Isaac Sim Version
[ ✔] 4.2.0
4.1.0
4.0.0
2023.1.1
2023.1.0-hotfix.1
Other (please specify):
Isaac Lab Version (if applicable)
[✔] 1.2
1.1
1.0
Other (please specify):
Operating System
Ubuntu 22.04
Ubuntu 20.04
Windows 11
[✔] Windows 10
Other (please specify):
GPU Information
- Model: 2080ti
- Driver Version: 565.90
Topic Description
Detailed Description
I want to achieve the effect in isaaclab where the markers move with a translating artifact, and the markers can be captured by the camera and used for reinforcement learning training. In each simulation frame, I would move the existing marker coordinates and then add new marker coordinates. visualizationmarkers
directly inputs all coordinates, while debug_draw
clears the existing markers before displaying new ones. When the number of markers exceeds 10,000, both methods become very laggy. The current solution is to keep the artifact stationary, move the robot and the scene, and then use debug_draw
to input only the new marker coordinates each time. The problem now is that the display effect of debug_draw
is not satisfactory, while visualizationmarkers
is too laggy. In the source code, the method self._instancer_manager.GetPositionsAttr().Set(Vt.Vec3fArray.FromNumpy(translations))
is not clear to me after checking the USD documentation. I want to ask if it can achieve this effect.
Steps to Reproduce
- visualizationmarkers:
all_sampled_data = torch.cat((all_sampled_data, sampled_data), dim=0)
if all_sampled_data.numel() > 0:
paint_marker.visualize(translations=all_sampled_data)
- debug_draw:
data_list = sampled_data.tolist()
tuple_list = [tuple(item) for item in data_list]
N=len(tuple_list)
if N > 0:
draw.draw_points(tuple_list, colors*N, sizes*N)