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VINS 预积分 雅各比矩阵和协方差矩阵推导过程

文章目录

  • VINS 预积分 雅各比矩阵和协方差矩阵推导过程
    • 根据中值积分
    • 旋转角度误差推导过程
    • 速度误差推导过程
    • 位置误差推导过程
    • 根据以上的计算结果整理成矩阵形式

根据中值积分

ω k + 1 = ω k + 1 + ω k 2 − b ω k + 1 omega_{k+1} = frac{omega_{k+1} + omega_k}{2} - b_{omega_{k+1}} ωk+1=2ωk+1+ωkbωk+1
q k + 1 = q k ⊗ [ 1 1 2 ω k δ t ] q_{k+1} = q_k otimes begin{bmatrix} 1 \ frac{1}{2} omega_k delta t end{bmatrix} qk+1=qk[121ωkδt]
a k + 1 = q k ( a k − b a k + n a 0 ) + q k + 1 ( a k + 1 − b a k + 1 + n a 1 ) 2 a_{k+1} = frac{q_kleft(a_k - b_{a_k} + n_{a_0}right) + q_{k+1} left(a_{k+1} - b_{a_{k+1}} + n_{a_1}right)}{2} ak+1=2qk(akbak+na0)+qk+1(ak+1bak+1+na1)

旋转角度误差推导过程

  在误差状态方程式最重要的部分是对 δ θ k + 1 delta theta_{k+1} δθk+1部分的推导。

由泰勒公式可得:
δ θ k + 1 ≈ δ θ k + δ θ k ˙ δ t delta theta_{k+1} approx delta theta_k + dot{delta theta_k} delta t δθk+1δθk+δθk˙δt
四元数导数的定义和一般形式定义分别为:
q t ˙ = 1 2 q t ⊗ ω t dot{q_t} = frac{1}{2} q_t otimes omega_t qt˙=21qtωt
q ˙ = 1 2 q ⊗ ω dot{q} = frac{1}{2} q otimes omega q˙=21qω
为了清晰起见,将大信号项和小信号项按角速率分组:
ω ≜ ω m − ω b omega triangleq omega_m - omega_b ωωmωb
δ ω ≜ − δ ω b − ω n delta omega triangleq -delta omega_b - omega_n δωδωbωn
注: ω m omega_m ωm为观测到的角速度值, ω b omega_b ωb角速度的偏置, ω n omega_n ωn 角速度的噪声。
对于 ω t omega_t ωt可以写成两部分:
ω t = ω + δ ω = ω m − ω b − δ ω b − ω n omega_t = omega + delta omega = omega_m - omega_b - delta omega_b - omega_n ωt=ω+δω=ωmωbδωbωn
计算 q t ˙ dot{q_t} qt˙通过左展开和右展开两种不同的方法:
q t ˙ = ( q t − 1 ⊗ δ q ) ˙ = 1 2 q t ⊗ ω t dot{q_t} = dot{left(q_{t-1} otimes delta q right)} = frac{1}{2}q_t otimes omega_t qt˙=(qt1δq)˙=21qtωt
q t ˙ = q t − 1 ˙ ⊗ δ q + q t − 1 ⊗ δ q ˙ = 1 2 q t − 1 ⊗ δ q ⊗ ω t dot{q_t} = dot{q_{t-1}} otimes delta q + q_{t-1} otimes dot{delta q} = frac{1}{2} q_{t-1} otimes delta q otimes omega_t qt˙=qt1˙δq+qt1δq˙=21qt1δqωt
⇒ 1 2 q t − 1 ⊗ ω t − 1 ⊗ δ q + q t − 1 ⊗ δ q ˙ = 1 2 q t − 1 ⊗ δ q ⊗ ω t Rightarrow frac{1}{2} q_{t-1} otimes omega_{t-1} otimes delta q + q_{t-1} otimes dot{delta q} = frac{1}{2} q_{t-1}otimes delta q otimes omega_t 21qt1ωt1δq+qt1δq˙=21qt1δqωt
⇒ 2 δ q ˙ = δ q ⊗ ω t − ω t − 1 ⊗ δ q Rightarrow 2 dot{delta q} = delta q otimes omega_t - omega_{t-1}otimes delta q 2δq˙=δqωtωt1δq

