚ߼㧘㜞ᯏ⢻ߥ࠮ࡦࠨࠍ↪޿ࠆߎߣ߇ߢ߈ࠆ‫ⷰߩߎޕ‬ὐᖱႎ߿ጁᱧᖱႎ߽฽߻ߣߔࠆ‫ޕ‬㧦ࠛ࡟ࠢ࠻ࡠࡔࠞ࠾ࠢࠬቇ⑼ᢎ᝼ (ogata@st.seikei.ac.jp)*2㧦ࠛ࡟ࠢ࠻ࡠࡔࠞ࠾ࠢࠬቇ⑼ಎᢎ᝼ (torige@st.seikei.ac.jp)*3㧦Ꮏቇ⎇ⓥ⑼ᯏ᪾Ꮏቇኾ᡹ୃੌ↢㧔⃻ (ᩣ)ᣣ┙ᑪᯏ㧕
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߆ࠄ㧘ᬺോ↪ㅜߦߪ੐೨⸘↹㊀ⷞဳࠕ࡞ࠧ࡝࠭ࡓ߇ㆡߒ

*1ߡ޿ࠆߣ޿߃ࠆ‫ࠄߥߗߥޕ‬㧘੐೨⸘↹㊀ⷞဳࠕ࡞ࠧ࡝࠭ࡓߢߪ㧘⸘↹Ბ㓏ߢ૞ᬺ㗔ၞߩᒻ⁁ᖱႎ߇ᔅⷐߢ޽ࠅ㧘㧙㧙૞ᬺታⴕᲑ㓏ߢߪ૞ᬺ㗔ၞ߇㕒⊛ߥᣇ߇߁߹ߊ૞ᬺ߇ታ߇ᔅⷐએ਄ߦⴕࠊࠇߡ޿ࠆㇱಽߣ߶ߣࠎߤⴕࠊࠇߡ޿ߥⴕߢ߈ࠆ߆ࠄߢ޽ࠆ‫ߚ߹ޕ‬㧘GPS ╬ߩᲧセ⊛㜞ଔߥ࠮ࡦ޿ㇱಽ߇ሽ࿷ߒߡ޿ࠆ᭽ሶ߇⷗ࠄࠇࠆ‫ޕ‬ࠨࠍ૶↪ߒ㧘⥄ಽߩ⛘ኻ૏⟎ߩ㜞♖ᐲߥᛠី߇น⢻ߢ޽ ᧄ⎇ⓥߩ⋡ᮡߪኅᐸ↪᝹㒰ࡠࡏ࠶࠻ߦਥߦ↪޿ࠄࠇࠆࠆ 21)‫ޕ‬૞ᬺ㗔ၞߩ㕙Ⓧߪ৻⥸ߦࡠࡏ࠶࠻ߩᄢ߈ߐߣᲧセ࠮ࡦࠨᖱႎ㊀ⷞဳࠕ࡞ࠧ࡝࠭ࡓࠍಽᨆߒ㧘ࠃࠅല₸⊛ߥߒߡᄢ߈ߊ㧘᝹ᒁ૞ᬺല₸ࠍᦨᄢ㒢ߦ㜞߼ࠆᔅⷐ߇޽ࠆ‫ޕ‬߽ߩࠍ⠨᩺ߔࠆߎߣߦ޽ࠆ‫ޕ‬⠨᩺ߒߚࠕ࡞ࠧ࡝࠭ࡓ߇ല ৻ᣇ㧘ኅᐸ↪ㅜߢߪ㧘ᠲ૞߇◲නߢ޽ࠆߎߣ߇ⷐ᳞ߐ₸⊛߆್ᢿߔࠆߦߪ㧘ઁߩࠕ࡞ࠧ࡝࠭ࡓߣᲧセߒߡ⹏ଔࠇ㧘⾼౉⠪߇૞ᬺ㗔ၞߩᒻ⁁ᖱႎࠍ౉ജߔࠆߥߤߩᠲ૞ߢ߈ࠆߎߣ߇೨ឭߣߥࠆ‫ޕ‬ߒ߆ߒ㧘૞ᬺ㗔ၞߩᒻ⁁ߪ᭽‫ޘ‬ߪㆱߌࠆᔅⷐ߇޽ࠆ‫ࠅ߹ߟޕ‬㧘ࡠࡏ࠶࠻ߦߣߞߡߪ૞ᬺߢ޽ࠅ㧘޽ࠆ᧦ઙਅߢߩ⹏ଔ⚿ᨐ߇ઁߩ᧦ઙਅߢ߽ᅷᒰⅣႺߪᧂ⍮ߢ޽ࠆ‫ߚ߹ޕ‬㧘ᚻ㗃ߥ⽼ᄁଔᩰߦߒ㧘ࡔࡦ࠹ߣߪ㒢ࠄߥ޿‫ޕ‬ߘߎߢ㧘޿ߊߟ߆ߩ᧦ઙਅߢ⹏ଔࠍⴕ޿㧘࠽ࡦ߽ࠬᦨዊ㒢ߣߔࠆߚ߼ߦߪ㧘ߢ߈ࠆߛߌන⚐ߢૐଔߘࠇࠄߩ⚿ᨐ߆ࠄઁߩ᭽‫᧦ߥޘ‬ઙਅߢߩ૞ᬺߩല₸ᕈࠍᩰߩ࠮ࡦࠨࠍᦨዊ㒢ขࠅઃߌࠆߛߌߢᷣ߹ߔᔅⷐ߇޽ࠅ㧘੍᷹ߢ߈ࠇ߫㧘ࠃࠅᱜ⏕ߥ⹏ଔࠍⴕ߃ࠆߣ⠨߃ࠄࠇࠆ‫ޕ‬ᬺോ↪ߩࠃ߁ߦࡠࡏ࠶࠻ߩ⛘ኻ૏⟎ࠍ㜞♖ᐲߢᓧࠆߎߣߎߩ⠨߃ߦၮߠ߈㧘ᧄ⺰ᢥߢߪኅᐸ↪᝹㒰ࡠࡏ࠶࠻ߦ߅ߪ೨ឭߦߢ߈ߥ޿‫ߚ߹ޕ‬㧘ኅᐸߩ᝹㒰ⅣႺߢߪ࠹࡯ࡉ࡞޿ߡઍ⴫⊛ߥ࠮ࡦࠨᖱႎ㊀ⷞဳࠕ࡞ࠧ࡝࠭ࡓࠍขࠅ਄ߍ㧘߿᫹ሶߩࠃ߁ߦ㧘⒖േน⢻ߥ㓚ኂ‛߇ሽ࿷ߒ㧘૞ᬺⅣႺ૞ᬺല₸ߩ੍᷹น⢻ᕈߦߟ޿ߡᬌ⸛ߔࠆ‫ޕ‬߇৻ቯߣ߽㕒⊛ߣ߽઒ቯߢ߈ߥ޿‫ޕ‬૞ᬺ㐿ᆎ૏⟎߇ㅢᏱਇቯߢ޽ࠅ㧘૞ᬺਛߦ૶↪⠪ߦࠃߞߡࡠࡏ࠶࠻߇ะ߈ࠍᄌ߃ࠄࠇߚࠅ೎ߩ႐ᚲߦ⒖േߐߖࠄࠇߚࠅߔࠆน⢻ᕈ߽⠨ᘦߔࠆᔅⷐ߇޽ࠆ‫ߚ߹ޕ‬㧘૞ᬺ㗔ၞߩ㕙Ⓧߪ৻⥸ߦዊߐ޿‫ߥ߁ࠃߩߎޕ‬૞ᬺ᧦ઙߢߪ੐೨⸘↹㊀ⷞဳࠕ࡞ࠧ࡝࠭ࡓߪ૶↪ߢ߈ߕ㧘࠮ࡦࠨᖱႎ㊀ⷞဳࠕ࡞ࠧ࡝࠭ࡓߩᣇ߇ㆡߒߡ޿ࠆߣ޿߃ࠆ‫ޕ‬ ૞ᬺⅣႺ߇ࡠࡏ࠶࠻ߦߣߞߡᧂ⍮ߣ޿߁᧦ઙߦኻಣߔࠆߚ߼ߦ㧘૞ᬺ㗔ၞᒻ⁁ࠍቇ⠌ߒ㧘ߘߩᖱႎߦၮߠ޿ߡ᝹ᒁേ૞ࠍ↢ᚑߔࠆ⹜ߺ߽⷗ࠄࠇࠆ߇ 5) 13) 14)㧘ታ㓙ߦᏒ⽼ߐࠇߡ޿ࠆ᝹㒰ࡠࡏ࠶࠻ߩ߶ߣࠎߤߪ࠮ࡦࠨᖱႎ㊀ⷞဳߦಽ㘃ߐࠇࠆࠕ࡞ࠧ࡝࠭ࡓࠍ૶↪ߒߡ޿ࠆ 7) 18) 19) 20)‫ޕ‬ ੐೨⸘↹㊀ⷞဳߦ㑐ߒߡߪ޿ߊߟ߆ߩല₸⊛ߥࠕ࡞ࠧ࡝࠭ࡓߩឭ᩺߇ߥߐࠇߡ޿ࠆ‫ޕ‬ઍ⴫⊛ߥᣇᴺߪ૞ᬺ㗔ၞ

