ORB_SLAM3_IMU预积分理论推导(更新)

2023-10-17 08:30

本文主要是介绍ORB_SLAM3_IMU预积分理论推导(更新),希望对大家解决编程问题提供一定的参考价值,需要的开发者们随着小编来一起学习吧!

  • ORB SLAM3系统初始化
  • ORB SLAM3 构建Frame
  • ORB_SLAM3 单目初始化
  • ORB_SLAM3 双目匹配
  • ORB_SLAM3_IMU预积分理论推导(预积分项)
  • ORB_SLAM3_IMU预积分理论推导(噪声分析)
  • ORB_SLAM3_IMU预积分理论推导(更新)
  • ORB_SLAM3_IMU预积分理论推导(残差)
  • ORB_SLAM3_优化方法 Pose优化
  • ORB_SLAM3 闭环检测

在这里插入图片描述

预积分测量值更新

当bias不发生变化时

  • Δ R ~ i j − 1 → Δ R ~ i j \Delta \tilde{R} _{ij-1}\to \Delta \tilde{R}_{ij} ΔR~ij1ΔR~ij
    Δ R ~ i j = ∏ k = i j − 1 Exp ⁡ ( ( ω ~ k − b i g ) Δ t ) = ∏ k = i j − 2 Exp ⁡ ( ( ω ~ k − b i g ) Δ t ) ⋅ Exp ⁡ ( ( ω ~ j − 1 − b i g ) Δ t ) = Δ R ~ i j − 1 ⋅ Δ R ~ j − 1 j \begin{array}{l} \Delta \tilde{\mathbf{R}}_{i j}=\prod_{k=i}^{j-1} \operatorname{Exp}\left(\left(\tilde{\boldsymbol{\omega}}_{k}-\mathbf{b}_{i}^{g}\right) \Delta t\right) \\ =\prod_{k=i}^{j-2} \operatorname{Exp}\left(\left(\tilde{\boldsymbol{\omega}}_{k}-\mathbf{b}_{i}^{g}\right) \Delta t\right)\cdot \operatorname{Exp}\left(\left(\tilde{\boldsymbol{\omega}}_{j-1}-\mathbf{b}_{i}^{g}\right) \Delta t\right) \\ =\Delta \tilde{\mathbf{R}}_{i j-1}\cdot\Delta \tilde{\mathbf{R}}_{j-1 j} \end{array} ΔR~ij=k=ij1Exp((ω~kbig)Δt)=k=ij2Exp((ω~kbig)Δt)Exp((ω~j1big)Δt)=ΔR~ij1ΔR~j1j

  • Δ v ~ i j − 1 → Δ v ~ i j \Delta \tilde{v}_{ij-1} \to \Delta \tilde{v}_{ij} Δv~ij1Δv~ij
    Δ v ~ i j ≜ ∑ k = i j − 1 [ Δ R ~ i k ⋅ ( f ~ k − b i a ) ⋅ Δ t ] ≜ ∑ k = i j − 2 [ Δ R ~ i k ⋅ ( f ~ k − b i a ) ⋅ Δ t ] + Δ R ~ i j − 1 ⋅ ( f ~ j − 1 − b i a ) ⋅ Δ t ≜ Δ v ~ i j − 1 + Δ R ~ i j − 1 ⋅ ( f ~ j − 1 − b i a ) ⋅ Δ t \begin{array}{l} \Delta \tilde{\mathbf{v}}_{i j} \triangleq \sum_{k=i}^{j-1}\left[\Delta \tilde{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\mathbf{b}_{i}^{a}\right) \cdot \Delta t\right] \\ \triangleq \sum_{k=i}^{j-2}\left[\Delta \tilde{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\mathbf{b}_{i}^{a}\right) \cdot \Delta t\right] + \Delta \tilde{\mathbf{R}}_{i j-1} \cdot\left(\tilde{\mathbf{f}}_{j-1}-\mathbf{b}_{i}^{a}\right) \cdot \Delta t\\ \triangleq \Delta \tilde{\mathbf{v}}_{i j-1}+ \Delta \tilde{\mathbf{R}}_{i j-1} \cdot\left(\tilde{\mathbf{f}}_{j-1}-\mathbf{b}_{i}^{a}\right) \cdot \Delta t \end{array} Δv~ijk=ij1[ΔR~ik(f~kbia)Δt]k=ij2[ΔR~ik(f~kbia)Δt]+ΔR~ij1(f~j1bia)ΔtΔv~ij1+ΔR~ij1(f~j1bia)Δt

  • Δ p ~ i j − 1 → Δ p ~ i j \Delta \tilde{p}_{ij-1} \to \Delta \tilde{p}_{ij} Δp~ij1Δp~ij
    Δ p ~ i j ≜ ∑ k = i j − 1 [ Δ v ~ i k Δ t + 1 2 Δ R ~ i k ⋅ ( f ~ k − b i a ) Δ t 2 ] ≜ ∑ k = i j − 2 [ Δ v ~ i k Δ t + 1 2 Δ R ~ i k ⋅ ( f ~ k − b i a ) Δ t 2 ] + Δ v ~ i j − 1 Δ t + 1 2 Δ R ~ i j − 1 ⋅ ( f ~ j − 1 − b i a ) Δ t 2 ≜ Δ p ~ i j − 1 + Δ v ~ i j − 1 Δ t + 1 2 Δ R ~ i j − 1 ⋅ ( f ~ j − 1 − b i a ) Δ t 2 \begin{array}{l} \Delta \tilde{\mathbf{p}}_{i j} \triangleq \sum_{k = i}^{j-1}\left[\Delta \tilde{\mathbf{v}}_{i k} \Delta t+\frac{1}{2} \Delta \tilde{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\mathbf{b}_{i}^{a}\right) \Delta t^{2}\right] \\ \triangleq \sum_{k = i}^{j-2}\left[\Delta \tilde{\mathbf{v}}_{i k} \Delta t+\frac{1}{2} \Delta \tilde{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\mathbf{b}_{i}^{a}\right) \Delta t^{2}\right] + \Delta \tilde{\mathbf{v}}_{i j-1} \Delta t+\frac{1}{2} \Delta \tilde{\mathbf{R}}_{i j-1} \cdot\left(\tilde{\mathbf{f}}_{j-1}-\mathbf{b}_{i}^{a}\right) \Delta t^{2} \\ \triangleq \Delta \tilde{\mathbf{p}}_{i j-1} + \Delta \tilde{\mathbf{v}}_{i j-1} \Delta t+\frac{1}{2} \Delta \tilde{\mathbf{R}}_{i j-1} \cdot\left(\tilde{\mathbf{f}}_{j-1}-\mathbf{b}_{i}^{a}\right) \Delta t^{2} \end{array} Δp~ijk=ij1[Δv~ikΔt+21ΔR~ik(f~kbia)Δt2]k=ij2[Δv~ikΔt+21ΔR~ik(f~kbia)Δt2]+Δv~ij1Δt+21ΔR~ij1(f~j1bia)Δt2Δp~ij1+Δv~ij1Δt+21ΔR~ij1(f~j1bia)Δt2

