Intelligence Mobile Robotics Homework 04

Intelligence Mobile Robotics
Homework 04

1 Task One
Simultaneous localization and mapping (SLAM) is the problem of acquiring a map of an unknown
environment, while simultaneously localizing the robot relative to the map. In this homework, you
are going to incorporate mapping while localizing the robot; this is a continuation of the HW3. You
should use the same robot model (HW3) for this homework as well.
1. Let’s say we have n landmarks and now we need to incorporate those locations into the state
vector (xk). Design the xk?
2. Design the system model (Φk)?
3. Derive an expression for x¯
−
k
and P
−
k
in general?
4. A sensor that attached to the robot gives the distances to each visible landmark. Hence, range
can be obtained to each sensor as follow. Assume, mi
x
and mi
y
are the distances on x and y
direction respectively. r =
q
(mi
x − x)
2 + (mi
y − y)
2 where i depicts i
th landmark. Relative
orientation to each landmark φ = arctan( mi
y−y
mi
x−x
) − θ. Using this information try to obtain the
measurement model (h(¯x
−
k
))?
5. Write down all the assumptions about errors of the filter?
6. The robot should route through two paths: straight line and taking a turn. Draw Pk changes
over time for each of the paths where at least 4 timestamps would be enough: start position,
end position and a few in between start and end position.
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2 Task Two
Id Name
01 Sabirova Adelya
02 Ahmed Nawaz
03 Andrey Stepanov
04 Arslan Siddique
05 Aydar Ahmetzyanov
06 Dmitriy Desyatkin
07 Lyailya Aminova
08 Maksim Rassabin
09 Oleg Balakhnov
10 Sami Sellami
11 Valeriya Skvortsova
12 Victor Massague Respall
Each of you is provided with an image sequence of a scenario. After browsing your image set, try
to seek an object which is moving through a few images (at least 5 images) continuously. Locate a
bounding box for a chosen object which can be done either manually or automatically. Assuming
an object is not going away from the initial bounding box, try to find some feature points for the
background using any feature descriptor. Now assume those feature points are the landmarks for
the robot you have developed for the task one. Update EKF for as suited for this task. Assume
robot is moving on a straight line. If you want to make any additional assumptions please state
them as well.
3 Submit
What should you turn in? Please, upload the single zip file which includes your source code (task
01 and task 02) and the report for both tasks.
4 Deadline
The deadline: May 7, 23:54:59 GMT+3.
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