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Gonzalez ࠄ 4)ߪ૞ᬺ㗔ၞࠍࠣ࡝࠶࠼ಽഀߔࠆᚻᴺࠍណ㧞㧚࠮ࡦࠨᖱႎ㊀ⷞဳ᝹ᒁࠕ࡞ࠧ࡝࠭ࡓߩಽ㘃

ᚻᴺ߇ߣࠄࠇߡ޿ࠆ‫ߚ߹ޕ‬㧘ⶄᢙߩ᝹㒰ࡠࡏ࠶࠻ߦࠃࠆ Ꮢ⽼߹ߚߪ㐿⊒ਛߩኅᐸ↪᝹㒰ࡠࡏ࠶࠻ߦ⷗ࠄࠇࠆ࠮૞ᬺࠍ೨ឭߣߒߚ⎇ⓥ߽޽ࠅ㧘ࠝࡈ࠮࠶࠻✢࡮ࡏࡠࡁࠗࡦࠨᖱႎ㊀ⷞဳ᝹ᒁࠕ࡞ࠧ࡝࠭ࡓߪ㧘න⁛ߢ߽ቢోߥ᝹✢ࠍ↪޿ߡല₸⊛ߥ゠㆏ࠍ↢ᚑߔࠆࠕ࡞ࠧ࡝࠭ࡓ߇ୖᨋᒁ૞ᬺ߇น⢻ߥၮᧄࠕ࡞ࠧ࡝࠭ࡓߣ㧘න⁛ߢߪቢోߥ᝹ࠄ 12)߆ࠄឭ᩺ߐࠇߡ޿ࠆ‫ޕ‬ᒁ૞ᬺࠍⴕ߃ߥ޿߇ၮᧄࠕ࡞ࠧ࡝࠭ࡓߣ૬↪ߔࠆߣല₸ ߘߩ৻ᣇߢ㧘࠮ࡦࠨᖱႎ㊀ⷞဳߩࠕ࡞ࠧ࡝࠭ࡓߦ㑐ߒࠍะ਄น⢻ߥઃടࠕ࡞ࠧ࡝࠭ࡓߣࠍ⚵ߺวࠊߖߚ߽ߩ߇ߡߪᏒ⽼ߩኅᐸ↪᝹㒰ࡠࡏ࠶࠻ߦ᭽‫߇ߩ߽ߩࡊࠗ࠲ߥޘ‬ᄙ޿‫ޕ‬↪ߒߡ޿ࠆ‫ޕ‬Wong ࠄ 15)16)ߩ⎇ⓥߢߪࠬ࡜ࠗࠬಽഀߔࠆታⵝߐࠇߡ޿ࠆߦ߽߆߆ࠊࠄߕ㧘ቇⴚ⊛ߦಽᨆࠍⴕߞߚၮᧄࠕ࡞ࠧ࡝࠭ࡓߦߪᰴߩ࠲ࠗࡊ߇⷗ࠄࠇࠆ‫ޕ‬߽ߩߪ⷗ࠄࠇߥ޿‫ޕ‬⋥ㅴォ࿁ဳ㧦⋥✢⊛ߦ⒖േߒ㧘ო߿㓚ኂ‛ߦⴣ⓭ߔࠆ ⃻ሽߩ࠮ࡦࠨᖱႎ㊀ⷞဳࠕ࡞ࠧ࡝࠭ࡓߪᔅߕߒ߽ኅᐸߣᣇะォ឵ࠍⴕ߁ߎߣࠍ➅ࠅ㄰ߔ߽ߩ㧔࿑㧞(a)㧕
‫ޕ‬↪ㅜߦᦨㆡൻߐࠇߡ޿ࠆߣߪ⸒߃ߥ޿‫߫߃଀ޕ‬㧘ኅౕߥᓔᓳ (direction parallel) ဳ㧦⋥✢⊛ߦ⒖േߒ㧘ო߿ߤߩ㓚ኂ‛ߩሽ࿷ߔࠆⶄ㔀ߥⅣႺߢߪ᝹㒰ࡓ࡜߇⊒↢ߒ㓚ኂ‛ߦⴣ⓭ߔࠆߣ㧘ࡠࡏ࠶࠻ߩ૞ᬺ᦭ല▸࿐ߩ᏷߿ߔ޿‫ޕ‬࿑㧝ߪᓟㅀߩࠪࡒࡘ࡟࡯࠲ߢ࠮ࡦࠨᖱႎ㊀ⷞဳd ߛߌᮮߦ⒖േߒ㧘180qᣇะォ឵ࠍⴕ߁ߎߣࠍ➅ࠅࠕ࡞ࠧ࡝࠭ࡓߩ㧝ߟࠍታⴕߐߖߚ႐วߩ゠〔ߛ߇㧘᝹ᒁ㄰ߔ߽ߩ㧔࿑㧞(b)㧕‫ޕ‬㧙㧙Ⴚ⇇ᐔⴕ(contour parallel)ဳ㧦ߪߓ߼ߦ૞ᬺ㗔ၞߩႺᤨ㑆߹ߚߪო߿㓚ኂ‛ߦⴣ⓭ߔࠆ߹ߢ⿛ⴕߔࠆ߽ߩ⇇ߦᴪߞߡ㧝๟ߒ㧘ߘߩᓟ㧘n ๟⋡ߦߪႺ⇇߆ࠄ d㧔࿑㧞(f)㧕

