SAPIEN is a realistic and physics-rich simulated environment that hosts a large-scale set for articulated objects. It enables various robotic vision and interaction tasks that require detailed part-level understanding. SAPIEN is a collaborative effort between researchers at UCSD, Stanford and SFU. The dataset is a continuation of ShapeNet and PartNet.
2.2
- Rename
VulkanRenderer
toSapienRenderer
(VulkanRenderer is still an alias) - Support ray tracing in
SapienRenderer
- Deprecate
KuafuRenderer
, use the rt shader inSapienRenderer
instead - GPU-accelerated stereo depth sensor simulation
- Render server
- Python 3.11
- bug fixes
- Fix inverse kinematics default active joint mask (now defaults to all 1s)
- Fix incorrectly exported memory in Vulkan-Cuda interop
- Fix joint
get_global_pose
2.1
- Python 3.10
- Bug fixes
- crash when not using renderer
- joint force limit (was impulse limit)
- incorrect inertia computation in scaled URDF
- incorrect point-light shadow
- incorrect collision when loaded from dae
- Utility improvements
- set_material
- active light
- flat shading
- dynamic point rendering
- envmap generation
- multi-thread envs
2.1
- Refactor light system
- Remove light functions on scene.renderer_scene
- Refactor camera system
- Cameras no longer require mounts
- Camera can change its mount and mounted pose by
camera.set_parent
andcamera.set_local_pose
. - When camera is not mounted, setting local pose is setting its global pose.
- Add functions
scene.add_camera
andscene.remove_camera
add_mounted_camera
can be replaced withadd_camera
followed bycamera.set_parent
andcamera.set_local_pose
.add_mounted_camera
is still provided but fovx should not longer be provided.- Remove functions related to mount, including
find_camera_by_mount
. - Cameras now support full camera parameters through
camera.near
,camera.far
,camera.set_fovx
,camera.set_fovy
,camera.set_focal_lengths
,camera.set_principal_point
,camera.skew
, and the all-in-one methodcamera.set_perspective_parameters
.
- Refactor render shape system
- Originally, after
actor.get_visual_bodies()
andvisual_body.get_render_shapes()
, users typically doshape.scale
andshape.pose
. These are no longer valid. It is required to checkvisual_body.type
. Whentype
ismesh
,shape.scale
is replaced withvisual_body.scale
andshape.pose
is replaced byvisual_body.local_pose
. These changes are made to matchadd_visual_shape
functions when building the actor.
- Originally, after
pre2.0
- Shader change: 4th component in default camera shader now gives the 0-1 depth value.
- Add "critical" and "off" log levels.
- Add support for pointcloud and line rendering (for visualizing camera and point cloud)
- Performance: the same shader only compile once per process
- Bug fix
- Articulation setDriveTarget was now correctly reversed for prismatic joint (joint setDriveTarget is not affected)
- Fix kinematic articulation loader
1 to 2 migration
- replace
scene.renderer_scene.add_xxx_light
withscene.add_xxx_light
- replace
scene.remove_mounted_camera
withscene.remove_camera
- optionally, remove
fovx
fromscene.add_mounted_camera
.
1.1
- Support nonconvex static/kinematic collision shape
- Add warning for small mass/inertia
- Introduce Entity as the base class of Actors
- Add Light classes inherited from entity, allowing manipulate light objects in sapien scene
- Updates to the viewer
- rename actor to entity when appropriate
- Partial support the material tag in URDF loader (primitive shape, single color)
- Bug fixes for the renderer
- Support inner and outer FOV for spotlight
1.0
- Replace the old Vulkan based renderer completely
- See
sapien.core.renderer
for details
- See
- Expose GUI functionalities to Python
- Reimplement Vulkan viewer in Python
- Expose PhysX shape wrapper to Python. For example,
- Collision shapes can be retrieved through
actor.get_collision_shapes
- Collision groups on a shape can be set by
CollisionShape.set_collision_groups
- Shapes are now also available in
Contact
.
- Collision shapes can be retrieved through
- API changes
- Render material creation is now
renderer.create_material()
- in actor builder:
add_xxx_shape
is replaced withadd_xxx_collision
. - move light functions from scene to
scene.renderer_scene
- Render material creation is now
- Add centrifugal and Coriolis force.
- Change default physical parameters for better stability.
SAPIEN Engine provides physical simulation for articulated objects. It powers reinforcement learning and robotics with its pure Python interface.
SAPIEN provides rasterized and ray traced rendering with Vulkan.
SAPIEN releases PartNet-Mobility dataset, which is a collection of 2K articulated objects with motion annotations and rendernig material. The dataset powers research for generalizable computer vision and manipulation.
SAPIEN Website: https://sapien.ucsd.edu/. SAPIEN Documentation: https://sapien.ucsd.edu/docs/latest/index.html.
Make sure all submodules are initialized git submodule update --init --recursive
.
To build SAPIEN, simply run ./docker_build_wheels.sh
. It is not recommended to
build outside of our provided docker.
For reference, the Dockerfile is provided here. Note that PhysX needs to be compiled with clang-9 into static libraries before building the Docker image.
It can be tricky to setup all dependencies outside of a Docker environment. You
need to install all dependencies according to the Docker
environment. If all dependencies set up correctly, run
python setup.py bdist_wheel
to build the wheel.
If you use SAPIEN and its assets, please cite the following works:
@InProceedings{Xiang_2020_SAPIEN,
author = {Xiang, Fanbo and Qin, Yuzhe and Mo, Kaichun and Xia, Yikuan and Zhu, Hao and Liu, Fangchen and Liu, Minghua and Jiang, Hanxiao and Yuan, Yifu and Wang, He and Yi, Li and Chang, Angel X. and Guibas, Leonidas J. and Su, Hao},
title = {{SAPIEN}: A SimulAted Part-based Interactive ENvironment},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}}
@InProceedings{Mo_2019_CVPR,
author = {Mo, Kaichun and Zhu, Shilin and Chang, Angel X. and Yi, Li and Tripathi, Subarna and Guibas, Leonidas J. and Su, Hao},
title = {{PartNet}: A Large-Scale Benchmark for Fine-Grained and Hierarchical Part-Level {3D} Object Understanding},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}
@article{chang2015shapenet,
title={Shapenet: An information-rich 3d model repository},
author={Chang, Angel X and Funkhouser, Thomas and Guibas, Leonidas and Hanrahan, Pat and Huang, Qixing and Li, Zimo and Savarese, Silvio and Savva, Manolis and Song, Shuran and Su, Hao and others},
journal={arXiv preprint arXiv:1512.03012},
year={2015}
}
If you use SAPIEN Realistic Depth generated by SAPIEN's simulated depth sensor, please cite the following work:
@ARTICLE{10027470,
author={Zhang, Xiaoshuai and Chen, Rui and Li, Ang and Xiang, Fanbo and Qin, Yuzhe and Gu, Jiayuan and Ling, Zhan and Liu, Minghua and Zeng, Peiyu and Han, Songfang and Huang, Zhiao and Mu, Tongzhou and Xu, Jing and Su, Hao},
journal={IEEE Transactions on Robotics},
title={Close the Optical Sensing Domain Gap by Physics-Grounded Active Stereo Sensor Simulation},
year={2023},
volume={},
number={},
pages={1-19},
doi={10.1109/TRO.2023.3235591}}