预积分测量值更新

当bias发生变化时,利用线性化来进行bias变化时预积分项的一阶近似更新

  • bias更新
    • b ˉ \bar{b} bˉ:旧的bias
    • b ^ \hat{b} b^:新的bias
    • δ b \delta b δb:bias更新量
      b ^ i g ← b ˉ i g + δ b i g b ^ i a ← b ˉ i a + δ b i a \begin{array}{c} \hat{b} _{i}^{g}\gets \bar{b} _{i}^{g}+\delta b_{i}^{g} \\ \hat{b} _{i}^{a}\gets \bar{b} _{i}^{a}+\delta b_{i}^{a} \end{array} b^igbˉig+δbigb^iabˉia+δbia
  • 一阶近似更新:
    Δ R ~ i j ( b ^ i g ) ≈ Δ R ~ i j ( b ‾ i g ) ⋅ Exp ⁡ ( ∂ Δ R ‾ i j ∂ b ‾ g δ b i g ) Δ v ~ i j ( b ^ i g , b ^ i a ) ≈ Δ v ~ i j ( b ‾ i g , b ‾ i a ) + ∂ Δ v ‾ i j ∂ b ‾ g δ b i g + ∂ Δ v ‾ i j ∂ b ‾ a δ b i a Δ p ~ i j ( b ^ i g , b ^ i a ) ≈ Δ p ~ i j ( b ‾ i g , b ‾ i a ) + ∂ Δ p ‾ i j ∂ b ‾ g δ b i g + ∂ Δ p ‾ i j ∂ b ‾ a δ b i a \begin{array}{l} \Delta \tilde{\mathbf{R}}_{i j}\left(\hat{\mathbf{b}}_{i}^{g}\right) \approx \Delta \tilde{\mathbf{R}}_{i j}\left(\overline{\mathbf{b}}_{i}^{g}\right) \cdot \operatorname{Exp}\left(\frac{\partial \Delta \overline{\mathbf{R}}_{i j}}{\partial \overline{\mathbf{b}}^{g}} \delta \mathbf{b}_{i}^{g}\right) \\ \Delta \tilde{\mathbf{v}}_{i j}\left(\hat{\mathbf{b}}_{i}^{g}, \hat{\mathbf{b}}_{i}^{a}\right) \approx \Delta \tilde{\mathbf{v}}_{i j}\left(\overline{\mathbf{b}}_{i}^{g}, \overline{\mathbf{b}}_{i}^{a}\right)+\frac{\partial \Delta \overline{\mathbf{v}}_{i j}}{\partial \overline{\mathbf{b}}^{g}} \delta \mathbf{b}_{i}^{g}+\frac{\partial \Delta \overline{\mathbf{v}}_{i j}}{\partial \overline{\mathbf{b}}^{a}} \delta \mathbf{b}_{i}^{a} \\ \Delta \tilde{\mathbf{p}}_{i j}\left(\hat{\mathbf{b}}_{i}^{g}, \hat{\mathbf{b}}_{i}^{a}\right) \approx \Delta \tilde{\mathbf{p}}_{i j}\left(\overline{\mathbf{b}}_{i}^{g}, \overline{\mathbf{b}}_{i}^{a}\right)+\frac{\partial \Delta \overline{\mathbf{p}}_{i j}}{\partial \overline{\mathbf{b}}^{g}} \delta \mathbf{b}_{i}^{g}+\frac{\partial \Delta \overline{\mathbf{p}}_{i j}}{\partial \overline{\mathbf{b}}^{a}} \delta \mathbf{b}_{i}^{a} \end{array} ΔR~ij(b^ig)ΔR~ij(big)Exp(bgΔRijδbig)Δv~ij(b^ig,b^ia)Δv~ij(big,bia)+bgΔvijδbig+baΔvijδbiaΔp~ij(b^ig,b^ia)Δp~ij(big,bia)+bgΔpijδbig+baΔpijδbia
  • 符号简化:
    Δ R ^ i j ≐ Δ R ~ i j ( b ^ i g ) , Δ R ‾ i j ≐ Δ R ~ i j ( b ‾ i g ) Δ v ^ i j ≐ Δ v ~ i j ( b ^ i g , b ^ i a ) , Δ v ‾ i j ≐ Δ v ~ i j ( b ‾ i g , b ‾ i a ) Δ p ^ i j ≐ Δ p ~ i j ( b ^ i g , b ^ i a ) , Δ p ‾ i j ≐ Δ p ~ i j ( b ‾ i g , b ‾ i a ) \begin{array}{l} \Delta \hat{\mathbf{R}}_{i j} \doteq \Delta \tilde{\mathbf{R}}_{i j}\left(\hat{\mathbf{b}}_{i}^{g}\right), \Delta \overline{\mathbf{R}}_{i j} \doteq \Delta \tilde{\mathbf{R}}_{i j}\left(\overline{\mathbf{b}}_{i}^{g}\right) \\ \Delta \hat{\mathbf{v}}_{i j} \doteq \Delta \tilde{\mathbf{v}}_{i j}\left(\hat{\mathbf{b}}_{i}^{g}, \hat{\mathbf{b}}_{i}^{a}\right), \Delta \overline{\mathbf{v}}_{i j} \doteq \Delta \tilde{\mathbf{v}}_{i j}\left(\overline{\mathbf{b}}_{i}^{g}, \overline{\mathbf{b}}_{i}^{a}\right) \\ \Delta \hat{\mathbf{p}}_{i j} \doteq \Delta \tilde{\mathbf{p}}_{i j}\left(\hat{\mathbf{b}}_{i}^{g}, \hat{\mathbf{b}}_{i}^{a}\right), \Delta \overline{\mathbf{p}}_{i j} \doteq \Delta \tilde{\mathbf{p}}_{i j}\left(\overline{\mathbf{b}}_{i}^{g}, \overline{\mathbf{b}}_{i}^{a}\right) \end{array} ΔR^ijΔR~ij(b^ig),ΔRijΔR~ij(big)Δv^ijΔv~ij(b^ig,b^ia),ΔvijΔv~ij(big,bia)Δp^ijΔp~ij(b^ig,b^ia),ΔpijΔp~ij(big,bia)
  • 更新公式可以简化为:
    Δ R ^ i j ≈ Δ R ‾ i j ⋅ Exp ⁡ ( ∂ Δ R ‾ i j ∂ b ‾ g δ b i g ) Δ v ^ i j ≈ Δ v ‾ i j + ∂ Δ v ‾ i j ∂ b ‾ g δ b i g + ∂ Δ v ‾ i j ∂ b ‾ a δ b i a Δ p ^ i j ≈ Δ p ‾ i j + ∂ Δ p ‾ i j ∂ b ‾ g δ b i g + ∂ Δ p ‾ i j ∂ b ‾ a δ b i a \begin{array}{l} \Delta \hat{\mathbf{R}}_{i j} \approx \Delta \overline{\mathbf{R}}_{i j} \cdot \operatorname{Exp}\left(\frac{\partial \Delta \overline{\mathbf{R}}_{i j}}{\partial \overline{\mathbf{b}}^{g}} \delta \mathbf{b}_{i}^{g}\right) \\ \Delta \hat{\mathbf{v}}_{i j} \approx \Delta \overline{\mathbf{v}}_{i j}+\frac{\partial \Delta \overline{\mathbf{v}}_{i j}}{\partial \overline{\mathbf{b}}^{g}} \delta \mathbf{b}_{i}^{g}+\frac{\partial \Delta \overline{\mathbf{v}}_{i j}}{\partial \overline{\mathbf{b}}^{a}} \delta \mathbf{b}_{i}^{a} \\ \Delta \hat{\mathbf{p}}_{i j} \approx \Delta \overline{\mathbf{p}}_{i j}+\frac{\partial \Delta \overline{\mathbf{p}}_{i j}}{\partial \overline{\mathbf{b}}^{g}} \delta \mathbf{b}_{i}^{g}+\frac{\partial \Delta \overline{\mathbf{p}}_{i j}}{\partial \overline{\mathbf{b}}^{a}} \delta \mathbf{b}_{i}^{a} \end{array} ΔR^ijΔRijExp(bgΔRijδbig)Δv^ijΔvij+bgΔvijδbig+baΔvijδbiaΔp^ijΔpij+bgΔpijδbig+baΔpijδbia
  • ∂ Δ R ‾ i j ∂ b ‾ g \frac{\partial \Delta \overline{\mathbf{R}}_{i j}}{\partial \overline{\mathbf{b}}^{g}} bgΔRij