(n-1/2)ߛߌౝ஥ߦ〒㔌ࠍ଻ߞߡ๟࿁ߔࠆ߽ߩ㧔࿑
㧞(c)㧕‫ޕ‬㧟㧚᝹ᒁ૞ᬺല₸ߩ⹏ଔ᝹ᒁ૞ᬺߩല₸ࠍ⼏⺰ߔࠆߚ߼ߦ㧘ᧄ⺰ᢥߢߪએਅߩ
೨ឭࠍ߅ߊ‫ޕ‬࡮᝹ᒁࠕ࡞ࠧ࡝࠭ࡓߩ஥㕙ߩߺߦ⌕⋡ߒ㧘ࡠࡏ࠶࠻ߩ૞ᬺ᦭ല▸࿐ߩᄢ߈ߐ㧘⿛ⴕࠬࡇ࡯࠼㧘ߏߺߩๆᒁ(a) Air hockey(b) Direction parallelജߩࠃ߁ߥࡂ࡯࠼࠙ࠚࠕ⊛᧦ઙߥߤߪ౒ㅢߣߔࠆ‫ޕ‬࡮ࡠࡏ࠶࠻ߩ૞ᬺ᦭ല▸࿐ߪᐩ㕙ో૕ߣߔࠆ‫ޕ‬࡮૞ᬺ㗔ၞߪ㧘ౝㇱߩߔߴߡߩὐ߇ࠬ࠲࡯࠻࿾ὐ߆ࠄࡠࡏ࠶࠻ߦࠃߞߡ೔㆐น⢻ߥࠃ߁ߦ⸳ቯߐࠇߡ޿ࠆߣߔࠆ‫ߩߘߪ࠻࠶ࡏࡠޕ‬૞ᬺ᦭ല▸࿐ߦᒰ⹥ὐࠍ฽߻ߎߣߦࠃߞߡ೔㆐ߒߚߣߺߥߔ‫߫߃଀ޕ‬㧘౞ᒻߩ(c) Contour parallel(d) Contour following᝹㒰ࡠࡏ࠶࠻ߦኻߒߡߪ㧘㐳ᣇᒻߩㇱደߩ྾㓈ߪ೔㆐ߢ߈ߥ޿ߩߢ૞ᬺ㗔ၞߦ฽߼ߥ޿‫ޕ‬࡮૞ᬺ㗔ၞౝߩછᗧߩὐߦኻߔࠆ᝹㒰૞ᬺߪ㧘ࡠࡏ࠶࠻ߩ૞ᬺ᦭ല▸࿐߇ߘߩὐࠍ㧝࿁ㅢㆊߔࠆߎߣߦࠃߞߡቢੌߔࠆ߽ߩߣߔࠆ‫ޕ‬ ߎߩ೨ឭߢߪ㧘᝹ᒁߩࠝ࡯ࡃ࡯࡜࠶ࡊ߇ዋߥ޿߶ߤ᝹ᒁ૞ᬺല₸߇㜞޿ߣ޿߃ࠆ‫ߡߞ߇ߚߒޕ‬㧘޽ࠆᤨὐ t ߢ(e) Wall following(f) Spiralߩ᝹ᒁ૞ᬺല₸ߪ㧘t ߦ߅ߌࠆᣢ᝹ᒁ㕙Ⓧࠍ૞ᬺ㗔ၞ㕙Ⓧߢഀߞߚ୯ߢ⴫ߖࠆ‫ߩߎޕ‬୯ࠍߎߎߢߪ᝹ᒁ₸ߣ๭߱‫ޕ‬(KI $CUKEOQVKQPRCVVGTPUHQT᝹ᒁ₸ߪᐨ⋚߆ࠄਛ⋚ߦ߆ߌߡߩ᝹ᒁ૞ᬺല₸ࠍᲧセߔ

EQXGTCIGCNIQTKVJOUࠆߩߦߪଢ೑ߛ߇㧘⚳⋚ߦߪ୯߇㘻๺୯ߩ㧝ߦㄭߠ߈㧘Ყセኻ⽎ߣߩ୯ߩᏅ߇ዊߐߊߥࠆᰳὐ߇޽ࠆ‫ߚ߹ޕ‬㧘૞ ⋥✢ォ࿁ဳߪធ⸅࠮ࡦࠨ߇៞タߐࠇߡ޿ࠇ߫ࠃ޿ߩߢ㧘ᬺో૕ߩല₸ࠍᢙ୯⊛ߦᲧセߔࠆߩߦߪㆡߒߡ޿ߥ޿‫ޕ‬Ꮢ⽼ߩኅᐸ↪᝹㒰ࡠࡏ࠶࠻ߦᦨ߽৻⥸⊛ߦ⷗ࠄࠇࠆ‫ޕ‬ᓔߘߩߚ߼㧘ᔅⷐߦᔕߓߡએਅߢ⸘▚ߐࠇࠆ᝹ᒁࡐࠗࡦ࠻ᓳဳߣႺ⇇ᐔⴕဳߪࡑ࠾ࡇࡘ࡟࡯࠲ࠍ૶↪ߒߚႣⵝ╬ߩߣ޿߁୯ࠍ↪޿ࠆ‫ޕ‬૞ᬺߢ߽ߣ߽ߣ↪޿ࠄࠇߡ޿ࠆ߽ߩߢ 12)㧘৻ㇱߩኅᐸ↪

