Merge branch 'master_new_binding' of github.com:ARISE-Initiative/robo…

…suite-dev into master_new_binding

.gitignore

@@ -111,4 +111,7 @@ mjkey.txt
 *.jpg
 .idea
 
-.pytest_cache/
+.pytest_cache/
+
+# private macros
+macros_private.py

docs/algorithms/sim2real.md

@@ -102,7 +102,7 @@ By default, Mujoco sensors are deterministic and delay-free, which is often an u
 }
 ```
 
-Note that for memory efficiency the `image-state` is not returned by default (this can be toggled in `robosuite/utils/macros.py`).
+Note that for memory efficiency the `image-state` is not returned by default (this can be toggled in `robosuite/macros.py`).
 
 We showcase how the `Observable` functionality can be used to model sensor corruption and delay via [demo_sensor_corruption.py](../demos.html#sensor-realism). We also highlight that each of the `sensor`, `corrupter`, and `filter` functions can be arbitrarily specified to suit the end-user's usage. For example, a common use case for these observables is to keep track of sampled values from a sensor operating at a higher frequency than the environment step (control) frequency. In this case, the `filter` function can be leveraged to keep track of the real-time sensor values as they're being sampled. We provide a minimal script showcasing this ability below:
 
@@ -154,4 +154,4 @@ print(f"\nPolicy Frequency: {control_freq}, Observable Sampling Frequency: {obs_
 print(f"Number of recorded samples after 1 policy step: {buffer._size}\n")
 for i in range(buffer._size):
     print(f"Recorded value {i}: {buffer.buf[i]}")
-```
+```

docs/modules/sensors.md

@@ -28,6 +28,6 @@ Cameras bundle a name to a set of properties to render images of the environment
 
 For more information on the vision ground-truth sensors supported, please see the [Renderer](./renderers) section.
 
-Note that for memory efficiency the `image-state` is not returned by default (this can be toggled in `robosuite/utils/macros.py`).
+Note that for memory efficiency the `image-state` is not returned by default (this can be toggled in `robosuite/macros.py`).
 
 Observables can also be used to model sensor corruption and delay, and refer the reader to the [Sensor Randomization](../algorithms/sim2real.html#sensors) section for additional information.

docs/source/robosuite.utils.rst

@@ -44,10 +44,10 @@ robosuite.utils.input\_utils module
    :undoc-members:
    :show-inheritance:
 
-robosuite.utils.macros module
+robosuite.macros module
 -----------------------------
 
-.. automodule:: robosuite.utils.macros
+.. automodule:: robosuite.macros
    :members:
    :undoc-members:
    :show-inheritance:

robosuite/controllers/base_controller.py

@@ -1,13 +1,10 @@
 import abc
 from collections.abc import Iterable
-import numpy as np
 
-import robosuite.utils.macros as macros
+import mujoco
+import numpy as np
 
-if macros.USE_DM_BINDING:
-    import mujoco
-else:
-    import mujoco_py
+import robosuite.macros as macros
 
 
 class Controller(object, metaclass=abc.ABCMeta):
@@ -155,12 +152,8 @@ def update(self, force=False):
             self.J_ori = np.array(self.sim.data.get_site_jacr(self.eef_name).reshape((3, -1))[:, self.qvel_index])
             self.J_full = np.array(np.vstack([self.J_pos, self.J_ori]))
 
-            if macros.USE_DM_BINDING:
-                mass_matrix = np.ndarray(shape=(self.sim.model.nv, self.sim.model.nv), dtype=np.float64, order='C')
-                mujoco.mj_fullM(self.sim.model._model, mass_matrix, self.sim.data.qM)
-            else:
-                mass_matrix = np.ndarray(shape=(len(self.sim.data.qvel) ** 2,), dtype=np.float64, order='C')
-                mujoco_py.cymj._mj_fullM(self.sim.model, mass_matrix, self.sim.data.qM)
+            mass_matrix = np.ndarray(shape=(self.sim.model.nv, self.sim.model.nv), dtype=np.float64, order="C")
+            mujoco.mj_fullM(self.sim.model._model, mass_matrix, self.sim.data.qM)