2 δ q ≈ [ 1 δ θ ] 2delta q approx begin{bmatrix} 1 \ delta theta end{bmatrix} 2δq[1δθ]对该公式进行求导得
[ 0 δ θ ˙ ] = 2 δ q ˙ begin{bmatrix} 0 \ dot{delta theta} end{bmatrix} = 2 dot{delta q} [0δθ˙]=2δq˙

[ 0 δ θ t ˙ ] = 2 δ q ˙ = δ q ⊗ ω t − ω t − 1 ⊗ δ q begin{bmatrix} 0 \ dot{delta theta_t} end{bmatrix} = 2 dot{delta q} = delta q otimes omega_t - omega_{t-1} otimes delta q [0δθt˙]=2δq˙=δqωtωt1δq
= [ q ] R ( ω t ) δ q − [ q ] L ( ω t − 1 ) δ q =left[qright]_Rleft(omega_tright) delta q - left[qright]_Lleft(omega_{t-1}right)delta q =[q]R(ωt)δq[q]L(ωt1)δq
= [ 0 − ( ω t − ω t − 1 ) T ( ω t − ω t − 1 ) − [ ω t + ω t − 1 ] × ] [ 1 1 2 δ θ t ] =begin{bmatrix} 0 & -left(omega_t - omega_{t-1}right)^T \ left(omega_t - omega_{t-1}right) & -left[omega_t + omega_{t-1}right]_{times} end{bmatrix}begin{bmatrix} 1 \ frac{1}{2}delta theta_t end{bmatrix} =[0(ωtωt1)(ωtωt1)T[ωt+ωt1]×][121δθt]
= [ 0 − δ ω T δ ω − [ 2 ω t + δ ω ] × ] [ 1 1 2 δ θ t ] =begin{bmatrix} 0 & -{delta omega}^T \ delta omega & -left[2 omega_t + delta omegaright]_{times} end{bmatrix}begin{bmatrix} 1 \ frac{1}{2}delta theta_t end{bmatrix} =[0δωδωT[2ωt+δω]×][121δθt]
根据上式整理得:
δ θ t ˙ = δ ω − [ ω t ] × δ θ t − 1 2 [ δ ω ] × δ θ t ≈ − [ ω t ] × δ θ t + δ ω dot{delta theta_t} = delta omega - left[omega_tright]_{times} delta theta_t - frac{1}{2}left[delta omega right]_{times}delta theta_tapprox-left[omega_tright]_{times}delta theta_t + delta omega δθt˙=δω[ωt]×δθt21[δω]×δθt[ωt]×δθt+δω
⇒ δ θ t ˙ = − [ ω t ] × δ θ t + δ ω Rightarrowdot{delta theta_t} = -left[omega_tright]_{times}delta theta_t + delta omega δθt˙=[ωt]×δθt+δω
⇒ δ θ ˙ = − [ ω m − ω b ] × δ θ − δ ω b − ω n Rightarrow dot{delta theta}=-left[omega_m - omega_bright]_{times}delta theta - delta omega_b - omega_n δθ˙=[ωmωb]×δθδωbωn
⇒ δ θ k ˙ = − [ ω k + 1 + ω k 2 − b g k ] × δ θ k − δ b g k + n ω 0 + n ω 1 2 Rightarrow dot{delta theta_k}= -left[frac{omega_{k+1} + omega_k }{2}-b_{g_k}right]_{times}delta theta_k - delta b_{g_k} + frac{n_{omega_0} + n_{omega_1}}{2} δθk˙=[2ωk+1+ωkbgk]×δθkδbgk+2nω0+nω1
将上式代入 δ θ k + 1 ≈ δ θ k + δ θ k ˙ δ t delta theta_{k+1} approx delta theta_k + dot{delta theta_k} delta t δθk+1δθk+δθk˙δt得:
δ θ k + 1 = ( I − [ ω k + 1 + ω k 2 − b g k ] × δ t ) δ θ k − δ b g k δ t + n ω 0 + n ω 1 2 δ t delta theta_{k+1} = left(I - left[frac{omega_{k+1} + omega_k}{2} - b_{g_k}right]_{times}delta tright)delta theta_k - delta b_{g_k}delta t + frac{n_{omega_0} + n_{omega_1}}{2}delta t δθk+1=(I[2ωk+1+ωkbgk]×δt)δθkδbgkδt+2nω0+nω1δt

