[AMR] Finish W3 summary

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2026-03-16 13:17:23 +01:00
parent 66256e3427
commit b2941c45a6
9 changed files with 127 additions and 7 deletions
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@@ -2,13 +2,13 @@
\begin{wrapfigure}[10]{r}{0.4\columnwidth} \begin{wrapfigure}[10]{r}{0.4\columnwidth}
\includegraphics[width=0.4\columnwidth]{assets/inverse-kinematics.png} \includegraphics[width=0.4\columnwidth]{assets/inverse-kinematics.png}
\end{wrapfigure} \end{wrapfigure}
Option: Solve Forward Kinematics for angles.\\ \bi{Option}: Solve Forward Kinematics for angles.\\
Better: Law of cosine with polar coordinates. Compute angle using cosine rule,\\ \bi{Better}: Law of cosine with polar coordinates. Compute angle using cosine rule,\\
$\theta_1 = \phi \pm \alpha$, $\theta_2 = \pm(\pi - \beta)$ $\theta_1 = \phi \pm \alpha$, $\theta_2 = \pm(\pi - \beta)$
(Positive for {\color{ForestGreen} Elbow Down}, Negative for {\color{red} Elbow Up}) (Positive for {\color{ForestGreen} Elbow Down}, Negative for {\color{red} Elbow Up})
Extension to 6R: \bi{Extension to 6R}:
1. Waist: spherical coords (2 sol.)\\ 1. Waist: spherical coords (2 sol.)\\
2. 2 sols from 2R for shoulder + elbow\\ 2. 2 sols from 2R for shoulder + elbow\\
3. Solve for wrist joints (no influence on pos) 3. Solve for wrist joints (no influence on pos)
@@ -1,18 +1,23 @@
\subsection{Temporal Models} \subsection{Temporal Models}
Often use cont-time n.-lin. system of ODE $\dot{\vec{x}} = \vec{f}_C(\vec{x}(t), \vec{u}(t))$, with measurements $\vec{z}(t) = \vec{h}(\vec{x}(t)) + \vec{v}(t)$. For \bi{Cont-time n.-lin. system of ODE} $\dot{\vec{x}} = \vec{f}_C(\vec{x}(t), \vec{u}(t))$, with measurements $\vec{z}(t) = \vec{h}(\vec{x}(t)) + \vec{v}(t)$.\\
Need linearised (around $\vec{f}_C(\vec{\overline{x}}, \vec{\overline{y}}) = 0$, at \bi{equilibrium}):\\ Need linearised (around $\vec{f}_C(\vec{\overline{x}}, \vec{\overline{y}}) = 0$, at \bi{equilibrium}):\\
$\delta \vec{\dot{x}}(t) = \vec{f}_C(\vec{\overline{x}}, \vec{\overline{u}}) + \mat{F}_C \delta \vec{x}(t) + \mat{G}_C \delta \vec{u}(t) + \mat{L}_C \vec{w}(t)$\\ $\delta \vec{\dot{x}}(t) = \vec{f}_C(\vec{\overline{x}}, \vec{\overline{u}}) + \mat{F}_C \delta \vec{x}(t) + \mat{G}_C \delta \vec{u}(t) + \mat{L}_C \vec{w}(t)$\\
$\delta \vec{z}(t) = \mat{H} \delta \vec{x}(t) + \vec{v}(t)$. $\delta \vec{z}(t) = \mat{H} \delta \vec{x}(t) + \vec{v}(t)$.
Herein, $\mat{H}$ is measurements, $\mat{F}_C$ system, $\mat{G}$ input gain, $\vec{w}$ process noise, $\vec{v}$ measurement noise, both zero-mean \bi{Gaussian White Noise Process}. Herein, $\mat{H}$ is measurements, $\mat{F}_C$ system, $\mat{G}$ input gain, $\vec{w}$ process noise, $\vec{v}$ measurement noise, both zero-mean \bi{Gaussian White Noise Process}.