             mass_matrix = np.reshape(mass_matrix, (len(self.sim.data.qvel), len(self.sim.data.qvel)))
             self.mass_matrix = mass_matrix[self.qvel_index, :][:, self.qvel_index]
 

robosuite/demos/demo_domain_randomization.py

@@ -2,7 +2,7 @@
 Script to showcase domain randomization functionality.
 """
 
-import robosuite.utils.macros as macros
+import robosuite.macros as macros
 from robosuite.controllers import load_controller_config
 from robosuite.utils.input_utils import *
 from robosuite.wrappers import DomainRandomizationWrapper

robosuite/demos/demo_video_recording.py

@@ -11,7 +11,7 @@
 import imageio
 import numpy as np
 
-import robosuite.utils.macros as macros
+import robosuite.macros as macros
 from robosuite import make
 
 # Set the image convention to opencv so that the images are automatically rendered "right side up" when using imageio

robosuite/environments/base.py

@@ -1,19 +1,12 @@
 from collections import OrderedDict
 
 import numpy as np
-from mujoco_py import MjRenderContextOffscreen, MjSim, load_model_from_xml
 
-import robosuite.utils.macros as macros
+import robosuite.macros as macros
 from robosuite.models.base import MujocoModel
 from robosuite.renderers.base import load_renderer_config
-from robosuite.utils import SimulationError, XMLError
-
-if macros.USE_DM_BINDING:
-    from robosuite.utils import PygameRenderer, OpenCVRenderer
-    from robosuite.utils.binding_utils import MjSim, MjRenderContextOffscreen
-else:
-    from robosuite.renderers.mujoco.mujoco_py_renderer import MujocoPyRenderer
-    from mujoco_py import MjSim, MjRenderContextOffscreen, load_model_from_xml
+from robosuite.utils import OpenCVRenderer, PygameRenderer, SimulationError, XMLError
+from robosuite.utils.binding_utils import MjRenderContextOffscreen, MjSim
 
 REGISTERED_ENVS = {}
 
@@ -103,18 +96,11 @@ def __init__(
         renderer="mujoco",
         renderer_config=None,
     ):
-        if not macros.USE_DM_BINDING:
-            # First, verify that both the on- and off-screen renderers are not being used simultaneously
-            if has_renderer is True and has_offscreen_renderer is True:
-                raise ValueError("the onscreen and offscreen renderers cannot be used simultaneously.")
 
         # Rendering-specific attributes
         self.has_renderer = has_renderer
-        if macros.USE_DM_BINDING:
-            # offscreen renderer needed for on-screen rendering
-            self.has_offscreen_renderer = (has_renderer or has_offscreen_renderer)
-        else:
-            self.has_offscreen_renderer = has_offscreen_renderer
+        # offscreen renderer needed for on-screen rendering
+        self.has_offscreen_renderer = has_renderer or has_offscreen_renderer
         self.render_camera = render_camera
         self.render_collision_mesh = render_collision_mesh
         self.render_visual_mesh = render_visual_mesh
@@ -243,16 +229,9 @@ def _initialize_sim(self, xml_string=None):
         Args:
             xml_string (str): If specified, creates MjSim object from this filepath
         """
-        if macros.USE_DM_BINDING:
-            xml = xml_string if xml_string else self.model.get_xml()
-            # Create the simulation instance
-            self.sim = MjSim.from_xml_string(xml)
-        else:
-            # if we have an xml string, use that to create the sim. Otherwise, use the local model
-            self.mjpy_model = load_model_from_xml(xml_string) if xml_string else self.model.get_model(mode="mujoco_py")
-
-            # Create the simulation instance
-            self.sim = MjSim(self.mjpy_model)
+        xml = xml_string if xml_string else self.model.get_xml()
+        # Create the simulation instance
+        self.sim = MjSim.from_xml_string(xml)
 
         # run a single step to make sure changes have propagated through sim state
         self.sim.forward()
@@ -310,20 +289,8 @@ def _reset_internal(self):
 
         # create visualization screen or renderer
