To install the package use pip:
pip install .
To run the planner for a particular robot and environment you can use scripts/run_planner.py**
. The script takes the following argumnet:
- robot [
tri
,diff
] : The robot for model. - env [
mini
,turn
,map
] : The environment that needs to be tested. - iterations : The number of iterations for the SST planner.
- graph : A flag that will enable display of graph construction.
- render : A flag that will enable the rendering of the environment if a path exists.
Egs:
python scripts/run_planner.py tri mini --iterations=100000
python scripts/run_planner.py diff map --iterations=1e6 --seed=5 --graph
python scripts/run_planner.py diff turn --render
You can run this planner on an object of class of subclass of bc_gym_planning_env.envs.base.env.PlanEnv
.
You can use the following script to create an object of class sparse_rrt.systems.system_interface.Isystem
for an object env
.
from sst_wrapper.envs.bc_gym_wrapper import BcGymWrapper
from sst_wrapper.envs.gym_sst_wrapper import BcSstWrapper
system = BcSstWrapper(BcGymWrapper(env))
system
can now be used to run sparse_rrt.planners.SST
. Look at sparse-rrt for more info.