Hi,
I'd like to get my wheeled robot with it's vision system to be able to identify various objects that are located in an out-door car park.
The objects are things like ... a door...a window ... lamp-post, gate, tree, etc.
The objective is that the robot will start at an undefined position, then move across about 100 meters and search for 1 or more object and thus determine it's location and position in the car-park.
The problem I foresee ( among several challenges ) is that the camera and the vision system will see the objects from different angles and positions, so just programming it to learn and identify each object, using standard object recognition code, might not work.
If the wheeled robot approaches from the right-hand side on 1 day, but approaches from the left-side on another day, how can it reliably identify an object or feature ?
What general solution would work ? ( I do not want to try complex 3-d based solid object recognition.)
What python-based solution can detect objects viewed from different positions and then figure out what the object is from a list of about 20 different objects ?
I've already created various basic / intermediate level applications that detect objects ... red ball, faces, dog, cat, etc.
I'm using python, a Raspberry Pi, networked to a windows laptop via wi-fi using client-server socket code.
I'd like to get your advice before starting to code - I hope to avoid creating a bad solution that is fundamentally wrong and having to start all over again !
Thanks for your suggestions,
Robert