᝹ᒁࡐࠗࡦ࠻ = − log(1 − ᝹ᒁ₸ )᝹㒰ࡠࡏ࠶࠻ 17)ߦ߽⷗ࠄࠇࠆ‫ߚ޿↪ࠍ࠲࡯࡟ࡘࡇ࠾ࡑޕ‬૞ᬺߢߪవ┵ࠍ㜞♖ᐲߢ૏⟎᳿߼ߢ߈ࠆ߇㧘ኅᐸ↪᝹㒰㧠㧚᝹ᒁ૞ᬺല₸ߩ⹏ଔࡠࡏ࠶࠻ߢߪ㧘቟ଔߥ࠮ࡦࠨߢ㧘ᐔⴕߦᓔᓳ⿛ⴕࠍⴕߞߡ޿ࠆ߆㧘߹ߚߪ૞ᬺ㗔ၞߩႺ⇇ߦᐔⴕߦ⿛ⴕߒߡ޿ࠆ ࠮ࡦࠨᖱႎ㊀ⷞဳ᝹ᒁࠕ࡞ࠧ࡝࠭ࡓࠍಽᨆߔࠆߚ߼ߦ߆ࠍᬌ಴ߒߡേ૞ࠍ⵬ᱜߔࠆߣ޿߁࿎㔍ߥ໧㗴ߦኻಣߔ᝹ᒁ૞ᬺࠪࡒࡘ࡟࡯࠲ࠍ૞ᚑߒߚ‫ߦࡦ࡚ࠪ࡯࡟ࡘࡒࠪޕ‬ࠆᔅⷐ߇޽ࠆ‫ޕ‬߅ߌࠆ⸳ቯ᧦ઙࠍએਅߦㅀߴࠆ‫ޕ‬ઃടࠕ࡞ࠧ࡝࠭ࡓߦߪᰴߩ࠲ࠗࡊ߇⷗ࠄࠇࠆ‫ޕ‬ೋᦼოᴪ޿㧝๟ဳ㧦᝹ᒁ૞ᬺ㐿ᆎᤨߦ૞ᬺ㗔ၞߩᄖ๟㧚 ࡠࡏ࠶࠻Ꮢ⽼ߩኅᐸ↪᝹㒰ࡠࡏ࠶࠻㧔iRobot ␠ Roomba original㧕ࠍ㧝๟ߔࠆ߽ߩ‫ޕ‬૞ᬺ㗔ၞߦ㑐ߔࠆᖱႎࠍขᓧߒߚࠍෳ⠨ߦ㧘એਅߩࠃ߁ߦ⸳ቯߒߚ‫ޕ‬ࠅ㧘ߏߺߩḳࠅ߇ߜߥ๟ㄝㇱࠍవⴕ⊛ߦ᝹ᒁߒߚࠅ࡮૞ᬺ᦭ല▸࿐㧦⋥ᓘ 35 cm ߩ౞ౝߔࠆ⋡⊛ߦⴕࠊࠇࠆߎߣ߇ᄙ޿㧔࿑㧞(d)㧕‫ޕ‬࡮⿛ⴕㅦᐲ㧦32 cm/sოᴪ޿ဳ㧦ო߿㓚ኂ‛ߦⴣ⓭ߒߚࠄ㧘ߘࠇߦᴪߞߡ৻࡮࿁ォㅦᐲ㧦90 deg/sቯᤨ㑆⿛ⴕߔࠆ߽ߩ㧔࿑㧞(e)㧕‫ޕ‬ⲷᣓဳ㧦ࠕ࡞ࠠࡔ࠺ࠬⲷᣓߩ゠〔ࠍឬ߈ߥ߇ࠄ㧘৻ቯ ߹ߚ㧘⋥ㅴォ࿁ဳࠕ࡞ࠧ࡝࠭ࡓࠍታ⃻ߔࠆߚ߼ߦᧄ㧙㧙ኤߢ߈ࠆ‫ࠍࡉ࡯ࠞߩߎߪߢߎߎޕ‬ᐔဋ᝹ᒁᦛ✢ߣ๭߱‫ޕ‬૕೨ㇱߦធ⸅ᗵ⍮࠮ࡦࠨࠍ៞タߒߡ޿ࠆ߽ߩߣߒ㧘ო߿㓚ኂ‛ߣធ⸅ߔࠆߣ࡜ࡦ࠳ࡓߦᣇะォ឵ࠍⴕ߁߽ߩߣߔࠆ‫ޕ‬㧚 ૞ᬺ㗔ၞ ࡠࡏ࠶࠻߇೔㆐น⢻ߥㇱಽߩߺ߆ࠄ᭴ᚑߐࠇࠆ૞ᬺ㗔ၞߩ࠺࡯࠲ࠍታ㛎⠪߇ᚻ૞ᬺߢ૞ᚑߔࠆߩߪ࿎㔍ߢ޽ࠆ‫ޕ‬ߘߩߚ߼㧘ᧄࠪࡒࡘ࡟࡯࠲ߢߪታ㛎⠪߇᝹ᒁ૞ᬺߩኻ⽎ߣߥࠆㇱደߩᒻ⁁࠺࡯࠲ࠍ૞ᚑߒ㧘ߘߩᓟ㧘⸘▚ᯏߢߘ
㧔C㧕4GEVCPING

㧔D㧕.UJCRGF

㧔E㧕6UJCRGF

㧔F㧕7UJCRGF

㧔G㧕)QWTFUJCRGF

㧔H㧕5VCKTNKMG

ߩㇱደߦ߅ߌࠆ૞ᬺ㗔ၞࠍ᳞߼ࠆᒻࠍߣࠆ‫ޕ‬ ਇേ↥ደ߿ࡕ࠺࡞࡞࡯ࡓߢᚒ߇࿖ߩ࡝ࡆࡦࠣ࡞࡯ࡓߩ

㑆ขࠅࠍ⺞ᩏߒߚ⚿ᨐ㧘ㇱደߩ㕙Ⓧߪ 186000 cm2㧔⚂

12 ⇥㧕ߦ⛔৻ߔࠆߎߣߦߒߚ‫߅ߥޕ‬㧘ㇱደ㕙Ⓧࠍ৻ቯߦߒߡ߽㧘ㇱደᒻ⁁ߦࠃࠅ૞ᬺ㗔ၞ㕙Ⓧߦߪ⧯ᐓߩ㆑޿߇
↢ߓࠆ‫ޕ‬ ૞ᬺኻ⽎ߣߥࠆㇱደߩ଀ߣ㧘ߘߎߢ᳞߼ࠄࠇߚ૞ᬺ㗔ၞࠍ࿑㧟ߦ␜ߔ‫ޕ‬

