QP-Spline-Path Optimizer
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Quadratic programming + Spline interpolation
1. Objective function
1.1 Get path length
Path is defined in station-lateral coordination system. The s range from vehicle's current position to default planing path length.
1.2 Get spline segments
Split the path into n segments. each segment trajectory is defined by a polynomial.
1.3 Define function for each spline segment
Each segment i has accumulated distance $d_i$ along reference line. The trajectory for the segment is defined as a polynomial of degree five by default.
$$ l = f_i(s) = a_{i0} + a_{i1} \cdot s + a_{i2} \cdot s^2 + a_{i3} \cdot s^3 + a_{i4} \cdot s^4 + a_{i5} \cdot s^5 (0 \leq s \leq d_{i}) $$
1.4 Define objective function of optimization for each segment
$$ cost = \sum_{i=1}^{n} \Big( w_1 \cdot \int\limits_{0}^{d_i} (f_i')^2(s) ds + w_2 \cdot \int\limits_{0}^{d_i} (f_i'')^2(s) ds + w_3 \cdot \int\limits_{0}^{d_i} (f_i^{\prime\prime\prime})^2(s) ds \Big) $$
1.5 Convert the cost function to QP formulation
QP formulation:
$$ \begin{aligned} minimize & \frac{1}{2} \cdot x^T \cdot H \cdot x + f^T \cdot x \ s.t. \qquad & LB \leq x \leq UB \ & A_{eq}x = b_{eq} \ & Ax \geq b \end{aligned} $$
Below is the example for converting the cost function into the QP formulaiton.
$$
f_i(s) =
\begin{vmatrix} 1 & s & s^2 & s^3 & s^4 & s^5 \end{vmatrix}
\cdot
\begin{vmatrix} a_{i0} \ a_{i1} \ a_{i2} \ a_{i3} \ a_{i4} \ a_{i5} \end{vmatrix}
$$
And
$$
f_i'(s) =
\begin{vmatrix} 0 & 1 & 2s & 3s^2 & 4s^3 & 5s^4 \end{vmatrix}
\cdot
\begin{vmatrix} a_{i0} \ a_{i1} \ a_{i2} \ a_{i3} \ a_{i4} \ a_{i5} \end{vmatrix}
$$
And
$$ f_i'(s)^2 = \begin{vmatrix} a_{i0} & a_{i1} & a_{i2} & a_{i3} & a_{i4} & a_{i5} \end{vmatrix} \cdot \begin{vmatrix} 0 \ 1 \ 2s \ 3s^2 \ 4s^3 \ 5s^4 \end{vmatrix} \cdot \begin{vmatrix} 0 & 1 & 2s & 3s^2 & 4s^3 & 5s^4 \end{vmatrix} \cdot \begin{vmatrix} a_{i0} \ a_{i1} \ a_{i2} \ a_{i3} \ a_{i4} \ a_{i5} \end{vmatrix} $$
then we have,
$$
\int\limits_{0}^{d_i} f_i'(s)^2 ds =
\int\limits_{0}^{d_i}
\begin{vmatrix} a_{i0} & a_{i1} & a_{i2} & a_{i3} & a_{i4} & a_{i5} \end{vmatrix}
\cdot
\begin{vmatrix} 0 \ 1 \ 2s \ 3s^2 \ 4s^3 \ 5s^4 \end{vmatrix}
\cdot
\begin{vmatrix} 0 & 1 & 2s & 3s^2 & 4s^3 & 5s^4 \end{vmatrix}
\cdot
\begin{vmatrix} a_{i0} \ a_{i1} \ a_{i2} \ a_{i3} \ a_{i4} \ a_{i5} \end{vmatrix} ds
$$
extract the const outside the integration, we have,
$$
\int\limits_{0}^{d_i} f'(s)^2 ds =
\begin{vmatrix} a_{i0} & a_{i1} & a_{i2} & a_{i3} & a_{i4} & a_{i5} \end{vmatrix}
\cdot
\int\limits_{0}^{d_i}
\begin{vmatrix} 0 \ 1 \ 2s \ 3s^2 \ 4s^3 \ 5s^4 \end{vmatrix}
\cdot