速度误差推导过程

δ β k + 1 ≈ δ β k + a k + 1 δ t = δ β k + q k ( a k − b a k + n a 0 ) + q k + 1 ( a k + 1 − b a k + 1 + n a 1 ) 2 δ t delta beta_{k+1} approx delta beta_k + a_{k+1}delta t = delta beta_k + frac{q_kleft(a_k -b_{a_k} + n_{a_0}right) + q_{k+1}left(a_{k+1} - b_{a_{k+1}} + n_{a_1}right)}{2}delta t δβk+1δβk+ak+1δt=δβk+2qk(akbak+na0)+qk+1(ak+1bak+1+na1)δt
即:
δ β k + 1 ≈ δ β k + δ β ˙ δ t delta beta_{k+1} approx delta beta_k + dot{delta beta}delta t δβk+1δβk+δβ˙δt
已知有如下关系成立:
R k = R ( I + [ δ θ ] × ) + O ( ∣ ∣ δ θ ∣ ∣ 2 ) R_k = Rleft(I + left[delta thetaright]_{times}right) + Oleft({||delta theta||}^2right) Rk=R(I+[δθ]×)+O(δθ2)
δ β ˙ = v ˙ = R a B + g dot{delta beta} = dot{v} = R a_B + g δβ˙=v˙=RaB+g
对于a(加速度)可以写成以下两部分:
a B ≜ a m − b a a_B triangleq a_m - b_a aBamba
δ a B ≜ − δ b a − n a delta a_B triangleq -delta b_a - n_a δaBδbana
在惯性系中可以把加速度写成两部分的组合:
a k = R k ( a B + δ a B ) + g a_k = R_kleft(a_B + delta a_Bright) + g ak=Rk(aB+δaB)+g
v k ˙ = v ˙ + δ v ˙ = R ( I + [ δ θ ] × ) ( a B + δ a B ) + g dot{v_k}=dot{v} + dot{delta v}=Rleft(I + left[delta thetaright]_{times}right)left(a_B + delta a_Bright)+g vk˙=v˙+δv˙=R(I+[δθ]×)(aB+δaB)+g
⇒ v k ˙ = R a B + g + δ v ˙ = R a B + R δ a B + R [ δ θ ] × a B + R [ δ θ ] × δ a B + g Rightarrow dot{v_k}=Ra_B + g + dot{delta v} = Ra_B + Rdelta a_B+Rleft[delta thetaright]_{times}a_B + Rleft[delta thetaright]_{times}delta a_B + g vk˙=RaB+g+δv˙=RaB+RδaB+R[δθ]×aB+R[δθ]×δaB+g
⇒ δ v ˙ = R ( δ a B + [ δ θ ] × a B ) + R [ δ θ ] × δ a B Rightarrowdot{delta v}=Rleft(delta a_B + left[delta thetaright]_{times}a_Bright)+Rleft[delta thetaright]_{times}delta a_B δv˙=R(δaB+[δθ]×aB)+R[δθ]×δaB
消除二阶项,并重新组织叉乘( [ a ] × b = − [ b ] × a left[aright]_{times}b = -left[bright]_{times}a [a]×b=[b]×a):
δ v ˙ = R ( δ a B − [ a B ] × δ θ ) dot{delta v} = Rleft(delta a_B - left[a_Bright]_{times}deltathetaright) δv˙=R(δaB[aB]×δθ)
把已知的公式代入上式中得到:
δ v ˙ = R ( − [ a m − b a ] × δ θ − δ b a − n a ) = − R [ a m − b a ] × δ θ − R δ b a − R n a dot{delta v} = Rleft(-left[a_m - b_aright]_{times}delta theta - delta b_a - n_aright)=-Rleft[a_m - b_aright]_{times}delta theta - Rdelta b_a - R n_a δv˙=R([amba]×δθδbana)=R[amba]×δθRδbaRna
  为了简化表达,通常假设加速度计噪声是白色的,不相关的,各向同性的
E [ n a ] = 0 Eleft[n_aright] = 0 E[na]=0
E [ n a n a T ] = σ a 2 I Eleft[n_a{n_a}^Tright]={sigma_a}^2I E[nanaT]=σa2I
  协方差椭球是以原点为中心的球面,意味着其均值和协方差在旋转时是不变的。