obstacletask area(KI 6JGVCUMCTGCKPCTQQO UJCFGFCTGC (KI 5QOGOCLQTV[RGUQHNKXKPITQQOU㧡㧚⋥ㅴォ࿁ဳࠕ࡞ࠧ࡝࠭ࡓߩಽᨆ㧚 ࡠࡏ࠶࠻ߩೋᦼ⁁ᘒߣ᝹ᒁ₸ ࠪࡒࡘ࡟࡯࠲ࠍ↪޿ߡ㧘⋥ㅴォ࿁ဳࠕ࡞ࠧ࡝࠭ࡓߩၮ ᝹ᒁ₸߇ࡠࡏ࠶࠻ߩೋᦼ⁁ᘒߦଐሽߔࠆ߆⏕߆߼ࠆታᧄ⊛ߥᕈ⾰ࠍ⺞ߴߚ‫ޕ‬㛎ࠍⴕߞߚ‫ޕ‬࿑㧠(d)ߩࠦߩሼဳߩㇱደߦ߅޿ߡ㧘ೋᦼ⁁㧚 ᝹ᒁ₸ߩᄌൻᦛ✢ࠍࡊࡠ࠶࠻ߒߚ⚿ᨐࠍ࿑㧡ߦ␜ߔ‫ߪߢ࠻࠶ࡠࡊޕ‬㧘 ࡝ࡆࡦࠣ࡞࡯ࡓߣߒߡࠃߊ⷗ࠄࠇࠆ㧢⒳㘃ߩㇱደᒻ⁁㧔࿑㧠㧕ߦ߅޿ߡ㧘૞ᬺ㐿ᆎᓟ 40 ಽ߹ߢߩ᝹ᒁ₸ߩᄌ❑ゲߦ᝹ᒁࡐࠗࡦ࠻ࠍߣߞߚ႐วߢ߽㧘ᐔဋ᝹ᒁᦛ✢ߪൻࠍⷰኤߒߚ‫ޕ‬40 ಽߣ޿߁ᤨ㑆ߪࡕ࠺࡞ߦߒߚᏒ⽼᝹㒰߶ߣࠎߤ㊀ߥߞߡ߅ࠅ㧘ೋᦼ⁁ᘒଐሽᕈ߇⷗ࠄࠇߥ߆ߞߚ‫ޕ‬ࡠࡏ࠶࠻߇ 12 ⇥ߩㇱደࠍ᝹㒰ߔࠆ႐วߩ⸳ቯᤨ㑆߆ࠄ ৻⥸ߦኅᐸߢߪ㧘ల㔚࠼࠶ࠢࠍ↪޿ߥ޿࠲ࠗࡊߩ᝹㒰ᘒࠍ 50 ▎ᚲ⸳ቯߒ㧘ฦ‫ ߡ޿ߟߦޘ‬100 ࿁ಽߩᐔဋ᝹ᒁ

ࡠࡏ࠶࠻ߩೋᦼ⁁ᘒߪਇቯߛ߇㧘ߎߩ⚿ᨐߪ㧘᝹ᒁല₸᳿ቯߒߚ‫ޕ‬ߩ⹏ଔߦߪߘߩⷐ⚛ࠍ⠨ᘦߒߥߊߡ߽ࠃ޿ߎߣࠍ␜ߔ߽ ᝹ᒁ₸ߪᤨ㑆ߦߟࠇߡන⺞ߦჇടߔࠆ߇㧘᝹ᒁߩࠝ࡯ߩߢ޽ࠆ‫ޕ‬ࡃ࡯࡜࠶ࡊ߇ᓇ㗀ߒߡ㧘Ṗࠄ߆ߦߪᄌൻߒߥ޿‫ߚ߹ޕ‬㧘એᓟߩࠪࡒࡘ࡟࡯࡚ࠪࡦߢߪೋᦼ⁁ᘒߪ૞ᬺ㗔ၞౝߢ࡜ࡠࡏ࠶࠻ߩೋᦼ⁁ᘒ㧔૏⟎࡮ᆫ൓㧕ࠍ৻ቯߦ⸳ቯߒߡ߽㧘ࡦ࠳ࡓߦ⸳ቯߔࠆ‫ޕ‬⋥ㅴォ࿁ࠕ࡞ࠧ࡝࠭ࡓߦߪ࡜ࡦ࠳ࡓߥⷐ⚛߇޽ࠆߚ߼㧘੕޿ߦหߓࠃ߁ߦߪᄌൻߒߥ޿‫ߒ߆ߒޕ‬㧘ᄙᢙ࿁ߩᐔဋ㧚 ㇱደᒻ⁁ߣ᝹ᒁ₸ࠍߣࠆߣ㧘Ṗࠄ߆ߥࠞ࡯ࡉߣߥࠅ᝹ᒁ₸ߩᄌൻ௑ะ߇ⷰ ᰴߦ㧘᝹ᒁ₸߇㧘ㇱደ㕙Ⓧ৻ቯߩ᧦ઙਅߢ㧘ߘߩᒻ⁁㧙㧙႐วߩㇱደ㕙Ⓧߪ㧘⚂ 12 ⇥ߩ 185856 cm2 ߣߥࠆ‫ޕ‬ߦଐሽߔࠆ߆⏕߆߼ࠆታ㛎ࠍⴕߞߚ‫ޕ‬࿑㧠ߩ㧢ㇱደߦᣂߚߦ㧡ߟߩㇱደᒻ⁁ࠍㅊടߒߡ㧘ߘࠇࠄߩ 11 ㇱደߦߟ޿ฦㇱደ߆ࠄ᛽಴ߒߚ․ᓽ㊂ߪᰴߩ 11 ⒳㘃ߢ޽ࠆ‫ޕ‬

ߡ 100 ࿁ಽߩᐔဋ᝹ᒁᦛ✢ࠍࡊࡠ࠶࠻ߒߚ⚿ᨐࠍ࿑㧢ߦ࡮ᦨᄢౝធ㐳ᣇᒻ㧦ㇱደߦౝធߔࠆᦨᄢߩ㐳ᣇᒻࠍ᭴␜ߔ‫ޕ‬ᚑߔࠆ࠮࡞ᢙ‫ߩ࡞࠮ޕ‬㓸ਛᐲࠍ⴫ߔߣߺߥߖࠆ‫ޕ‬ ࡊࡠ࠶࠻ߢߪᐔဋ᝹ᒁᦛ✢ߪ㊀ߥߞߡ޿ࠆߣߪ⸒߃ߕ㧘࡮㓚ኂ‛ᢙ㧦㒰෰ߐࠇߚ࠮࡞߇ⓨ㑆ౝߢᒻᚑߔࠆ㗔ၞᢙ‫ޕ‬ㇱደᒻ⁁ߩⶄ㔀ᐲࠍ⴫ߔߣߺߥߖࠆ‫ޕ‬᝹ᒁ₸ߪㇱደᒻ⁁ߦଐሽߔࠆ⚿ᨐߣߥߞߡ޿ࠆ‫ޕ‬
2.5࡮ఝⷺᢙ㧦ㇱደࠍ᭴ᚑߔࠆㄝߩ㑆ߩఝⷺߩᢙ‫߽ࠇߎޕ‬ㇱደᒻ⁁ߩⶄ㔀ᐲࠍ⴫ߔߣߺߥߖࠆ‫ޕ‬