Δ R ^ i j = Δ R ~ i j ( b ^ i g ) = ∏ k = i j − 1 Exp ⁡ ( ( ω ~ k − b ^ i g ) Δ t ) = ∏ k = i j − 1 Exp ⁡ ( ( ω ~ k − ( b ‾ i g + δ b i g ) ) Δ t ) = ∏ k = i j − 1 Exp ⁡ ( ( ω ~ k − b ‾ i g ) Δ t − δ b i g Δ t ) ≈ ( 1 ) ∏ k = i j − 1 ( Exp ⁡ ( ( ω ~ k − b ‾ i g ) Δ t ) ⋅ Exp ⁡ ( − J r k δ b i g Δ t ) ) ⏟ Exp ⁡ ( ϕ ⃗ + δ ϕ ⃗ ) ≈ Exp ⁡ ( ϕ ⃗ ) ⋅ Exp ⁡ ( J r ( ϕ ⃗ ) ⋅ δ ϕ ⃗ ) a n d Exp ⁡ ( ϕ ⃗ ) ⋅ R = R ⋅ Exp ⁡ ( R T ϕ ⃗ ) = Δ R ‾ i j ∏ k = i j − 1 Exp ⁡ ( − Δ R ‾ k + 1 j T J r k δ b i g Δ t ) \begin{aligned} \Delta \hat{\mathbf{R}}_{i j} & =\Delta \tilde{\mathbf{R}}_{i j}\left(\hat{\mathbf{b}}_{i}^{g}\right) \\ & =\prod_{k=i}^{j-1} \operatorname{Exp}\left(\left(\tilde{\mathbf{\omega}}_{k}-\hat{\mathbf{b}}_{i}^{g}\right) \Delta t\right) \\ & =\prod_{k=i}^{j-1} \operatorname{Exp}\left(\left(\tilde{\mathbf{\omega}}_{k}-\left(\overline{\mathbf{b}}_{i}^{g}+\delta \mathbf{b}_{i}^{g}\right)\right) \Delta t\right) \\ & =\prod_{k=i}^{j-1} \operatorname{Exp}\left(\left(\tilde{\mathbf{\omega}}_{k}-\overline{\mathbf{b}}_{i}^{g}\right) \Delta t-\delta \mathbf{b}_{i}^{g} \Delta t\right) \\ & \stackrel{(1)}{\approx}\underbrace{ \prod_{k=i}^{j-1}\left(\operatorname{Exp}\left(\left(\tilde{\mathbf{\omega}}_{k}-\overline{\mathbf{b}}_{i}^{g}\right) \Delta t\right) \cdot \operatorname{Exp}\left(-\mathbf{J}_{r}^{k} \delta \mathbf{b}_{i}^{g} \Delta t\right)\right)}_{\operatorname{Exp}(\vec{\phi}+\delta \vec{\phi}) \approx \operatorname{Exp}(\vec{\phi}) \cdot \operatorname{Exp}\left(\mathbf{J}_{r}(\vec{\phi}) \cdot \delta \vec{\phi}\right) and \operatorname{Exp}(\vec{\phi}) \cdot \mathbf{R} = \mathbf{R} \cdot \operatorname{Exp}\left(\mathbf{R}^{T} \vec{\phi}\right)} \\ & =\Delta \overline{\mathbf{R}}_{i j} \prod_{k=i}^{j-1} \operatorname{Exp}\left(-\Delta \overline{\mathbf{R}}_{k+1 j}^{T} \mathbf{J}_{r}^{k} \delta \mathbf{b}_{i}^{g} \Delta t\right) \end{aligned} ΔR^ij=ΔR~ij(b^ig)=k=ij1Exp((ω~kb^ig)Δt)=k=ij1Exp((ω~k(big+δbig))Δt)=k=ij1Exp((ω~kbig)ΔtδbigΔt)(1)Exp(ϕ +δϕ )Exp(ϕ )Exp(Jr(ϕ )δϕ )andExp(ϕ )R=RExp(RTϕ ) k=ij1(Exp((ω~kbig)Δt)Exp(JrkδbigΔt))=ΔRijk=ij1Exp(ΔRk+1jTJrkδbigΔt)
可以得到,
∂ Δ R ‾ i j ∂ b ‾ g = ∑ k = i j − 1 ( − Δ R ‾ k + 1 j T J r k Δ t ) \frac{\partial \Delta \overline{\mathbf{R}}_{i j}}{\partial \overline{\mathbf{b}}^{g}}=\sum_{k=i}^{j-1}\left(-\Delta \overline{\mathbf{R}}_{k+1 j}^{T} \mathbf{J}_{r}^{k} \Delta t\right) bgΔRij=k=ij1(ΔRk+1jTJrkΔt)
其中,
J r k = J r ( ( ω ~ k − b i g ) Δ t ) \mathbf{J}_{r}^{k}=\mathbf{J}_{r}\left(\left(\tilde{\boldsymbol{\omega}}_{k}-\mathbf{b}_{i}^{g}\right) \Delta t\right) Jrk=Jr((ω~kbig)Δt)

