alice-st / darp Goto Github PK

Hey there, thanks a lot for your python version of the DARP (java) project. It's very helpful for me and my master thesis.
The DARP algorithm had a problem which wouldn't let it find a optimal result, so I had a good look into your code and found the culpit. I want to share my work with you, so see my PullRequest [deleted] for the fix.

Hello, from my understanding, when configuring the graph, you take 2m x 2m as the dimensions where m = {1,2,3...}, which makes sense. However, with that in mind, how do you define the starting point? For example, if 0,0 is the starting point, you technically have 4 grids to decide? Is there anywhere in the code that I can change/update such feature?

The obstacle position argument seems to be 0 indexed i.e. (row=0, column=0 --> cell = 0). However in the "Usgae" section of the Readme file the documentation mentions it as (row=0, column=0 --> cell = 1).

When installing venv using instructions, I get the error message:

ERROR: No matching distribution found for numba==0.54.1
I'removed version specification for numba. Then:

The conflict is caused by:
    The user requested numpy==1.20
    opencv-python 4.5.4.60 depends on numpy>=1.21.2

I removed version specification for numpy. Now it works.

So, installation is successful when you change Dependencies.sh into:

if [ "$#" -ne 1 ]; then
  echo "Give only one argument, the name of the virtual environment to create"
  exit
fi

python3 -m venv $1

source $1/bin/activate

pip install \
	numpy\
	opencv-python==4.5.4.60 \
	pygame==2.1.0 \
	scipy==1.7.3 \
	jupyter==1.0.0 \
  numba\
  nose==1.3.7\
  parameterized==0.8.1\
  sklearn \
  Pillow

I'm on Ubuntu 22.04 LTS

Olivier here,

You will want to add an "iteration =0" at this spot, in order for the subsequent loops (when self.MaxIter gets divided by 2) to actually take place, and not simply to be skipped.

How can i get all possible path (or all possible MST generated)?

Hey there, while browsing through the code and inserting my own runtime improvements I realized the self.BWlist matrix inside the assign methode (with numba njit now a function) will always get generated but never used in the main update loop.
At the end of the update loops the self.getBinaryRobotRegions() methode generates the self.BinaryRobotRegions matrix, which will be used for the pathfinding later... so you get the robot segments (in a binary way) in a n-dimensional array there.
The BWList generation is useless in my point of view, cause the algorithm never uses the in-between-steps for anything.
You could remove self.BWlist or do you have reasons to keep it?

Have a nice day :)

This work looks very interesting! Can you specify the license under which this repository is shared?