2sweep point࡮࠴ࡖࡀ࡞ᢙ㧔㧟⒳㘃㧕
㧦ㇱደࠍಲᄙⷺᒻߦಽ⸃ߒߚߣ
1.5߈㧘㓞ធߔࠆಲᄙⷺᒻ㑆ߩㄝߩ㐳ߐ߇࠮࡞㧝ㄝಽ㧘
2 ㄝಽ㧘㧞ㄝಽߣߥࠆ߽ߩߩ୘ᢙ‫ޕ‬㧞ㄝಽߣߥࠆ߽

1ߩߩ୘ᢙ߇ᄙߌࠇ߫㧘ࡠࡏ࠶࠻ߪ࠴ࡖࡀ࡞ࠍ⿧߃ߡ

0.5

ߩ⒖േࠍᲧセ⊛ኈᤃߦⴕ߃ࠆߣ⠨߃ࠄࠇࠆ‫৻ޕ‬ᣇ㧘㧝ㄝಽߣߥࠆ߽ߩߩ୘ᢙ߇ᄙߌࠇ߫⒖േ߇Ყセ⊛࿎

0010

2030

㔍ߣ⠨߃ࠄࠇࠆ‫ޕ‬40࡮࠮࡞㓞ធࡄ࠲࡯ࡦ㧔㧡⒳㘃㧕
㧦㓞ធߔࠆ࠮࡞ߩࡄ࠲࡯

time (min.)ࡦ߇౒ㅢߢ޽ࠆ࠮࡞ߩᢙ‫ޕ‬㧠ㅪ⚿ߢ⠨߃ߚ႐ว㧘㓞ធ࠮࡞ߩࡄ࠲࡯ࡦߪએਅߩ㧡⒳㘃ߩߺߢ޽ࠆ‫ޕ‬(KI #XGTCIGEJCPIGQHUYGGRKPIRQKPVQHVJGVCUM

0 ဳ㧦㓞ធ࠮࡞߇޿ߕࠇ߽㓚ኂ‛ߢߪߥ޿ࡄ࠲࡯ࡦ‫ޕ‬

KPVJGUCOGTQQODWVFKHHGTGPVUVCTVRQKPVU

1 ဳ㧦㓞ធ࠮࡞ߩ߁ߜ㧘㧝୘߇㓚ኂ‛ߣߥࠆࡄ࠲࡯ࡦ‫ޕ‬

2a ဳ㧦㓞ធ࠮࡞ߩ߁ߜ㧘ኻะߒߥ޿㧞୘߇㓚ኂ‛

2.5ߣߥࠆࡄ࠲࡯ࡦ‫ޕ‬

sweep point

22b ဳ㧦㓞ធ࠮࡞ߩ߁ߜ㧘ኻะߔࠆ㧞୘߇㓚ኂ‛ߣ

1.5ߥࠆࡄ࠲࡯ࡦ‫ޕ‬3 ဳ㧦㓞ធ࠮࡞ߩ߁ߜ㧘㧟୘߇㓚ኂ‛ߣߥࠆࡄ࠲࡯ࡦ‫ޕ‬1 ߎࠇࠄߩ⺑᣿ᄌᢙߣ᝹ᒁࡐࠗࡦ࠻ߣߩ㑆ߦ✢ᒻ㑐ଥ߇޽ࠆߣ઒ቯߒ㧘㊀࿁Ꮻಽᨆߢߩ੍᷹ࠍ⹜ߺߚ‫⿒ޕ‬ᳰᖱႎ

0.5㊂ⷙḰ(AIC)୯ࠍෳ⠨ߦ㧘ߎࠇࠄߩਛߢ㧘࠴ࡖࡀ࡞ᢙ㧔ㄝߩ㐳ߐ߇࠮࡞㧝ㄝಽߩ߽ߩ㧕㧘ఝⷺᢙ㧘࠮࡞㓞ធࡄ࠲࡯ࡦ㪇㪇

10203040㧔0 ဳ㧘2b ဳ㧕ߩ㧠୘ࠍ⺑᣿ᄌᢙߣߒߡㆬᛯߒߚ‫ࠇߎޕ‬time (min.)(KI #XGTCIGEJCPIGQHUYGGRKPIRQKPVQHVJGVCUM
KPFKHHGTGPVTQQOUDWVCVVJGUCOGFKOGPUKQPUࠄߩ⺑᣿ᄌᢙࠍߘࠇߙࠇ x1 㨪 x4 ߣ⟎߈㧘 y ࠍ᝹ᒁ㐿ᆎ ಽᓟߩ᝹ᒁࡐࠗࡦ࠻ߩ੍᷹୯ߣߒߚߣߎࠈ㧘એਅߩ㊀࿁Ꮻᑼ߇ᓧࠄࠇߚ㧔࿑㧣㧕‫ޕ‬㧢㧚⋥ㅴォ࿁ဳࠕ࡞ࠧ࡝࠭ࡓߩ᝹ᒁࡐࠗࡦ࠻੍᷹

y = −0 .014 x1 − 0 .027 x 2 + 0 .025 x 3 − 0 .052 x 4+ 1.802

 ㊀᳿ቯଥᢙߪ 0.86 ߢ޽ࠅ㧘✢ᒻࡕ࠺࡞ߦࠃߞߡዋᢙߩ․ᓽ߆ࠄ᦭ലߥ੍᷹ࠍⴕ߃ࠆߣ޿߁⚿ᨐ߇ᓧࠄࠇߚ‫ޕ‬ ೨▵ߩ⚿ᨐࠍ〯߹߃ߡ㧘ߎߎߢߪㇱደᒻ⁁߆ࠄ㧘⋥ㅴォ࿁ဳࠕ࡞ࠧ࡝࠭ࡓߩ᝹ᒁࡐࠗࡦ࠻ߩ੍᷹߇น⢻߆ᬌ⸽ߔࠆ‫ޕ‬㧣㧚ࠝࡦ࡜ࠗࡦߢߩ᝹ᒁࡐࠗࡦ࠻੍᷹ ㇱደᒻ⁁߆ࠄ޿ߊߟ߆ߩ․ᓽ㊂ࠍ᛽಴ߒ㧘ࡄ࡜ࡔ࡯࠲ൻߒߚ‫ޕ‬㧢⒳㘃ߩㇱደߛߌߢߪਇචಽߥߎߣߣ㧘․ᓽ㊂ ᰴߦ㧘૞ᬺ㗔ၞᒻ⁁ࠍ੐೨ߦ⍮ࠆߎߣߩߢ߈ߥ޿ኅᐸ