  • ∂ Δ v ‾ i j ∂ b ‾ g \frac{\partial \Delta \overline{\mathbf{v}}_{i j}}{\partial \overline{\mathbf{b}}^{g}} bgΔvij ∂ Δ v ‾ i j ∂ b ‾ a \frac{\partial \Delta \overline{\mathbf{v}}_{i j}}{\partial \overline{\mathbf{b}}^{a}} baΔvij
    Δ R ^ i j = Δ R ‾ i j Exp ⁡ ( ∑ k = i j − 1 ( − Δ R ‾ k + 1 j T J r k δ b i g Δ t ) ) \Delta \hat{\mathbf{R}}_{i j}=\Delta \overline{\mathbf{R}}_{i j} \operatorname{Exp}\left(\sum_{k=i}^{j-1}\left(-\Delta \overline{\mathbf{R}}_{k+1 j}^{T} \mathbf{J}_{r}^{k} \delta \mathbf{b}_{i}^{g} \Delta t\right)\right) ΔR^ij=ΔRijExp(k=ij1(ΔRk+1jTJrkδbigΔt))代入
    Δ v ^ i j = Δ v ~ i j ( b ^ i g , b ^ i a ) = ∑ k = i j − 1 [ Δ R ~ i k ( b ^ i g ) ⋅ ( f ~ k − b ^ i a ) Δ t ] ≈ ∑ k = i j − 1 [ Δ R ‾ i k ⋅ Exp ⁡ ( ∂ Δ R ‾ i k ∂ b ‾ g δ b i g ) ⋅ ( f ~ k − b ‾ i a − δ b i a ) Δ t ] ≈ ( 1 ) ∑ k = i j − 1 [ Δ R ‾ i k ⋅ ( I + ( ∂ Δ R ‾ i k ∂ b ‾ g δ b i g ) ∧ ) ⋅ ( f ~ k − b ‾ i a − δ b i a ) Δ t ] = ∑ k = i j − 1 [ Δ R ‾ i k ⋅ ( f ~ k − b ‾ i a ) Δ t − Δ R ‾ i k δ b i a Δ t + Δ R ‾ i k ⋅ ( ∂ Δ R ‾ i k ∂ b ‾ g δ b i g ) ∧ ( f ~ k − b ‾ i a ) Δ t − Δ R ‾ i k ⋅ ( ∂ Δ R ‾ i k ∂ b ‾ g δ b i g ) ∧ δ b i a Δ t ] ≈ ( 2 ) Δ v ‾ i j + ∑ k = i j − 1 { − [ Δ R ‾ i k Δ t ] δ b i a − [ Δ R ‾ i k ⋅ ( f ~ k − b ‾ i a ) ∧ ∂ Δ R ‾ i k ∂ b ‾ g Δ t ] δ b i g } \begin{array}{l} \Delta \hat{\mathbf{v}}_{i j}=\Delta \tilde{\mathbf{v}}_{i j}\left(\hat{\mathbf{b}}_{i}^{g}, \hat{\mathbf{b}}_{i}^{a}\right) \\ =\sum_{k=i}^{j-1}\left[\Delta \tilde{\mathbf{R}}_{i k}\left(\hat{\mathbf{b}}_{i}^{g}\right) \cdot\left(\tilde{\mathbf{f}}_{k}-\hat{\mathbf{b}}_{i}^{a}\right) \Delta t\right] \\ \approx \sum_{k=i}^{j-1}\left[\Delta \overline{\mathbf{R}}_{i k} \cdot \operatorname{Exp}\left(\frac{\partial \Delta \overline{\mathbf{R}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \delta \mathbf{b}_{i}^{g}\right) \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}-\delta \mathbf{b}_{i}^{a}\right) \Delta t\right] \\ \stackrel{(1)}{\approx} \sum_{k=i}^{j-1}\left[\Delta \overline{\mathbf{R}}_{i k} \cdot\left(\mathbf{I}+\left(\frac{\partial \Delta \overline{\mathbf{R}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \delta \mathbf{b}_{i}^{g}\right)^{\wedge}\right) \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}-\delta \mathbf{b}_{i}^{a}\right) \Delta t\right] \\ =\sum_{k=i}^{j-1}\left[\Delta \overline{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}\right) \Delta t-\Delta \overline{\mathbf{R}}_{i k} \delta \mathbf{b}_{i}^{a} \Delta t+\Delta \overline{\mathbf{R}}_{i k} \cdot\left(\frac{\partial \Delta \overline{\mathbf{R}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \delta \mathbf{b}_{i}^{g}\right)^{\wedge}\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}\right) \Delta t-\Delta \overline{\mathbf{R}}_{i k} \cdot\left(\frac{\partial \Delta \overline{\mathbf{R}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \delta \mathbf{b}_{i}^{g}\right)^{\wedge} \delta \mathbf{b}_{i}^{a} \Delta t\right] \\ \stackrel{(2)}{\approx} \Delta \overline{\mathbf{v}}_{i j}+\sum_{k=i}^{j-1}\left\{-\left[\Delta \overline{\mathbf{R}}_{i k} \Delta t\right] \delta \mathbf{b}_{i}^{a}-\left[\Delta \overline{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}\right)^{\wedge} \frac{\partial \Delta \overline{\mathbf{R}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \Delta t\right] \delta \mathbf{b}_{i}^{g}\right\} \\ \end{array} Δv^ij=Δv~ij(b^ig,b^ia)=k=ij1[ΔR~ik(b^ig)(f~kb^ia)Δt]k=ij1[ΔRikExp(bgΔRikδbig)(f~kbiaδbia)Δt](1)k=ij1[ΔRik(I+(bgΔRikδbig))(f~kbiaδbia)Δt]=k=ij1[ΔRik(f~kbia)ΔtΔRikδbiaΔt+ΔRik(bgΔRikδbig)(f~kbia)ΔtΔRik(bgΔRikδbig)δbiaΔt](2)Δvij+k=ij1{[ΔRikΔt]δbia[ΔRik(f~kbia)bgΔRikΔt]δbig}
    可以得到
    ∂ Δ v ‾ i j ∂ b ‾ g = − ∑ k = i j − 1 ( Δ R ‾ i k ⋅ ( f ~ k − b ‾ i a ) ∧ ∂ Δ R ‾ i k ∂ b ‾ g Δ t ) ∂ Δ v ‾ i j ∂ b ‾ a = − ∑ k = i j − 1 ( Δ R ‾ i k Δ t ) \begin{aligned} \frac{\partial \Delta \overline{\mathbf{v}}_{i j}}{\partial \overline{\mathbf{b}}^{g}} & =-\sum_{k=i}^{j-1}\left(\Delta \overline{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}\right)^{\wedge} \frac{\partial \Delta \overline{\mathbf{R}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \Delta t\right) \\ \frac{\partial \Delta \overline{\mathbf{v}}_{i j}}{\partial \overline{\mathbf{b}}^{a}} & =-\sum_{k=i}^{j-1}\left(\Delta \overline{\mathbf{R}}_{i k} \Delta t\right) \end{aligned} bgΔvijbaΔvij=k=ij1(ΔRik(f~kbia)bgΔRikΔt)=k=ij1(ΔRikΔt)
  • ∂ Δ p ‾ i j ∂ b ‾ g \frac{\partial \Delta \overline{\mathbf{p}}_{i j}}{\partial \overline{\mathbf{b}}^{g}} bgΔpij ∂ Δ p ‾ i j ∂ b ‾ a \frac{\partial \Delta \overline{\mathbf{p}}_{i j}}{\partial \overline{\mathbf{b}}^{a}} baΔpij
    Δ p ^ i j = Δ p ~ i j ( b ^ i g , b ^ i a ) = ∑ k = i j − 1 [ Δ v ~ i k ( b ^ i g , b ^ i a ) Δ t + 1 2 Δ R ~ i k ( b ^ i g ) ⋅ ( f ~ k − b ^ i a ) Δ t 2 ] = ∑ k = i j − 1 [ Δ v ~ i k ( b ^ i g , b ^ i a ) Δ t ] ⏟ 1 + 1 2 ∑ k = i j − 1 [ Δ R ~ i k ( b ^ i g ) ⋅ ( f ~ k − b ^ i a ) Δ t 2 ] ⏟ 2 \begin{aligned} \Delta \hat{\mathbf{p}}_{i j} & =\Delta \tilde{\mathbf{p}}_{i j}\left(\hat{\mathbf{b}}_{i}^{g}, \hat{\mathbf{b}}_{i}^{a}\right) \\ & =\sum_{k=i}^{j-1}\left[\Delta \tilde{\mathbf{v}}_{i k}\left(\hat{\mathbf{b}}_{i}^{g}, \hat{\mathbf{b}}_{i}^{a}\right) \Delta t+\frac{1}{2} \Delta \tilde{\mathbf{R}}_{i k}\left(\hat{\mathbf{b}}_{i}^{g}\right) \cdot\left(\tilde{\mathbf{f}}_{k}-\hat{\mathbf{b}}_{i}^{a}\right) \Delta t^{2}\right] \\ & =\underbrace{\sum_{k=i}^{j-1}\left[\Delta \tilde{\mathbf{v}}_{i k}\left(\hat{\mathbf{b}}_{i}^{g}, \hat{\mathbf{b}}_{i}^{a}\right) \Delta t\right]}_{1}+\underbrace{\frac{1}{2} \sum_{k=i}^{j-1}\left[\Delta \tilde{\mathbf{R}}_{i k}\left(\hat{\mathbf{b}}_{i}^{g}\right) \cdot\left(\tilde{\mathbf{f}}_{k}-\hat{\mathbf{b}}_{i}^{a}\right) \Delta t^{2}\right]}_{2} \end{aligned} Δp^ij=Δp~ij(b^ig,b^ia)=k=ij1[Δv~ik(b^ig,b^ia)Δt+21ΔR~ik(b^ig)(f~kb^ia)Δt2]=1 k=ij1[Δv~ik(b^ig,b^ia)Δt]+2 21k=ij1[ΔR~ik(b^ig)(f~kb^ia)Δt2]
    对于12分别推导:
