A block-stacking task built based on robosuite.
- 首先安装
robosuite，推荐git clone + pip install -e .安装，方便定制环境 - 将
si-visual.xml, siBig-visual.xml, siRed-visual.xml复制至robosuite/robosuite/models/assets/objects/目录下 - 将
table_arena_si.xml复制至robosuite/robosuite/models/assets/arenas/目录下 - 将环境代码
spatial_intelligence.py复制至robosuite/robosuite/environments/manipulation/目录下 - 在
robosuite/robosuite/__init__.py中添加代码from robosuite.environments.manipulation.spatial_intelligence import SpatialIntelligence
./test.sh- 输出类似如下内容
result: True, message: Cube is placed at position [1 0 0].
result: True, message: Cube is placed at position [2 0 0].
result: True, message: Cube is placed at position [3 0 0].
result: True, message: Cube is placed at position [4 0 0].
result: True, message: Cube is placed at position [5 0 0].
result: True, message: Cube is placed at position [6 0 0].
result: True, message: Cursor is moved to position [5 0 0].
...- 生成
task_view目录，且目录中包含随机生成的积木cube_xyz_idx的三个视角图 - 生成
video目录，且目录中包含挪动光标搭建随机生成的积木cube_xyz_idx的视频
则表示环境可用
已经用CUDA_VISIBLE_DEVICES=0 python gen_connected_cube_set.py事先生成了目标积木和搭建对应积木的action序列，存储在connected_cube_set_100.pkl和connected_cube_set_1000.pkl中，分别表示100个eps和1000个eps
可以用run_gened_connected_cube_set.py复现事先生成的积木，但是需要将196-199行的注释取消，然后将200注释上，然后将38行的"test"改为"train"