᛽಴ࠍኈᤃߦߔࠆℂ↱߆ࠄ㧘ߎߎߢߪᡷ߼ߡᰴߩ࡞࡯࡞↪᝹㒰ࡠࡏ࠶࠻߇૞ᬺਛߦᓧߚᖱႎ߆ࠄ዁᧪ߩ᝹ᒁࡐࠗ

ߢ 108 ⒳㘃ߩᒻ⁁ߩㇱደࠍ↪ᗧߒߚ‫ޕ‬

࡮440 cm528 cm ߩ㐳ᣇᒻߩⓨ㑆ࠍ 88 cm88 cmࡦ࠻ࠍ੍᷹ߔࠆߎߣࠍ⠨߃ࠆ‫ޕ‬዁᧪ߩ᝹ᒁࡐࠗࡦ࠻ࠍ੍ߩ࠮࡞ߦಽഀߒ㧘ߘߩ߁ߜߩ㧢୘ࠍ㒰෰ߔࠆ‫ߩߎޕ‬ㆬᛯߒ㧘૞ᬺല₸ࠍ㜞߼ࠆߎߣ߇น⢻ߦߥࠆߣ⠨߃ࠄࠇࠆ‫ޕ‬᷹ߢ߈ࠇ߫㧘ߘߩ૞ᬺⅣႺߦࠃࠅㆡߒߚࠕ࡞ࠧ࡝࠭ࡓࠍ㧙㧙 ߎߎߢߪ㧘੍᷹ߩߚ߼ߦએਅߩᖱႎࠍ↪޿ࠆߎߣߦߒ ߎࠇ߽᳿ቯଥᢙ߇ 0.82 ߢ޽ߞߚ‫ޕ‬20 ಽߩ႐วߣ 10 ಽߚ‫ߚߒߣ࡞࠺ࡕ߽ࠇߕ޿ߪࠄࠇߎޕ‬᝹㒰ࡠࡏ࠶࠻ߩ࠮ࡦ

ߩ႐วߩ㊀࿁ᏫᑼࠍᲧセߔࠆߣ㧘࠲࡯ࡦᢙߩ஍࿁Ꮻଥᢙࠨ߆ࠄขᓧน⢻ߥᖱႎߢ޽ࠆ‫ޕ‬ߪ೨⠪߇ᓟ⠪ߩඨಽߩ୯ߣߥߞߡ޿ࠆ‫ᤨߪࠇߎޕ‬㑆߇୚࡮࠲࡯ࡦᢙ㧦૞ᬺ㐿ᆎᤨ߆ࠄ⃻ᤨὐ߹ߢߦࡠࡏ࠶࠻߇ߦߥࠆߣ࠲࡯ࡦᢙ߽߶߷୚ߦߥࠆߎߣߦኻᔕߔࠆ‫ߚ߹ޕ‬㧘㓚ኂ‛ߣⴣ⓭ߒ㧘ᣇะォ឵ߒߚ࿁ᢙ‫ޕ‬ᦨᄢ⋥ㅴ〒㔌ߩ஍࿁Ꮻଥᢙߣಾ ߩ୯ߪ߶߷╬ߒ޿‫ߎޕ‬
ࠇߪ 10 ಽ߽⿛ⴕߒߡ޿ࠇ߫ᦨᄢ⋥ㅴ〒㔌߇ߛ޿ߚ޿ᓧ࡮ᦨᄢ⋥ㅴ〒㔌㧦⃻ᤨὐ߹ߢߦ㧘ࡠࡏ࠶࠻߇⋥ㅴߩߺࠄࠇ㧘20 ಽᤨὐߢ߽ߘߩ୯ߦ޽߹ࠅᄌൻ߇ߥ޿ߎߣࠍ␜

ߢ⒖േߢ߈ߚᦨᄢ〒㔌‫ޕ‬ ㇱደ㕙Ⓧߩ౒ㅢߥ 150 ⒳㘃ߩ૞ᬺⅣႺࠍ↪ᗧߒ㧘዁᧪ߒߡ޿ࠆ‫߽ࠄ߆ߣߎࠆ߈ߢ߇㉼⸃ߩࠄࠇߎޕ‬㧘ᓧࠄࠇߚߩ᝹ᒁࡐࠗࡦ࠻߇੍᷹น⢻߆ታ㛎ࠍⴕߞߚ‫ޕ‬ฦⅣႺߦ߅

㊀࿁Ꮻᑼߪᅷᒰߣ޿߃ࠆ‫ޕ‬޿ߡ㧘100 ࿁ߕߟ᝹ᒁࠪࡒࡘ࡟࡯࡚ࠪࡦࠍⴕ޿㧘࠺࡯࠲ એ਄ߩߎߣ߆ࠄ㧘ࠝࡦ࡜ࠗࡦߢ߽㧘✢ᒻࡕ࠺࡞ߦࠃߞ

ࠍขᓧߒߚ‫ޕ‬ߡ᦭ലߥ੍᷹߇ⴕ߃ࠆߣ޿߁⚿ᨐ߇ᓧࠄࠇߚ‫ޕ‬ ߹ߕ㧘᝹ᒁ㐿ᆎᓟ 20 ಽߢ㧘40 ಽᤨὐߢߩ᝹ᒁࡐࠗࡦ࠻ y ߇੍᷹น⢻߆ࠍ⺞ߴߚ‫ࡦ࡯࠲ޕ‬ᢙ x1 㧘ᦨᄢ⋥ㅴ〒㧤㧚߅ࠊࠅߦ㔌 x 2 ࠍ⺑᣿ᄌᢙߣߒ㧘✢ᒻ㑐ଥࠍ઒ቯߒ㧘㊀࿁Ꮻಽᨆ ᧄ⎇ⓥߢߪ㧘ኅᐸ↪᝹㒰ࡠࡏ࠶࠻ߢઍ⴫⊛ߥ⋥ㅴォ࿁ߢߩ੍᷹ࠍ⹜ߺߚ‫ޕ‬ᓧࠄࠇߚ㊀࿁Ꮻᑼࠍએਅߦ␜ߔ‫ޕ‬㊀᳿ቯଥᢙߪ 0.82 ߢ޽ߞߚ‫ޕ‬ဳࠕ࡞ࠧ࡝࠭ࡓߦ߅޿ߡ㧘ㇱደᒻ⁁߿㧘ࡠࡏ࠶࠻ߦࠃߞ

y = −0.0045x1 − 0.00037x2 + 2.52

ߡᓧࠄࠇߚ૞ᬺೋᦼߩ࠮ࡦࠨᖱႎ߆ࠄ㧘᝹ᒁ૞ᬺߩല₸߇੍᷹น⢻ߢ޽ࠆߎߣࠍࠪࡒࡘ࡟࡯࡚ࠪࡦߦࠃߞߡ⏕⹺ ᰴߦ㧘᝹ᒁ㐿ᆎᓟ 10 ಽߩ࠺࡯࠲߆ࠄห᭽ߦ੍᷹น⢻߆ߒߚ‫ޕ‬actual sweep pointࠍ⺞ߴߚ‫ޕ‬ᓧࠄࠇߚ㊀࿁Ꮻᑼࠍએਅߦ␜ߔ㧔࿑㧤㧕

y = −0.0090x1 − 0.00041x2 + 2.50

ෳ⠨ᢥ₂2.11) 㕍ጊ ర㧘↰ፉ⨃᮸㧘ᮮ↰෹㓉㧘የፒഞ৻㧘ጊᧄ⚐
y=x1.9㓶㧦⥄ᓞ⿛ⴕᑼᐥ㕙ᷡ᝹ࡠࡏ࠶࠻ߩ㐿⊒㧘ᣣᧄࡠࡏ2)