    ( 1 ) = ∑ k = i j − 1 [ ( Δ v ‾ i k + ∂ Δ v ‾ i k ∂ b ‾ g δ b i g + ∂ Δ v ‾ i k ∂ b ‾ a δ b i a ) Δ t ] = ∑ k = i j − 1 [ Δ v ‾ i k Δ t + ( ∂ Δ v ‾ i k ∂ b ‾ g Δ t ) δ b i g + ( ∂ Δ v ‾ i k ∂ b ‾ a Δ t ) δ b i a ] \begin{aligned} (1) & =\sum_{k=i}^{j-1}\left[\left(\Delta \overline{\mathbf{v}}_{i k}+\frac{\partial \Delta \overline{\mathbf{v}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \delta \mathbf{b}_{i}^{g}+\frac{\partial \Delta \overline{\mathbf{v}}_{i k}}{\partial \overline{\mathbf{b}}^{a}} \delta \mathbf{b}_{i}^{a}\right) \Delta t\right] \\ & =\sum_{k=i}^{j-1}\left[\Delta \overline{\mathbf{v}}_{i k} \Delta t+\left(\frac{\partial \Delta \overline{\mathbf{v}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \Delta t\right) \delta \mathbf{b}_{i}^{g}+\left(\frac{\partial \Delta \overline{\mathbf{v}}_{i k}}{\partial \overline{\mathbf{b}}^{a}} \Delta t\right) \delta \mathbf{b}_{i}^{a}\right] \end{aligned} (1)=k=ij1[(Δvik+bgΔvikδbig+baΔvikδbia)Δt]=k=ij1[ΔvikΔt+(bgΔvikΔt)δbig+(baΔvikΔt)δbia]
    ( 2 ) ≈ Δ t 2 2 ∑ k = i j − 1 [ Δ R ~ i k ( b ^ i g ) ⋅ ( f ~ k − b ^ i a ) ] = Δ t 2 2 ∑ k = i j − 1 [ Δ R ‾ i k ⋅ Exp ⁡ ( ∂ Δ R ‾ i k ∂ b ‾ g δ b i g ) ⋅ ( f ~ k − b ‾ i a − δ b i a ) ] ≈ Δ t 2 2 ∑ k = i j − 1 [ Δ R ‾ i k ⋅ ( I + ( ∂ Δ R ‾ i k ∂ b ‾ g δ b i g ) ∧ ) ⋅ ( f ~ k − b ‾ i a − δ b i a ) ] ≈ Δ t 2 2 ∑ k = i j − 1 [ Δ R ‾ i k ⋅ ( f ~ k − b ‾ i a ) − Δ R ‾ i k δ b i a − Δ R ‾ i k ⋅ ( f ~ k − b ‾ i a ) ∧ ∂ Δ R ‾ i k ∂ b ‾ g δ b i g ] \begin{aligned} (2) & \approx \frac{\Delta t^{2}}{2} \sum_{k=i}^{j-1}\left[\Delta \tilde{\mathbf{R}}_{i k}\left(\hat{\mathbf{b}}_{i}^{g}\right) \cdot\left(\tilde{\mathbf{f}}_{k}-\hat{\mathbf{b}}_{i}^{a}\right)\right] \\ & =\frac{\Delta t^{2}}{2} \sum_{k=i}^{j-1}\left[\Delta \overline{\mathbf{R}}_{i k} \cdot \operatorname{Exp}\left(\frac{\partial \Delta \overline{\mathbf{R}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \delta \mathbf{b}_{i}^{g}\right) \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}-\delta \mathbf{b}_{i}^{a}\right)\right] \\ & \approx \frac{\Delta t^{2}}{2} \sum_{k=i}^{j-1}\left[\Delta \overline{\mathbf{R}}_{i k} \cdot\left(\mathbf{I}+\left(\frac{\partial \Delta \overline{\mathbf{R}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \delta \mathbf{b}_{i}^{g}\right)^{\wedge}\right) \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}-\delta \mathbf{b}_{i}^{a}\right)\right] \\ & \approx \frac{\Delta t^{2}}{2} \sum_{k=i}^{j-1}\left[\Delta \overline{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}\right)-\Delta \overline{\mathbf{R}}_{i k} \delta \mathbf{b}_{i}^{a}-\Delta \overline{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}\right)^{\wedge} \frac{\partial \Delta \overline{\mathbf{R}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \delta \mathbf{b}_{i}^{g}\right] \end{aligned} (2)2Δt2k=ij1[ΔR~ik(b^ig)(f~kb^ia)]=2Δt2k=ij1[ΔRikExp(bgΔRikδbig)(f~kbiaδbia)]2Δt2k=ij1[ΔRik(I+(bgΔRikδbig))(f~kbiaδbia)]2Δt2k=ij1[ΔRik(f~kbia)ΔRikδbiaΔRik(f~kbia)bgΔRikδbig]
    12组合:
    Δ p ^ i j = ∑ k = i j − 1 { [ Δ v ‾ i k Δ t + 1 2 Δ R ‾ i k ⋅ ( f ~ k − b ‾ i a ) Δ t 2 ] + [ ∂ Δ v ‾ i k ∂ b ‾ g Δ t − 1 2 Δ R ‾ i k ⋅ ( f ~ k − b ‾ i a ) ∧ ∂ Δ R ‾ i k ∂ b ‾ g Δ t 2 ] δ b i g + [ ∂ Δ v ‾ i k ∂ b ‾ a Δ t − 1 2 Δ R ‾ i k Δ t 2 ] δ b i a } = Δ p ‾ i j + { ∑ k = i j − 1 [ ∂ Δ v ‾ i k ∂ b ‾ g Δ t − 1 2 Δ R ‾ i k ⋅ ( f ~ k − b ‾ i a ) ∧ ∂ Δ R ‾ i k ∂ b ‾ g Δ t 2 ] } δ b i g + { ∑ k = i j − 1 [ ∂ Δ v ‾ i k ∂ b ‾ a Δ t − 1 2 Δ R ‾ i k Δ t 2 ] } δ b i a \begin{array}{l} \Delta \hat{\mathbf{p}}_{i j} =\sum_{k=i}^{j-1}\left\{\left[\Delta \overline{\mathbf{v}}_{i k} \Delta t+\frac{1}{2} \Delta \overline{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}\right) \Delta t^{2}\right]+\left[\frac{\partial \Delta \overline{\mathbf{v}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \Delta t-\frac{1}{2} \Delta \overline{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}\right)^{\wedge} \frac{\partial \Delta \overline{\mathbf{R}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \Delta t^{2}\right] \delta \mathbf{b}_{i}^{g}+\left[\frac{\partial \Delta \overline{\mathbf{v}}_{i k}}{\partial \overline{\mathbf{b}}^{a}} \Delta t-\frac{1}{2} \Delta \overline{\mathbf{R}}_{i k} \Delta t^{2}\right] \delta \mathbf{b}_{i}^{a}\right\} \\ =\Delta \overline{\mathbf{p}}_{i j}+\left\{\sum_{k=i}^{j-1}\left[\frac{\partial \Delta \overline{\mathbf{v}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \Delta t-\frac{1}{2} \Delta \overline{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}\right)^{\wedge} \frac{\partial \Delta \overline{\mathbf{R}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \Delta t^{2}\right]\right\} \delta \mathbf{b}_{i}^{g}+\left\{\sum_{k=i}^{j-1}\left[\frac{\partial \Delta \overline{\mathbf{v}}_{i k}}{\partial \overline{\mathbf{b}}^{a}} \Delta t-\frac{1}{2} \Delta \overline{\mathbf{R}}_{i k} \Delta t^{2}\right]\right\} \delta \mathbf{b}_{i}^{a} \end{array} Δp^ij=k=ij1{[ΔvikΔt+21ΔRik(f~kbia)Δt2]+[bgΔvikΔt21ΔRik(f~kbia)bgΔRikΔt2]δbig+[baΔvikΔt21ΔRikΔt2]δbia}=Δpij+{k=ij1[bgΔvikΔt21ΔRik(f~kbia)bgΔRikΔt2]}δbig+{k=ij1[baΔvikΔt21ΔRikΔt2]}δbia
    得到
    ∂ Δ p ‾ i j ∂ b ‾ g = ∑ k = i j − 1 [ ∂ Δ v ‾ i k ∂ b ‾ g Δ t − 1 2 Δ R ‾ i k ⋅ ( f ~ k − b ‾ i a ) ∧ ∂ Δ R ‾ i k ∂ b ‾ g Δ t 2 ] ∂ Δ p ‾ i j ∂ b ‾ a = ∑ k = i j − 1 [ ∂ Δ v ‾ i k ∂ b ‾ a Δ t − 1 2 Δ R ‾ i k Δ t 2 ] \begin{aligned} \frac{\partial \Delta \overline{\mathbf{p}}_{i j}}{\partial \overline{\mathbf{b}}^{g}} & =\sum_{k=i}^{j-1}\left[\frac{\partial \Delta \overline{\mathbf{v}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \Delta t-\frac{1}{2} \Delta \overline{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}\right)^{\wedge} \frac{\partial \Delta \overline{\mathbf{R}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \Delta t^{2}\right] \\ \frac{\partial \Delta \overline{\mathbf{p}}_{i j}}{\partial \overline{\mathbf{b}}^{a}} & =\sum_{k=i}^{j-1}\left[\frac{\partial \Delta \overline{\mathbf{v}}_{i k}}{\partial \overline{\mathbf{b}}^{a}} \Delta t-\frac{1}{2} \Delta \overline{\mathbf{R}}_{i k} \Delta t^{2}\right] \end{aligned} bgΔpijbaΔpij=k=ij1[bgΔvikΔt21ΔRik(f~kbia)bgΔRikΔt2]=k=ij1[baΔvikΔt21ΔRikΔt2]