\begin{vmatrix} 0 & 1 & 2s & 3s^2 & 4s^3 & 5s^4 \end{vmatrix} ds
\cdot
\begin{vmatrix} a_{i0} \ a_{i1} \ a_{i2} \ a_{i3} \ a_{i4} \ a_{i5} \end{vmatrix}
$$
$$
=\begin{vmatrix} a_{i0} & a_{i1} & a_{i2} & a_{i3} & a_{i4} & a_{i5} \end{vmatrix}
\cdot \int\limits_{0}^{d_i}
\begin{vmatrix}
0 & 0 &0&0&0&0\
0 & 1 & 2s & 3s^2 & 4s^3 & 5s^4\
0 & 2s & 4s^2 & 6s^3 & 8s^4 & 10s^5\
0 & 3s^2 & 6s^3 & 9s^4 & 12s^5&15s^6 \
0 & 4s^3 & 8s^4 &12s^5 &16s^6&20s^7 \
0 & 5s^4 & 10s^5 & 15s^6 & 20s^7 & 25s^8
\end{vmatrix} ds
\cdot
\begin{vmatrix} a_{i0} \ a_{i1} \ a_{i2} \ a_{i3} \ a_{i4} \ a_{i5} \end{vmatrix}
$$
Finally, we have
$$ \int\limits_{0}^{d_i} f'_i(s)^2 ds =\begin{vmatrix} a_{i0} & a_{i1} & a_{i2} & a_{i3} & a_{i4} & a_{i5} \end{vmatrix} \cdot \begin{vmatrix} 0 & 0 & 0 & 0 &0&0\\ 0 & d_i & d_i^2 & d_i^3 & d_i^4&d_i^5\\ 0& d_i^2 & \frac{4}{3}d_i^3& \frac{6}{4}d_i^4 & \frac{8}{5}d_i^5&\frac{10}{6}d_i^6\\ 0& d_i^3 & \frac{6}{4}d_i^4 & \frac{9}{5}d_i^5 & \frac{12}{6}d_i^6&\frac{15}{7}d_i^7\\ 0& d_i^4 & \frac{8}{5}d_i^5 & \frac{12}{6}d_i^6 & \frac{16}{7}d_i^7&\frac{20}{8}d_i^8\\ 0& d_i^5 & \frac{10}{6}d_i^6 & \frac{15}{7}d_i^7 & \frac{20}{8}d_i^8&\frac{25}{9}d_i^9 \end{vmatrix} \cdot \begin{vmatrix} a_{i0} \\ a_{i1} \\ a_{i2} \\ a_{i3} \\ a_{i4} \\ a_{i5} \end{vmatrix} $$
Please notice that we got a 6 x 6 matrix to represent the derivative cost of 5th order spline.
Similar deduction can also be used to calculate the cost of second and third order derivatives.
2 Constraints
2.1 The init point constraints
Assume that the first point is ($s_0$, $l_0$), ($s_0$, $l'_0$) and ($s_0$, $l''_0$), where $l_0$ , $l'_0$ and $l''_0$ is the lateral offset and its first and second derivatives on the init point of planned path, and are calculated from $f_i(s)$, $f'_i(s)$, and $f_i(s)''$.
Convert those constraints into QP equality constraints, using:
$$ A_{eq}x = b_{eq} $$
Below are the steps of conversion.$$ f_i(s_0) = \begin{vmatrix} 1 & s_0 & s_0^2 & s_0^3 & s_0^4&s_0^5 \end{vmatrix} \cdot \begin{vmatrix} a_{i0} \ a_{i1} \ a_{i2} \ a_{i3} \ a_{i4} \ a_{i5}\end{vmatrix} = l_0 $$
And$$ f'i(s_0) = \begin{vmatrix} 0& 1 & 2s_0 & 3s_0^2 & 4s_0^3 &5 s_0^4 \end{vmatrix} \cdot \begin{vmatrix} a{i0} \ a_{i1} \ a_{i2} \ a_{i3} \ a_{i4} \ a_{i5} \end{vmatrix} = l'0 $$
And$$ f''_i(s_0) = \begin{vmatrix} 0&0& 2 & 3\times2s_0 & 4\times3s_0^2 & 5\times4s_0^3 \end{vmatrix} \cdot \begin{vmatrix} a{i0} \ a_{i1} \ a_{i2} \ a_{i3} \ a_{i4} \ a_{i5} \end{vmatrix} = l''_0 $$
where i is the index of the segment that contains the $s_0$.2.2 The end point constraints
Similar to the init point, the end point $(s_e, l_e)$ is known and should produce the same constraint as described in the init point calculations.