For n-lin. cont-time system: For \bi{n-lin. cont-time system}:
$\vec{\dot{x}}(t) = \vec{f}_C(\vec{x}(t), \vec{u}(t), \vec{w}(t))$\\ $\vec{\dot{x}}(t) = \vec{f}_C(\vec{x}(t), \vec{u}(t), \vec{w}(t))$\\
$\vec{z}(t) = \vec{h}(\vec{x}(t)) = \vec{v})(t)$, $\vec{z}(t) = \vec{h}(\vec{x}(t)) = \vec{v})(t)$,
linearization is the same linearization is the same
To discretize, integrate from $t_{k - 1}$ to $t_k$: To \bi{discretize}, integrate from $t_{k - 1}$ to $t_k$:\\
$\vec{x}_k = \vec{f}(\vec{x}_{k - 1}, \vec{u}_k, \vec{w}_k)$ $\vec{x}_k = \vec{f}(\vec{x}_{k - 1}, \vec{u}_k, \vec{w}_k)$
$\vec{z}_k = \vec{h}(\vec{x}_k) + \vec{v}_k$, $\vec{z}_k = \vec{h}(\vec{x}_k) + \vec{v}_k$,
linearised:\\ \bi{linearised}:\\
$\delta \vec{x}_k = \vec{f}(\vec{\overline{x}}, \vec{\overline{u}}) + \mat{F} \delta \vec{x}_{k - 1} + \mat{G}_k \delta \vec{u}_k + \mat{L}_k \vec{w}_k$; $\delta \vec{x}_k = \vec{f}(\vec{\overline{x}}, \vec{\overline{u}}) + \mat{F} \delta \vec{x}_{k - 1} + \mat{G}_k \delta \vec{u}_k + \mat{L}_k \vec{w}_k$;
$\delta \vec{z}_k = \mat{H}_k \delta \vec{x}_k$ $\delta \vec{z}_k = \mat{H}_k \delta \vec{x}_k$
\bi{Trapezoidal num. int}
$\Delta \vec{x}_1 = \Delta t \vec{f}_C (\vec{x}_{k - 1}, \vec{u}_{k - 1}, t_{k - 1})$\\
$\Delta \vec{x}_2 = \Delta t \vec{f}_C (\vec{x}_{k - 1} + \Delta \vec{x}_1, \vec{u}_{k}, t_{k})$, then:\\
$\vec{x}_k = \vec{x}_{k - 1} + 0.5 \cdot (\Delta \vec{x}_1 + \Delta \vec{x}_2)$
@@ -1 +1,50 @@
\newpage
\subsection{Rigid body \& IMU kinematics} \subsection{Rigid body \& IMU kinematics}
\begin{wrapfigure}[5]{r}{0.3\columnwidth}
\includegraphics[width=0.3\columnwidth]{assets/rigid-body-6d.png}
\end{wrapfigure}
\bi{Velocity} ${_I}\vec{v}_{IB} = \diff{t} ({_I}\vec{t}_B)$
\bi{Rot. Velocity} ${_I}\vec{\omega}_{IB} = \diff{t} (\alpha)\; {_I}\vec{t}$
\bi{Velocity point $P$} ${_B}\vec{v}_{IP} = {_B}\vec{v}_{IB} + {_B}\vec{\omega}_{IB} \times {_B}\vec{t}_{P}$
\bi{Rotation Matrices}
\begin{itemize}
\item For left pertubing\\
$\mat{\dot{R}}_{IB} = [{_I} \omega_{IB}]^\times \mat{R}_{IB}$
\item For right pertubing
$\mat{\dot{R}}_{IB} = \mat{R}_{IB} [{_I} \omega_{IB}]^\times$
\item Constant angular velocity ($\exp{[\Delta \alpha]^\times} = \delta \mat{R}(\Delta \alpha)$)\\
$\mat{R}_{IB}(t + \Delta t) = \exp{[\Delta \alpha]^\times} \mat{R}_{IB}(t)$
\end{itemize}
\bi{Quaternions}
\begin{itemize}
\item For left pertubing
$\displaystyle \vec{\dot{q}}_{IB} = \frac{1}{2} \begin{bmatrix}
{_I}\vec{\omega}_{IB} \\
0
\end{bmatrix}
\otimes \vec{q}_{IB}$
\item For right pertubing
$\displaystyle \vec{\dot{q}}_{IB} = \frac{1}{2} \vec{q}_{IB} \otimes \begin{bmatrix}
{_B}\vec{\omega}_{IB} \\
0
\end{bmatrix}$
\end{itemize}
\bi{IMU} (Outputs {\color{blue} ${_S}\vec{\tilde{a}}$} (accel.), {\color{red} ${_S}\vec{\tilde{\omega}}$} (rot. accel.))\\
${_W}\vec{\dot{t}}_S = {_W} \vec{v}$,
$\displaystyle \vec{\dot{q}}_{WS} = \frac{1}{2} \vec{q}_{WS} \otimes
\begin{bmatrix}
{\color{red}{_S}\vec{\tilde{\omega}}} {\color{gray} + \vec{w}_g - \vec{b}_g} \\
0
\end{bmatrix}$
${_W}\vec{\dot{v}} = \mat{R}_{WS}\; ({\color{blue}{_S}\vec{\tilde{a}}} {\color{gray} + \vec{w}_a - \vec{b}_a}) + {_W}\vec{g}$
where {\color{gray} gray parts} only IRL (in theor. models, leave out), with $\vec{\dot{b}}_g = \vec{w}_{b_g}$ and $\vec{\dot{b}}_a = \vec{w}_{b_a}$
\bi{IMU Sensor Model}: $\vec{\tilde{z}} = \vec{b}_C + s\mat{M}\vec{z} + \vec{b} + \vec{n} + \vec{o}$
where bias $\vec{b}$ and scale $s$ often modled as time-varying state $\dot{b}(t) = \sigma_C n(t)$.