Jacobian更新

  • ∂ Δ v ‾ i j − 1 ∂ b ‾ g → ∂ Δ v ‾ i j ∂ b ‾ g \frac{\partial \Delta \overline{\mathbf{v}}_{i j-1}}{\partial \overline{\mathbf{b}}^{g}} \to \frac{\partial \Delta \overline{\mathbf{v}}_{i j}}{\partial \overline{\mathbf{b}}^{g}} bgΔvij1bgΔvij
    ∂ Δ v ‾ i j ∂ b ‾ g = − ∑ k = i j − 1 ( Δ R ‾ i k ⋅ ( f ~ k − b ‾ i a ) ∧ ∂ Δ R ‾ i k ∂ b ‾ g Δ t ) = − ∑ k = i j − 2 ( Δ R ‾ i k ⋅ ( f ~ k − b ‾ i a ) ∧ ∂ Δ R ‾ i k ∂ b ‾ g Δ t ) − Δ R ‾ i j − 1 ⋅ ( f ~ j − 1 − b ‾ i a ) ∧ ∂ Δ R ‾ i j − 1 ∂ b ‾ g Δ t = ∂ Δ v ‾ i j − 1 ∂ b ‾ g − Δ R ‾ i j − 1 ⋅ ( f ~ j − 1 − b ‾ i a ) ∧ ∂ Δ R ‾ i j − 1 ∂ b ‾ g Δ t \begin{array}{l} \frac{\partial \Delta \overline{\mathbf{v}}_{i j}}{\partial \overline{\mathbf{b}}^{g}} =-\sum_{k=i}^{j-1}\left(\Delta \overline{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}\right)^{\wedge} \frac{\partial \Delta \overline{\mathbf{R}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \Delta t\right) \\ =-\sum_{k=i}^{j-2}\left(\Delta \overline{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}\right)^{\wedge} \frac{\partial \Delta \overline{\mathbf{R}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \Delta t\right) - \Delta \overline{\mathbf{R}}_{i j-1} \cdot\left(\tilde{\mathbf{f}}_{j-1}-\overline{\mathbf{b}}_{i}^{a}\right)^{\wedge} \frac{\partial \Delta \overline{\mathbf{R}}_{i j-1}}{\partial \overline{\mathbf{b}}^{g}} \Delta t \\ = \frac{\partial \Delta \overline{\mathbf{v}}_{i j-1}}{\partial \overline{\mathbf{b}}^{g}}-{\color{Green} \Delta \overline{\mathbf{R}}_{i j-1}} \cdot\left(\tilde{\mathbf{f}}_{j-1}-\overline{\mathbf{b}}_{i}^{a}\right)^{\wedge} {\color{Yellow} \frac{\partial \Delta \overline{\mathbf{R}}_{i j-1}}{\partial \overline{\mathbf{b}}^{g}}} \Delta t \end{array} bgΔvij=k=ij1(ΔRik(f~kbia)bgΔRikΔt)=k=ij2(ΔRik(f~kbia)bgΔRikΔt)ΔRij1(f~j1bia)bgΔRij1Δt=bgΔvij1ΔRij1(f~j1bia)bgΔRij1Δt
  • ∂ Δ v ‾ i j − 1 ∂ b ‾ a → ∂ Δ v ‾ i j ∂ b ‾ a \frac{\partial \Delta \overline{\mathbf{v}}_{i j-1}}{\partial \overline{\mathbf{b}}^{a}} \to \frac{\partial \Delta \overline{\mathbf{v}}_{i j}}{\partial \overline{\mathbf{b}}^{a}} baΔvij1baΔvij