E [ R n a ] = R E [ n a ] = 0 Eleft[R n_aright]=REleft[n_aright] = 0 E[Rna]=RE[na]=0
E [ ( R n a ) ( R n a ) T ] = R E [ n a n a T ] R T = R σ a 2 I R T = σ a 2 I Eleft[left(R n_aright)left(R n_aright)^Tright]=REleft[n_a {n_a}^Tright]R^T = R {sigma_a}^2IR^T = {sigma_a}^2I E[(Rna)(Rna)T]=RE[nanaT]RT=Rσa2IRT=σa2I

重新定义加速度计的噪声:
R n a → n a Rn_a to n_a Rnana
则有:
δ v ˙ = R ( − [ a m − b a ] × δ θ − δ b a − n a ) = − R [ a m − b a ] × δ θ − R δ b a − n a dot{delta v} = Rleft(-left[a_m - b_aright]_{times}delta theta - delta b_a - n_aright)=-Rleft[a_m - b_aright]_{times}delta theta - Rdelta b_a - n_a δv˙=R([amba]×δθδbana)=R[amba]×δθRδbana
δ β k ˙ = − 1 2 q k [ a k − b a k ] × δ θ k − 1 2 q k + 1 [ a k + 1 − b a k + 1 ] × δ θ k + 1 dot{delta beta_k}=-frac{1}{2}q_kleft[a_k-b_{a_k}right]_{times}deltatheta_k - frac{1}{2}q_{k+1}left[a_{k+1} - b_{a_{k+1}}right]_{times}deltatheta_{k+1} δβk˙=21qk[akbak]×δθk21qk+1[ak+1bak+1]×δθk+1
− 1 2 ( q k + q k + 1 ) δ b a k − 1 2 ( q k n a 0 + q k + 1 n a 1 ) - frac{1}{2}left(q_k + q_{k+1}right)delta b_{a_k}-frac{1}{2}left(q_k n_{a_0} + q_{k+1} n_{a_1}right) 21(qk+qk+1)δbak21(qkna0+qk+1na1)
δ θ k + 1 delta theta_{k+1} δθk+1代入上式得:
δ β k ˙ = − 1 2 q k [ a k − b a k ] × δ θ k − 1 2 q k + 1 [ a k + 1 − b a k + 1 ] × dot{delta beta_k} = -frac{1}{2}q_kleft[a_k-b_{a_k}right]_{times}deltatheta_k - frac{1}{2}q_{k+1}left[a_{k+1} - b_{a_{k+1}}right]_{times} δβk˙=21qk[akbak]×δθk21qk+1[ak+1bak+1]× ( ( I − [ ω k + 1 + ω k 2 − b g k ] × δ t ) δ θ k − δ b g k δ t + n ω 0 + n ω 1 2 δ t ) left(left(I - left[frac{omega_{k+1} + omega_k}{2} - b_{g_k}right]_{times}delta tright)delta theta_k - delta b_{g_k}delta t + frac{n_{omega_0} + n_{omega_1}}{2}delta tright) ((I[2ωk+1+ωkbgk]×δt)δθkδbgkδt+2nω0+nω1δt)
− 1 2 ( q k + q k + 1 ) δ b a k − 1 2 ( q k n a 0 + q k + 1 n a 1 ) - frac{1}{2}left(q_k + q_{k+1}right)delta b_{a_k}-frac{1}{2}left(q_k n_{a_0} + q_{k+1} n_{a_1}right) 21(qk+qk+1)δbak21(qkna0+qk+1na1)
把上式代入
δ β k + 1 ≈ δ β k + δ β k ˙ δ t delta beta_{k+1} approx delta beta_k + dot{delta beta_k}delta t δβk+1δβk+δβk˙δt