Combine the init point and end point, and show the equality constraint as:
$$ \begin{vmatrix} 1 & s_0 & s_0^2 & s_0^3 & s_0^4&s_0^5 \\ 0&1 & 2s_0 & 3s_0^2 & 4s_0^3 & 5s_0^4 \\ 0& 0&2 & 3\times2s_0 & 4\times3s_0^2 & 5\times4s_0^3 \\ 1 & s_e & s_e^2 & s_e^3 & s_e^4&s_e^5 \\ 0&1 & 2s_e & 3s_e^2 & 4s_e^3 & 5s_e^4 \\ 0& 0&2 & 3\times2s_e & 4\times3s_e^2 & 5\times4s_e^3 \end{vmatrix} \cdot \begin{vmatrix} a_{i0} \\ a_{i1} \\ a_{i2} \\ a_{i3} \\ a_{i4} \\ a_{i5} \end{vmatrix} = \begin{vmatrix} l_0\\ l'_0\\ l''_0\\ l_e\\ l'_e\\ l''_e\\ \end{vmatrix} $$
2.3 Joint smoothness constraints
This constraint is designed to smooth the spline joint. Assume two segments $seg_k$ and $seg_{k+1}$ are connected, and the accumulated s of segment $seg_k$ is $s_k$. Calculate the constraint equation as:
$$ f_k(s_k) = f_{k+1} (s_0) $$
Below are the steps of the calculation.$$ \begin{vmatrix} 1 & s_k & s_k^2 & s_k^3 & s_k^4&s_k^5 \ \end{vmatrix} \cdot \begin{vmatrix} a_{k0} \ a_{k1} \ a_{k2} \ a_{k3} \ a_{k4} \ a_{k5} \end{vmatrix} = \begin{vmatrix} 1 & s_{0} & s_{0}^2 & s_{0}^3 & s_{0}^4&s_{0}^5 \ \end{vmatrix} \cdot \begin{vmatrix} a_{k+1,0} \ a_{k+1,1} \ a_{k+1,2} \ a_{k+1,3} \ a_{k+1,4} \ a_{k+1,5} \end{vmatrix} $$
Then
$$
\begin{vmatrix}
1 & s_k & s_k^2 & s_k^3 & s_k^4&s_k^5 & -1 & -s_{0} & -s_{0}^2 & -s_{0}^3 & -s_{0}^4&-s_{0}^5\
\end{vmatrix}
\cdot
\begin{vmatrix}
a_{k0} \ a_{k1} \ a_{k2} \ a_{k3} \ a_{k4} \ a_{k5} \ a_{k+1,0} \ a_{k+1,1} \ a_{k+1,2} \ a_{k+1,3} \ a_{k+1,4} \ a_{k+1,5}
\end{vmatrix}
= 0
$$
Similarly calculate the equality constraints for:
$$ f'k(s_k) = f'{k+1} (s_0) \ f''k(s_k) = f''{k+1} (s_0) \ f'''k(s_k) = f'''{k+1} (s_0) $$
2.4 Sampled points for boundary constraint
Evenly sample m points along the path, and check the obstacle boundary at those points. Convert the constraint into QP inequality constraints, using:
$$ Ax \geq b $$
First find the lower boundary $l_{lb,j}$ at those points $(s_j, l_j)$ and $j\in[0, m]$ based on the road width and surrounding obstacles. Calculate the inequality constraints as:$$ \begin{vmatrix} 1 & s_0 & s_0^2 & s_0^3 & s_0^4&s_0^5 \ 1 & s_1 & s_1^2 & s_1^3 & s_1^4&s_1^5 \ ...&...&...&...&...&... \ 1 & s_m & s_m^2 & s_m^3 & s_m^4&s_m^5 \ \end{vmatrix} \cdot \begin{vmatrix}a_{i0} \ a_{i1} \ a_{i2} \ a_{i3} \ a_{i4} \ a_{i5} \end{vmatrix} \geq \begin{vmatrix} l_{lb,0}\ l_{lb,1}\ ...\ l_{lb,m}\ \end{vmatrix} $$
Similarly, for the upper boundary $l_{ub,j}$, calculate the inequality constraints as:
$$ \begin{vmatrix} -1 & -s_0 & -s_0^2 & -s_0^3 & -s_0^4&-s_0^5 \ -1 & -s_1 & -s_1^2 & -s_1^3 & -s_1^4&-s_1^5 \ ...&...-&...&...&...&... \ -1 & -s_m & -s_m^2 & -s_m^3 & -s_m^4&-s_m^5 \ \end{vmatrix} \cdot \begin{vmatrix} a_{i0} \ a_{i1} \ a_{i2} \ a_{i3} \ a_{i4} \ a_{i5} \end{vmatrix} \geq -1 \cdot \begin{vmatrix} l_{ub,0}\ l_{ub,1}\ ...\ l_{ub,m}\ \end{vmatrix} $$