Apparatus and method for characterizing an object based on measurement samples from one or more location sensors
View Patent ↗A concept of characterizing an object based on measurement samples from one or more location sensors, the measurement samples having a first spatial resolution. The measurement samples are quantized to a grid map of weighted cells having a second spatial resolution lower than the first spatial resolution, wherein a measurement sample contributes to a weight coefficient of one or more weighted cells depending on a measurement accuracy. Parameters of one or more lines fitting the weighted cells are computed to obtain a characterization of the object.
1. An apparatus for characterizing an object based on measurement samples from one or more location sensors, the measurement samples having a first spatial resolution, the apparatus comprising:
a processor circuit configured to
quantize the measurement samples to a grid map of weighted cells having a second spatial resolution lower than the first spatial resolution, wherein a measurement sample contributes to a weight coefficient of one or more weighted cells depending on a measurement accuracy;
and compute line parameters of one or more lines fitting the weighted cells to obtain a characterization of the object.
2. The apparatus of claim 1 , wherein the processor circuit is configured to determine the weight coefficient of a weighted cell based on a probability distribution around the measurement sample, wherein the probability distribution is based on the measurement accuracy of the one or more location sensors.
3. The apparatus of claim 2 , wherein a measurement sample having an associated non-vanishing probability distribution in an area of a weighted cell adds to the weight coefficient of said cell.
4. The apparatus of claim 1 , wherein the processor circuit is configured to detect, based on the weighted cells, one or more edges of the object, the one or more edges corresponding to the one or more lines.
5. The apparatus of claim 1 , wherein the processor circuit is configured to compute line parameters of two orthogonal lines fitting the weighted cells.
6. The apparatus of claim 1 , wherein the processor circuit is configured to compute the line parameters of the one or more lines based on a weighted constraint least square algorithm taking into account the weight coefficients of the one or more weighted cells.
7. The apparatus of claim 6 , wherein the processor circuit is configured to compute a first and a second line parameter corresponding to an orientation of the one or more lines based on a computation of an eigenvector of a normalized system matrix, the normalized system matrix comprising normalized coordinates of the weighted cells, the normalized coordinates being normalized to mean coordinates of the one or more lines.
8. The apparatus of claim 7 , wherein the processor circuit is configured to compute at least one further line parameter c j corresponding to a position of line j based on:
c
j
=
W
j
A
j
∑
w
j
,
i
[
n
1
n
2
]
T
,
wherein n 1 and n 2 correspond to the first and a second line parameter,
W
j
=
(
w
j
,
1
0
0
0
⋱
0
0
0
w
j
,
N
)
with w j,i being the weight of the i-th weighted cell of line j,
wherein A j is the corresponding part of the system matrix A, including the measurement samples of line j.
9. The apparatus of claim 6 , wherein the processor circuit is configured to compute a system covariance matrix including variances of the respective line parameters and covariances between different line parameters based on a system matrix including coordinates of the weighted cells, the weight coefficients of the weighted cells, and based on deviations of the weighted cells from the one or more lines.
10. The apparatus of claim 9 , wherein the processor circuit is configured to compute the system covariance matrix Σ Sys according to:
Σ
S
y
s
=
r
T
W
r
2
∑
w
j
,
i
(
A
T
W
A
)
-
1
wherein A is a system matrix including coordinates of the measurement samples, r is a vector including the deviations of the weighted cells from the one or more lines, Σ is a matrix including variances and covariances of the line parameters and W is a matrix including weight matrices corresponding to the one or more lines according to
W
=
[
W
j
=
1
0
0
0
⋱
0
0
0
W
j
=
K
]
,
wherein K is the number of lines.
11. The apparatus of claim 9 , wherein the processor circuit is configured to compute a covariance matrix of coordinates (x c , y c ) of an intersection point between a first and a second line based on the system covariance matrix and the coordinates (x c , y c ).
12. The apparatus of claim 9 , wherein the processor circuit is configured to compute a variance of an orientation of the one or more lines based on line parameters corresponding to an orientation of the one or more lines, variances, and covariances thereof.
13. A vehicle comprising one or more location sensors and an apparatus of claim 1 .
14. A method for characterizing an object based on measurement samples from one or more location sensors, the measurement samples having a first spatial resolution, the method comprising:
quantizing the measurement samples to a grid map of weighted cells having a second spatial resolution lower than the first spatial resolution, wherein a measurement sample contributes to a weight coefficient of one or more weighted cells depending on a measurement accuracy; and
computing parameters of one or more lines fitting the weighted cells to obtain a characterization of the object.
15. A non-transitory computer-readable medium having a program code for performing the method of claim 14 , when the program code is executed on a programmable hardware device.