位置误差推导过程

δ α k + 1 = δ α k + δ α k ˙ δ t delta alpha_{k+1} = delta alpha_k + dot{delta alpha_k}delta t δαk+1=δαk+δαk˙δt
δ β ˙ δ t dot{delta beta}delta t δβ˙δt表示的是速度的增量,那么在该速度的增量下的位置的增量为:
δ a k ˙ = 1 2 δ β k ˙ δ t dot{delta a_k} = frac{1}{2}dot{delta beta_k}delta t δak˙=21δβk˙δt
= 1 4 q k [ a k − b a k ] × δ θ δ t =frac{1}{4}q_kleft[a_k - b_{a_k}right]_{times}delta theta delta t =41qk[akbak]×δθδt
− 1 4 q k + 1 [ a k + 1 − b a k + 1 ] × ( ( I − [ ω k + 1 + ω k 2 ] × δ t ) δ θ k − δ b g k δ t + n w 0 + n w 1 2 δ t ) δ t -frac{1}{4}q_{k+1}left[a_{k+1}-b_{a_{k+1}}right]_{times}left(left(I-left[frac{omega_{k+1} + omega_k}{2}right]_{times}delta tright)delta theta_k-delta b_{g_k}delta t + frac{n_{w_0} + n_{w_1}}{2}delta tright)delta t 41qk+1[ak+1bak+1]×((I[2ωk+1+ωk]×δt)δθkδbgkδt+2nw0+nw1δt)δt
− 1 4 ( q k + q k + 1 ) δ b a k δ t − 1 4 ( q k n 0 + q k + 1 n a 1 ) δ t -frac{1}{4}left(q_k + q_{k+1}right)delta b_{a_k} delta t - frac{1}{4}left(q_k n_0 + q_{k+1} n_{a_1}right)delta t 41(qk+qk+1)δbakδt41(qkn0+qk+1na1)δt
根据上式可以得到: δ α k + 1 delta alpha_{k+1} δαk+1

