Indications.txt

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Occupancy gridmap building
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The goal of this optional project is to implement the needed functionality so a robot moving in an environment can build an occupancy gridmap of it.

Starting setup
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 - A 2D laser simulator is provided.
 - The environment is defined with lines. You can modify it.
 - Localization is known.

Implementation
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 - All the code must be implemented by your own.
 - Implementation as a Jupyter notebook.
 - In order to build the map, the robot has to move within it. Implement the robot motion.
 - Implement the building of the occupancy gridmap with the information coming from the laser and the known robot pose. 
 - You would need to implement the inverse sensor model.

Optional aspects
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 - Change the map definition to an arbitrary input image.
 - Implement a new laser simulator able to work with this new representation (e.g. ray tracing).
 - Consider that the localization is not given, so you have to compute it when the robot moves. You can use, for example, ICP.
 - Implement different surfaces in the map, so the sensor performance may vary (e.g., appearing large errors). For example, black surfaces absorb more infrarred rays, difficulting sensor operation.
Laser related:
  - Test the efect of different real lasers (surf the internet to find them, e.g. Hokuyo, Sick) in the resulting map (different FOV, max range, resolution, error, etc.).
 - Implement additional sources of uncertainty in the laser measurements: random and max range.
 - Implement moving obstacles (people, pets, etc.).