$\vec{b}_C$ const. calib. and $\vec{n}$ the model.
@@ -1 +1,11 @@
\subsection{Rigid Body Dynamics} \subsection{Rigid Body Dynamics}
\inlinedefinition[Newton II] For fin. body w/ mass $m$ and inertia mat. $I$, with force $\vec{F}$ and torque $\vec{T}$ on \bi{Centre of Mass} (CoM), expressed in body frame:
\rmvspace[1.5]
\begin{align*}
{_B}\vec{F} &= \sum {_B}\vec{F}_i = m({_B} \vec{\dot{v}}_{CoM}) + m_B \vec{\omega} \times {_B}\vec{v}_{CoM} \\
{_B}\vec{T} &= \sum {_B}\vec{T}_i = \mat{I}({_B} \vec{\dot{\omega}}) + {_B} \vec{\omega} \times \mat{I}_B\vec{\omega}
\end{align*}
\rmvspace
${_B} \vec{v}_{CoM}$ vel. of CoM, ${_B}\omega$ rot. speed; both w.r.t. world frame
@@ -1 +1,57 @@
\subsection{Wheeled robot Kinematics} \subsection{Wheeled robot Kinematics}
\begin{wrapfigure}[7]{r}{0.2\columnwidth}
\includegraphics[width=0.2\columnwidth]{assets/wheel-constraints.png}
\end{wrapfigure}
\bi{Non-holonomic} systems \textbf{not integrable}, no inst. move in every direct.
\bi{Wheel constraints} $v_i = \omega_i r_i$
\begin{itemize}
\item \textit{Driving straight} all $\vec{v}$ equal
\item \textit{Turning} Wheel axis must intersect the \bi{Instant Centre of Rotation} (ICR),
speeds: $v_i \div R_i = \Omega$ ($R_i$ dist. wheel-ICR, $\Omega$, vehicle body rotation rate)
\end{itemize}
\bi{Maneuverability}
\begin{itemize}
\item Deg. of Mobility: $\delta_m = 3 - $\#constrained directions
\item Deg. of Steerability: $\delta_s = $\#steerable wheels
\item Deg. of Maneuverability: $\delta_M = \delta_m + \delta_s$
\end{itemize}
\bi{Wheel Configurations}
\includegraphics[width=1\columnwidth]{assets/wheel-config.png}
\begin{scriptsize}
\begin{tabular}{llllll}
Bicyle & Tricycle & Ackermann & Diff. Drive & Two-Steer & Three-Steer \\
$\delta_m = 1$ & $\delta_m = 1$ & $\delta_m = 0$ & $\delta_m = 2$ & $\delta_m = 1$ & $\delta_m = 0$ \\
$\delta_s = 1$ & $\delta_s = 1$ & $\delta_s = 2$ & $\delta_s = 0$ & $\delta_s = 2$ & $\delta_s = 3$ \\
$\delta_M = 2$ & $\delta_M = 2$ & $\delta_M = 2$ & $\delta_M = 2$ & $\delta_M = 3$ & $\delta_M = 3$ \\
\end{tabular}
\end{scriptsize}
\bi{Differential Drive Kinematics}
\bi{State vec} $\vec{x} = [x_1, x_2, \theta]^\top$,
\bi{Inputs} $\vec{u} = [\omega_l, \omega_r]^\top$, $r_r$ radius of right wheel, $w$ width of robot
\bi{Gen. eq. of Motion} $\dot{x}_1 = v\cos(\theta)$, $\dot{x}_2 = v\sin(\theta)$, $\dot{\theta} = \Omega$,
with $v = 0.5\cdot(\omega_l r_l + \omega_r + r_r)$, $\Omega = \frac{\omega_r r_r - \omega_l r_l}{w}$
\textit{Straight}: $v = \omega_l r_l = \omega_r r_r$, $\Omega = 0$, $D = v\Delta t$.\\
$\vec{b}_s = \begin{bmatrix}
D \cos(\theta) \\
D \sin(\theta) \\
0
\end{bmatrix}$
$\vec{b}_t = \begin{bmatrix}
R(\sin(\Delta \theta + \theta) - \sin(\theta))\\
-R(\cos(\Delta \theta + \theta) - \cos(\theta))\\
\Delta \theta
\end{bmatrix}$
\textit{Turning}: $\Omega = (\omega_l r_l) / R_l\! =\! (\omega_r r_r) / R_r$, $R\! =\! v / \Omega$, $\Delta \theta\! =\! \Omega \Delta t$
\textbf{Discretized}: $\vec{x}_k = \vec{x}_{k - 1} b_i$ with $i \in \{s, t\}$. ($\int \ldots \dx \Delta t$)