Comments (4)
Awesome! I'll take a look. Thanks, @JacopoPan
from gym-pybullet-drones.
Hi @thaipduong
yes, that is expected, of course, the slowdown will be proportional to:
- number of UAVs
num_drones
(Not the the vision is in each UAV frame so these are all separate render views) - resolution
self.IMG_RES = np.array([64, 48])
inBaseAviary
- framerate of capture
self.IMG_FRAME_PER_SEC = 24
inBaseAviary
For the sake of collecting data, I would recommend running headless (gui=False
) and to use an Ubuntu machine and GPU
In this case you can uncomment line 203 inBaseAviary
if platform == "linux": p.setAdditionalSearchPath(pybullet_data.getDataPath()); plugin = p.loadPlugin(egl.get_filename(), "_eglRendererPlugin"); print("plugin=", plugin)
for hardware acceleration (see section "Plugins" of PyBullet manual)
from gym-pybullet-drones.
I see. Thank you, @JacopoPan
Just to confirm, there is currently no lidar on the drone, right?
from gym-pybullet-drones.
Sorry, I forgot to answer your second question.
I didn't implement anything specifically in this repo, but if you look at another work-in-progress env I have here there is an example of how to use PyBullet's rayTest
to determine if there is line-of-sight between agents.
from gym-pybullet-drones.
Related Issues (20)
- Parameters error while running learn.py HOT 1
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- Cannot run simulation on linux Fedora HOT 9
- Question about action buffer HOT 2
- Custom training environment HOT 4
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from gym-pybullet-drones.