∂ Δ v ‾ i j ∂ b ‾ a = − ∑ k = i j − 1 ( Δ R ‾ i k Δ t ) = − ∑ k = i j − 2 ( Δ R ‾ i k Δ t ) − Δ R ‾ i j − 1 Δ t = ∂ Δ v ‾ i j − 1 ∂ b ‾ a − Δ R ‾ i j − 1 Δ t \begin{array}{l} \frac{\partial \Delta \overline{\mathbf{v}}_{i j}}{\partial \overline{\mathbf{b}}^{a}} =-\sum_{k=i}^{j-1}\left(\Delta \overline{\mathbf{R}}_{i k} \Delta t\right) \\ =-\sum_{k=i}^{j-2}\left(\Delta \overline{\mathbf{R}}_{i k} \Delta t\right)-\Delta \overline{\mathbf{R}}_{i j-1} \Delta t \\ =\frac{\partial \Delta \overline{\mathbf{v}}_{i j-1}}{\partial \overline{\mathbf{b}}^{a}} -{\color{Green} \Delta \overline{\mathbf{R}}_{i j-1} } \Delta t \end{array} baΔvij=k=ij1(ΔRikΔt)=k=ij2(ΔRikΔt)ΔRij1Δt=baΔvij1ΔRij1Δt

  • ∂ Δ p ‾ i j − 1 ∂ b ‾ g → ∂ Δ p ‾ i j ∂ b ‾ g \frac{\partial \Delta \overline{\mathbf{p}}_{i j-1}}{\partial \overline{\mathbf{b}}^{g}} \to \frac{\partial \Delta \overline{\mathbf{p}}_{i j}}{\partial \overline{\mathbf{b}}^{g}} bgΔpij1bgΔpij

∂ Δ p ‾ i j ∂ b ‾ g = ∑ k = i j − 1 [ ∂ Δ v ‾ i k ∂ b ‾ g Δ t − 1 2 Δ R ‾ i k ⋅ ( f ~ k − b ‾ i a ) ∧ ∂ Δ R ‾ i k ∂ b ‾ g Δ t 2 ] = ∑ k = i j − 2 [ ∂ Δ v ‾ i k ∂ b ‾ g Δ t − 1 2 Δ R ‾ i k ⋅ ( f ~ k − b ‾ i a ) ∧ ∂ Δ R ‾ i k ∂ b ‾ g Δ t 2 ] + ∂ Δ v ‾ i j − 1 ∂ b ‾ g Δ t − 1 2 Δ R ‾ i j − 1 ⋅ ( f ~ j − 1 − b ‾ i a ) ∧ ∂ Δ R ‾ i j − 1 ∂ b ‾ g Δ t 2 = ∂ Δ p ‾ i j − 1 ∂ b ‾ g + ∂ Δ v ‾ i j − 1 ∂ b ‾ g Δ t − 1 2 Δ R ‾ i j − 1 ⋅ ( f ~ j − 1 − b ‾ i a ) ∧ ∂ Δ R ‾ i j − 1 ∂ b ‾ g Δ t 2 \begin{array}{l} \frac{\partial \Delta \overline{\mathbf{p}}_{i j}}{\partial \overline{\mathbf{b}}^{g}} =\sum_{k=i}^{j-1}\left[\frac{\partial \Delta \overline{\mathbf{v}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \Delta t-\frac{1}{2} \Delta \overline{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}\right)^{\wedge} \frac{\partial \Delta \overline{\mathbf{R}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \Delta t^{2}\right] \\ =\sum_{k=i}^{j-2}\left[\frac{\partial \Delta \overline{\mathbf{v}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \Delta t-\frac{1}{2} \Delta \overline{\mathbf{R}}_{i k} \cdot\left(\tilde{\mathbf{f}}_{k}-\overline{\mathbf{b}}_{i}^{a}\right)^{\wedge} \frac{\partial \Delta \overline{\mathbf{R}}_{i k}}{\partial \overline{\mathbf{b}}^{g}} \Delta t^{2}\right] + {\color{Red} \frac{\partial \Delta \overline{\mathbf{v}}_{i j-1}}{\partial \overline{\mathbf{b}}^{g}}} \Delta t-\frac{1}{2} {\color{Green} \Delta \overline{\mathbf{R}}_{i j-1}} \cdot\left(\tilde{\mathbf{f}}_{j-1}-\overline{\mathbf{b}}_{i}^{a}\right)^{\wedge} {\color{Yellow} \frac{\partial \Delta \overline{\mathbf{R}}_{i j-1}}{\partial \overline{\mathbf{b}}^{g}} } \Delta t^{2} \\ =\frac{\partial \Delta \overline{\mathbf{p}}_{i j-1}}{\partial \overline{\mathbf{b}}^{g}} + {\color{Red} \frac{\partial \Delta \overline{\mathbf{v}}_{i j-1}}{\partial \overline{\mathbf{b}}^{g}}} \Delta t-\frac{1}{2} {\color{Green} \Delta \overline{\mathbf{R}}_{i j-1}} \cdot\left(\tilde{\mathbf{f}}_{j-1}-\overline{\mathbf{b}}_{i}^{a}\right)^{\wedge} {\color{Yellow} \frac{\partial \Delta \overline{\mathbf{R}}_{i j-1}}{\partial \overline{\mathbf{b}}^{g}} } \Delta t^{2} \end{array} bgΔpij=k=ij1[bgΔvikΔt21ΔRik(f~kbia)bgΔRikΔt2]=k=ij2[bgΔvikΔt21ΔRik(f~kbia)bgΔRikΔt2]+bgΔvij1Δt21ΔRij1(f~j1bia)bgΔRij1Δt2=bgΔpij1+bgΔvij1Δt21ΔRij1(f~j1bia)bgΔRij1Δt2

  • ∂ Δ p ‾ i j − 1 ∂ b ‾ a → ∂ Δ p ‾ i j ∂ b ‾ a \frac{\partial \Delta \overline{\mathbf{p}}_{i j-1}}{\partial \overline{\mathbf{b}}^{a}} \to \frac{\partial \Delta \overline{\mathbf{p}}_{i j}}{\partial \overline{\mathbf{b}}^{a}} baΔpij1baΔpij

