• Optics and Precision Engineering
  • Vol. 29, Issue 9, 2126 (2021)
Xiao-bin HONG1,*, Zheng-pan XU1, Xin-yong WEI1, Kun-cai ZHU1, and Yuan-ming CHEN2
Author Affiliations
  • 1College of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou50640, China
  • 2College of Civil Engineering and Transportation, South China University of Technology, Guangzhou510641, China
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    DOI: 10.37188/OPE.2021.0272 Cite this Article
    Xiao-bin HONG, Zheng-pan XU, Xin-yong WEI, Kun-cai ZHU, Yuan-ming CHEN. Dynamic obstacle avoidance of unmanned surface vehicle based on improved speed obstacle method[J]. Optics and Precision Engineering, 2021, 29(9): 2126 Copy Citation Text show less

    Abstract

    Aiming at solving the dynamic collision avoidance problem for unmanned surface vehicle under complex marine status, this study constructs the obstacle model and the collision risk model to achieve the track re-planning of dynamic collision avoidance in complex sea conditions with the improved velocity obstacle method that introduced multiple constraints.Firstly, an obstacle model description method for rectangular bounding box was proposed for USV's geometric characteristics of large aspect ratio.A relative motion model of USV in hull coordinate system was established with the relative motion parameters calculated. Secondly,the collision risk was calculated to determine the time to start avoiding the obstacle.Lastly, improved obstacle avoidance path was constructed by introducing obstacle model constraints and characteristic constraints of USV’s autonomous local obstacle avoidance system based on velocity obstacle method. The track re-planning results were obtained through experiments.The simulated experiment on the physical simulation platform of V-REP (Virtual Robot Experimentation Platform) and the actual ship obstacle avoidance experiment show that the path re-planning time during collision avoidance is less than 15 s at a speed of 12 knots, meeting the dynamic collision avoidance requirements of unmanned surface vehicle under multiple constraints of actual navigation.
    vo=vox2+voy2(1)

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    φu=arctanvuyvux+α(2)

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    α=0         if vux0,vuy0180     if vux<0,vuy<0180     if vux0,vuy<0360     if vux<0,vuy0(3)

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    vo=vox2+voy2(4)

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    φo=arctanvoyvox+α(5)

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    K=vovu(6)

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    vr=vrx2+vry2(7)

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    φr=arctanvryvrx+α(8)

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    vrx=vox-vuxvry=voy-vuy(9)

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    RT=xo-xu2+yo-yu2(10)

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    αT=arctanxo-xuyo-yu+α(11)

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    θT=αT-φu(12)

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    D=RTsinφr-αT-π(13)

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    T=RTcosφr-αT-π/vr(14)

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    γDCPA=1   Dd112-12sinπd2-d1D-d1+d22   d1<Dd20   d2<D(15)

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    d1=1.1-0.2θT/180°   0θT<112.5°1.0-0.4θT/180°   112.5°θT<180°1.0-0.4360-θT/180°   180°θT<247.5°1.1-0.2360-θT/180°   247.5°θT360°(16)

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    d2=2d1(17)

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    γTCPA=1   Tt1t2-Tt2-t12   t1<Tt20   t2<T(18)

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    t1=D12-D2vr(19)

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    t2=122-D2vr(20)

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    γ=αDCPAγDCPA+αTCPAγTCPA(21)

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    λPu,vr=Pu+vrtt0(22)

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    RCCUO=vrλPu,vrO(23)

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    VOUO=RCCUOvo(24)

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    VOUO=vuλPu,vrO(25)

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    VO=VOi(27)

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    WVOUO=VOUOWO(28)

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    vd=vvvc-v·bΔt,vc+v·aΔt(29)

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    ωd=ωωωc-ω·bΔt,ωc+ω·aΔt(30)

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    vd2RTv·b,ωd2RTω·b(31)

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    θd=θθθc+ωcΔt-12ω·bΔt2,θc+ωcΔt+12ω·aΔt2(32)

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    RAV=VVRV,VWVOUO(33)

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    V3=vpo-puv-vo<0,vWVOUO(34)

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    V1=vpo-pu×v-voz<0,vWVOUO,vV3(35)

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    V2=vpo-pu×v-voz>0,vWVOUO,vV3(36)

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    CRAV=vvRAV,vV1V3(37)

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    CRAV=vvRAV,vV2V3(38)

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    Cij=ω1vicos θjvisin θj-vg2+ω2vicos θjvisin θj-vccos θcvcsin θc2(39)

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    vg=vcPg-PuPg-Pu2(40)

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    Pr=Pu+vuoptnΔt(41)

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    Xiao-bin HONG, Zheng-pan XU, Xin-yong WEI, Kun-cai ZHU, Yuan-ming CHEN. Dynamic obstacle avoidance of unmanned surface vehicle based on improved speed obstacle method[J]. Optics and Precision Engineering, 2021, 29(9): 2126
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