根据以上的计算结果整理成矩阵形式

[ δ α k + 1 δ θ k + 1 δ β k + 1 δ b a k + 1 δ b g k + 1 ] = [ I f 01 δ t − 1 4 ( q k + q k + 1 ) δ t 2 f 04 0 I − [ ω k + 1 + ω k 2 − b w k ] × δ t 0 0 − δ t 0 f 21 I − 1 2 ( q k + q k + 1 ) δ t f 24 0 0 0 I 0 0 0 0 0 I ] [ δ α k δ θ k δ β k δ b a k δ b g k ] begin{bmatrix} delta alpha_{k+1} \ delta theta_{k+1} \ delta beta_{k+1} \ delta b_{a_{k+1}} \ delta b_{g_{k+1}} end{bmatrix}= begin{bmatrix} I & f_{01} & delta t & -frac{1}{4}left(q_k + q_{k+1}right){delta t}^2 & f_{04} \ 0 & I - left[frac{omega_{k+1} + omega_k}{2} - b_{w_k}right]_{times}delta t & 0 & 0 & -delta t \ 0 & f_{21} & I & -frac{1}{2}left(q_k + q_{k+1}right)delta t & f_{24} \ 0 & 0 & 0 & I & 0 \ 0 & 0 & 0 & 0 & I end{bmatrix} begin{bmatrix} delta alpha_k \ delta theta_k \ delta beta_k \ delta b_{a_k} \ delta b_{g_k} end{bmatrix} δαk+1δθk+1δβk+1δbak+1δbgk+1=I0000f01I[2ωk+1+ωkbwk]×δtf2100δt0I0041(qk+qk+1)δt2021(qk+qk+1)δtI0f04δtf240Iδαkδθkδβkδbakδbgk
+ [ 1 4 q k δ t 2 v 01 1 4 q k + 1 δ t 2 v 03 0 0 0 1 2 δ t 0 1 2 δ t 0 0 1 2 q k δ t v 21 1 2 q k + 1 δ t v 23 0 0 0 0 0 0 δ t 0 0 0 0 0 0 δ t ] [ n a 0 n w 0 n a 1 n w 1 n b a n b g ] +begin{bmatrix} frac{1}{4}q_k{delta t}^2 & v_{01} & frac{1}{4}q_{k+1}{delta t}^2 & v_{03} & 0 & 0 \ 0 & frac{1}{2}delta t & 0 & frac{1}{2}delta t & 0 & 0 \ frac{1}{2}q_kdelta t & v_{21} & frac{1}{2}q_{k+1}delta t & v_{23} & 0 & 0 \ 0 & 0 & 0 & 0 & delta t & 0 \ 0 & 0 & 0 & 0 & 0 & delta t end{bmatrix} begin{bmatrix} n_{a_0} \ n_{w_0} \ n_{a_1} \ n_{w_1} \ n_{b_a} \ n_{b_g} end{bmatrix} +41qkδt2021qkδt00v0121δtv210041qk+1δt2021qk+1δt00v0321δtv2300000δt00000δtna0nw0na1nw1nbanbg
其中:
f 01 = − 1 4 q k [ a k − b a k ] × δ t 2 − 1 4 q k + 1 [ a k + 1 − b a k ] × ( I − [ ω k + ω k + 1 2 − b g k ] × δ t ) δ t 2 f_{01}=-frac{1}{4}q_kleft[a_k-b_{a_k}right]_{times}{delta t}^2 - frac{1}{4}q_{k+1}left[a_{k+1} - b_{a_k}right]_{times}left(I - left[frac{omega_k + omega_{k+1}}{2} - b_{g_k}right]_{times}delta tright){delta t}^2 f01=41qk[akbak]×δt241qk+1[ak+1bak]×(I[2ωk+ωk+1bgk]×δt)δt2
f 21 = − 1 2 q k [ a k − b a k ] × δ t − 1 2 q k + 1 [ a k + 1 − b a k ] × ( I − [ ω k + ω k + 1 2 ] × δ t ) δ t f_{21}=-frac{1}{2}q_kleft[a_k - b_{a_k}right]_{times}delta t - frac{1}{2}q_{k+1}left[a_{k+1}-b_{a_k}right]_{times}left(I-left[frac{omega_k + omega_{k+1}}{2}right]_{times}delta tright)delta t f21=21qk[akbak]×δt21qk+1[ak+1bak]×(I[2ωk+ωk+1]×δt)δt
f 04 = 1 4 ( q k + 1 [ a k + 1 − b a k ] × δ t 2 ) δ t f_{04}=frac{1}{4}left(q_{k+1}left[a_{k+1}-b_{a_k}right]_{times}{delta t}^2right)delta t f04=41(qk+1[ak+1bak]×δt2)δt
f 24 = 1 2 ( q k + 1 [ a k + 1 − b a k ] × δ t ) δ t f_{24} = frac{1}{2}left(q_{k+1}left[a_{k+1} - b_{a_k}right]_{times}delta tright)delta t f24=21(qk+1[ak+1bak]×δt)δt
v 01 = − 1 4 ( q k + 1 [ a k + 1 − b a k ] × δ t 2 ) 1 2 δ t v_{01} = -frac{1}{4}left(q_{k+1}left[a_{k+1} - b_{a_k}right]_{times}{delta t}^2right) frac{1}{2}delta t v01=41(qk+1[ak+1bak]×δt2)21δt
v 03 = − 1 4 ( q k + 1 [ a k + 1 − b a k ] × δ t 2 ) 1 2 δ t v_{03} = -frac{1}{4}left(q_{k+1}left[a_{k+1} - b_{a_k}right]_{times}{delta t}^2right) frac{1}{2}delta t v03=41(qk+1[ak+1bak]×δt2)21δt
v 21 = − 1 2 ( q k + 1 [ a k + 1 − b a k ] × δ t 2 ) 1 2 δ t v_{21}=-frac{1}{2}left(q_{k+1}left[a_{k+1} - b_{a_k}right]_{times}{delta t}^2right)frac{1}{2}delta t v21=21(qk+1[ak+1bak]×δt2)21δt
v 23 = − 1 2 ( q k + 1 [ a k + 1 − b a k ] × δ t 2 ) 1 2 δ t v_{23}=-frac{1}{2}left(q_{k+1}left[a_{k+1} - b_{a_k}right]_{times}{delta t}^2right)frac{1}{2}delta t v23=21(qk+1[ak+1bak]×δt2)21δt
将上个矩阵简写为:
δ k + 1 = F δ k + V Q delta_{k+1} = F delta_k + VQ δk+1=Fδk+VQ
最后得到系统的雅各比矩阵 J k + 1 J_{k+1} Jk+1和协方差矩阵 P k + 1 P_{k+1} Pk+1
初始值为:
J k = I J_k = I Jk=I
P k = 0 P_k = 0 Pk=0
J k + 1 = F J k J_{k+1} = FJ_k Jk+1=FJk
P k + 1 = F P k F T + V Q V T P_{k+1} = FP_kF^T + VQV^T Pk+1=FPkFT+VQVT

最后

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