1.7⨹੗ ⓛ㧘⚦↰␭ม㧘ᨩᎹ ⚝㧘ዊ㑐◊ᔒ㧘↰ፉᵏᴦ㧘ᦺ ᐽඳ㧘ጟ↰␭ሶ㧦ኅᐸ↪᝹㒰ࡠࡏ࠶࠻ߩࠪ
ࠬ࠹ࡓ⸳⸘, ╙ 48 ࿁⥄േ೙ᓮㅪว⻠Ṷળ, (2005).

1.53) Y. Gabriely, E. Rimon: Spiral-STC: An On-Line Coverage
1.5㪈㪅㪊㪈㪅㪊1.71.9

2.1

forecasted sweep pointf(KI #EVWCNUYGGRRQKPVCPFVJGQPGUHQTGECUVGF
HTQOVJGUJCRGQHVJGTQQO
2.1

actual sweep point࠶࠻ቇળ⹹㧘16㧘1㧘(1998) pp. 57-64.

2003-10, ᣣ┙⵾૞ᚲ, (2003) pp. 13-14.

6) Y.Y. Huang, Z.L. Cao, E.L. Hall: Region Filling

Operations for Mobile Robot Using Computer Graphics,


1.3
1.1

Conf.


1.3

1.5 on1607-1614.

1.14) E. Gonzalez, M. Alarcon, P. Aristizabal, C. Parra: BSA: A5) ⥄ ᓞ ⒖ േ ဳ ߩ ኅ ᐸ ↪ ᝹ 㒰 ࡠ ࡏ ࠶ ࠻ 㧘 ߪ ޿ ߚ ߞ ߊ

1.5

(2002) pp. 954-960.

Robots and Systems, (2003) pp. 1679-1684.

y=x
y=x



1.7

International Conference on Robotics & Automation,

Coverage Algorithm, Intl. Conference on Intelligent

1.9

Algorithm of Grid Environments by a Mobile Robot,

1.7

forecasted
 sweep point

1.9

2.1f

(KI #EVWCNUYGGRRQKPVCPFVJGQPGUHQTGECUVGF

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andAutomation,(1986)

pp.

7) T. Kurt: Hacking Roomba, John Wiley & Sons, (1996).

8) ች⣁࿖↵㧘ቯኅᐽᶈ㧦㧺㧯Ⴃⵝࡠࡏ࠶࠻ߩ゠㆏♖ᐲ⹏ ଔ ᴺ 㧘 ᣣ ᧄ ࡠ ࡏ ࠶ ࠻ ቇ ળ ⹹ 㧘 16, 7, (1998) pp.
1017-1025.

D[UGPUKPIQPNKPG

Robotics9)ᚑᷡㄖ↢㧦㕖ᐓᷤൻߐࠇߚ૏⟎ߣജߩࡂࠗࡉ࡝࠶࠼೙ᓮߦࠃࠆ⎇⏴ടᎿ㧘ᣣᧄࡠࡏ࠶࠻ቇળ⹹㧘14, 4,(1996) pp. 586-592.

10) K. Nonami, N. Shimoi, J. Huang Qing, D. Komizo, H.
Uchida:Developmentof

Teleoperated

Six-legged

Walking Robot for Mine Detection and Mapping of Mine
Field, International Conference on Intelligent Robots andSystems, (2000) pp. 775-779.

11) ጟ↰␭ሶ㧘ᨩᎹ ⚝㧘ᦺ ᐽඳ㧘⨹੗ ⓛ㧘↰ፉᵏᴦ㧘ዊ㑐◊ᔒ㧘⚦↰␭ม㧦ኅᐸ↪᝹㒰ࡠࡏ࠶࠻ߩേ૞೙ᓮࠕ࡞ࠧ࡝࠭ࡓ, ╙ 48 ࿁⥄േ೙ᓮㅪว⻠Ṷળ,(2005).

12) ᄥ↰ 㗅, ୖᨋᄢテ㧘ᣂ੗᳃ᄦ㧦⍮⢻ࡠࡏ࠶࠻౉㐷,ࠦࡠ࠽␠ (2001).

13) ᧲᪯⋥ੱ㧦ਃ⪉㔚ᯏ㧔ᩣ㧕ߦ߅ߌࠆ↢ᵴᡰេࡠࡏ࠶࠻ߩ㐿⊒㧘࠙ࠗ࡯ࠢࠛࡦ࠼࡮࠮ࡒ࠽࡯⾗ᢱ, ᣣᧄᯏ14)

᪾ቇળ, (2003) pp. 23-28.

J. VanderHeide, N. Rao 㧦 Terrain Coverage of an

Unknown Room by an Autonomous Mobile Robot,

Technical Report ORNL/TM-13117, Oak Ridge National
Laboratory, (1995) pp. 1-11.

15) S. Wong, B. MacDonald: A topological Coverage
Algorithm for Mobile Robots, International ConferenceonIntelligent

1685-1690.

RobotsandSystems,(2003)

pp.

16) S. Wong, B. MacDonald: Complete Coverage by Mobile

Robots Using Slice Decomposition Based on Natural
Landmarks, 8th Pacific Rim International Conference on
Artificial Intelligence, (2004), pp. 683-692.

17) ⮐ౝ⑲㓉㧘↲↰ື਽㧦᝹㒰ࡠࡏ࠶࠻‫ޡ‬N-Robo‫ߩޢ‬㐿⊒ߦߟ޿ߡ㧘࠙ࠗ࡯ࠢࠛࡦ࠼࡮࠮ࡒ࠽࡯⾗ᢱ, ᣣᧄᯏ᪾ቇળ, (2003) pp. 43-49.

18) http:// trilobite.electrolux.com/
19) http:// www.karcher.com/20) http://www.kao.co.jp/21) http://www.nedo.go.jp/expo2005/robot/work/page002.html

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