∂ Δ p ‾ i j ∂ b ‾ a = ∑ k = i j − 1 [ ∂ Δ v ‾ i k ∂ b ‾ a Δ t − 1 2 Δ R ‾ i k Δ t 2 ] = ∑ k = i j − 2 [ ∂ Δ v ‾ i k ∂ b ‾ a Δ t − 1 2 Δ R ‾ i k Δ t 2 ] + ∂ Δ v ‾ i j − 1 ∂ b ‾ a Δ t − 1 2 Δ R ‾ i j − 1 Δ t 2 = ∂ Δ p ‾ i j − 1 ∂ b ‾ a + ∂ Δ v ‾ i j − 1 ∂ b ‾ a Δ t − 1 2 Δ R ‾ i j − 1 Δ t 2 \begin{array}{l} \frac{\partial \Delta \overline{\mathbf{p}}_{i j}}{\partial \overline{\mathbf{b}}^{a}} =\sum_{k=i}^{j-1}\left[\frac{\partial \Delta \overline{\mathbf{v}}_{i k}}{\partial \overline{\mathbf{b}}^{a}} \Delta t-\frac{1}{2} \Delta \overline{\mathbf{R}}_{i k} \Delta t^{2}\right] \\ =\sum_{k=i}^{j-2}\left[\frac{\partial \Delta \overline{\mathbf{v}}_{i k}}{\partial \overline{\mathbf{b}}^{a}} \Delta t-\frac{1}{2} \Delta \overline{\mathbf{R}}_{i k} \Delta t^{2}\right] + {\color{Red} \frac{\partial \Delta \overline{\mathbf{v}}_{i j-1}}{\partial \overline{\mathbf{b}}^{a}}} \Delta t-\frac{1}{2} {\color{Green} \Delta \overline{\mathbf{R}}_{i j-1} } \Delta t^{2} \\ =\frac{\partial \Delta \overline{\mathbf{p}}_{i j-1}}{\partial \overline{\mathbf{b}}^{a}} + {\color{Red} \frac{\partial \Delta \overline{\mathbf{v}}_{i j-1}}{\partial \overline{\mathbf{b}}^{a}}} \Delta t-\frac{1}{2} {\color{Green} \Delta \overline{\mathbf{R}}_{i j-1} } \Delta t^{2} \end{array} baΔpij=k=ij1[baΔvikΔt21ΔRikΔt2]=k=ij2[baΔvikΔt21ΔRikΔt2]+baΔvij1Δt21ΔRij1Δt2=baΔpij1+baΔvij1Δt21ΔRij1Δt2

  • ∂ Δ R ‾ i j − 1 ∂ b ‾ g → ∂ Δ R ‾ i j ∂ b ‾ g \frac{\partial \Delta \overline{\mathbf{R}}_{i j-1}}{\partial \overline{\mathbf{b}}^{g}} \to \frac{\partial \Delta \overline{\mathbf{R}}_{i j}}{\partial \overline{\mathbf{b}}^{g}} bgΔRij1bgΔRij

∂ Δ R ‾ i j ∂ b ‾ g = ∑ k = i j − 1 ( − Δ R ‾ k + 1 j T J r k Δ t ) = ∑ k = i j − 2 ( − Δ R ‾ k + 1 j T J r k Δ t ) − Δ R ‾ j j T J r k Δ t = ∑ k = i j − 2 ( − ( Δ R ‾ k + 1 j − 1 Δ R ‾ j − 1 j ) T J r k Δ t ) − Δ R ‾ j j T J r k Δ t = − Δ R ‾ j − 1 j T ⋅ ∑ k = i j − 2 ( Δ R ‾ k + 1 j − 1 T J r k Δ t ) − Δ R ‾ j j T J r k Δ t = − Δ R ‾ j − 1 j T ⋅ ∂ Δ R ‾ i j − 1 ∂ b ‾ g − Δ R ‾ j j T ⏟ I J r k Δ t \begin{array}{l} \frac{\partial \Delta \overline{\mathbf{R}}_{i j}}{\partial \overline{\mathbf{b}}^{g}}=\sum_{k=i}^{j-1}\left(-\Delta \overline{\mathbf{R}}_{k+1 j}^{T} \mathbf{J}_{r}^{k} \Delta t\right) \\ =\sum_{k=i}^{j-2}\left(-\Delta \overline{\mathbf{R}}_{k+1 j}^{T} \mathbf{J}_{r}^{k} \Delta t\right) -\Delta \overline{\mathbf{R}}_{j j}^{T} \mathbf{J}_{r}^{k} \Delta t \\ =\sum_{k=i}^{j-2}\left(-\left(\Delta \overline{\mathbf{R}}_{k+1 j-1}\Delta \overline{\mathbf{R}}_{j-1 j} \right)^{T}\mathbf{J}_{r}^{k} \Delta t\right) -\Delta \overline{\mathbf{R}}_{j j}^{T} \mathbf{J}_{r}^{k} \Delta t \\ =-\Delta \overline{\mathbf{R}}_{ j-1 j}^{T}\cdot \sum_{k=i}^{j-2}\left(\Delta \overline{\mathbf{R}}_{k+1 j-1}^{T} \mathbf{J}_{r}^{k} \Delta t\right) -\Delta \overline{\mathbf{R}}_{j j}^{T} \mathbf{J}_{r}^{k} \Delta t \\ = -\Delta \overline{\mathbf{R}}_{ j-1 j}^{T}\cdot \frac{\partial \Delta \overline{\mathbf{R}}_{i j-1}}{\partial \overline{\mathbf{b}}^{g}} -\underbrace{\Delta \overline{\mathbf{R}}_{j j}^{T}}_{I} \mathbf{J}_{r}^{k} \Delta t \end{array} bgΔRij=k=ij1(ΔRk+1jTJrkΔt)=k=ij2(ΔRk+1jTJrkΔt)ΔRjjTJrkΔt=k=ij2((ΔRk+1j1ΔRj1j)TJrkΔt)ΔRjjTJrkΔt=ΔRj1jTk=ij2(ΔRk+1j1TJrkΔt)ΔRjjTJrkΔt=ΔRj1jTbgΔRij1I ΔRjjTJrkΔt

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题库来源:安全生产模拟考试一点通公众号小程序 2024年流动式起重机司机证模拟考试题库及流动式起重机司机理论考试试题是由安全生产模拟考试一点通提供,流动式起重机司机证模拟考试题库是根据流动式起重机司机最新版教材,流动式起重机司机大纲整理而成(含2024年流动式起重机司机证模拟考试题库及流动式起重机司机理论考试试题参考答案和部分工种参考解析),掌握本资料和学校方法,考试容易。流动式起重机司机考试技

poj3468(线段树成段更新模板题)

题意:包括两个操作:1、将[a.b]上的数字加上v;2、查询区间[a,b]上的和 下面的介绍是下解题思路: 首先介绍  lazy-tag思想:用一个变量记录每一个线段树节点的变化值,当这部分线段的一致性被破坏我们就将这个变化值传递给子区间,大大增加了线段树的效率。 比如现在需要对[a,b]区间值进行加c操作,那么就从根节点[1,n]开始调用update函数进行操作,如果刚好执行到一个子节点,

hdu1394(线段树点更新的应用)

题意:求一个序列经过一定的操作得到的序列的最小逆序数 这题会用到逆序数的一个性质,在0到n-1这些数字组成的乱序排列,将第一个数字A移到最后一位,得到的逆序数为res-a+(n-a-1) 知道上面的知识点后,可以用暴力来解 代码如下: #include<iostream>#include<algorithm>#include<cstring>#include<stack>#in

hdu1689(线段树成段更新)

两种操作:1、set区间[a,b]上数字为v;2、查询[ 1 , n ]上的sum 代码如下: #include<iostream>#include<algorithm>#include<cstring>#include<stack>#include<queue>#include<set>#include<map>#include<stdio.h>#include<stdl

uva 10014 Simple calculations(数学推导)

直接按照题意来推导最后的结果就行了。 开始的时候只做到了第一个推导,第二次没有继续下去。 代码: #include<stdio.h>int main(){int T, n, i;double a, aa, sum, temp, ans;scanf("%d", &T);while(T--){scanf("%d", &n);scanf("%lf", &first);scanf

hdu 1754 I Hate It(线段树,单点更新,区间最值)

题意是求一个线段中的最大数。 线段树的模板题,试用了一下交大的模板。效率有点略低。 代码: #include <stdio.h>#include <string.h>#define TREE_SIZE (1 << (20))//const int TREE_SIZE = 200000 + 10;int max(int a, int b){return a > b ? a :