         if self.has_renderer and self.viewer is None:
-            if macros.USE_DM_BINDING:
-                # self.viewer = PygameRenderer(self.sim)
-                self.viewer = OpenCVRenderer(self.sim)
-            else:
-                self.viewer = MujocoPyRenderer(self.sim)
-                self.viewer.viewer.vopt.geomgroup[0] = (1 if self.render_collision_mesh else 0)
-                self.viewer.viewer.vopt.geomgroup[1] = (1 if self.render_visual_mesh else 0)
-
-                # hiding the overlay speeds up rendering significantly
-                self.viewer.viewer._hide_overlay = True
-
-                # make sure mujoco-py doesn't block rendering frames
-                # (see https://github.com/StanfordVL/robosuite/issues/39)
-                self.viewer.viewer._render_every_frame = True
+            # self.viewer = PygameRenderer(self.sim)
+            self.viewer = OpenCVRenderer(self.sim)
 
             # Set the camera angle for viewing
             if self.render_camera is not None:
@@ -333,9 +300,6 @@ def _reset_internal(self):
         if self.has_offscreen_renderer:
             if self.sim._render_context_offscreen is None:
                 render_context = MjRenderContextOffscreen(self.sim, device_id=self.render_gpu_device_id)
-                if not macros.USE_DM_BINDING:
-                    # TODO: we kept this line for consistency with old code with old binding, but should probably remove it
-                    self.sim.add_render_context(render_context)
             self.sim._render_context_offscreen.vopt.geomgroup[0] = 1 if self.render_collision_mesh else 0
             self.sim._render_context_offscreen.vopt.geomgroup[1] = 1 if self.render_visual_mesh else 0
 
@@ -696,7 +660,7 @@ def _destroy_sim(self):
         """
         Destroys the current MjSim instance if it exists
         """
-        if macros.USE_DM_BINDING and (self.sim is not None):
+        if self.sim is not None:
             self.sim.free()
             self.sim = None
 

robosuite/environments/robot_env.py

@@ -3,7 +3,7 @@
 
 import numpy as np
 
-import robosuite.utils.macros as macros
+import robosuite.macros as macros
 from robosuite.controllers import reset_controllers
 from robosuite.environments.base import MujocoEnv
 from robosuite.robots import ROBOT_CLASS_MAPPING

robosuite/utils/macros.py → robosuite/macros.py

@@ -4,15 +4,12 @@
 
 To make sure global reference is maintained, should import these settings as:
 
-`import robosuite.utils.macros as macros`
+`import robosuite.macros as macros`
 """
 
 # Global Mujoco Simulation Parameters
 SIMULATION_TIMESTEP = 0.002  # Internal simulation timestep (in seconds)
 
-# Whether to use the new DeepMind MuJoCo python binding instead of OpenAI mujoco-py binding (default)
-USE_DM_BINDING = True
-
 # Instance Randomization
 # Used if we want to randomize geom groups uniformly per instance -- e.g.: entire robot arm, vs. per-joint geom
 # This should get set to True in your script BEFORE an environment is created or the DR wrapper is used
@@ -34,3 +31,15 @@
 # In general, observations are concatenated together by modality. However, image observations are expensive memory-wise,
 # so we skip concatenating all images together by default, unless this flag is set to True
 CONCATENATE_IMAGES = False
+
+
+try:
+    from robosuite.macros_private import *
+except ImportError:
+    from robosuite.utils.log_utils import log_warning
+
+    log_warning(
+        "No private macro file found!"
+        "\nIt is recommended to use a private macro file"
+        "\nTo setup, run: python robosuite/scripts/setup_macros.py"
+    )

robosuite/models/assets/arenas/bins_arena.xml

@@ -63,9 +63,7 @@
         <geom pos="-0.15 -0.2 -0.4" size="0.01 0.4" type="cylinder" conaffinity="0" contype="0" group="1" name="bin2_leg3_visual" material="table_legs_metal"/>
         <geom pos="0.15 -0.2 -0.4" size="0.01 0.4" type="cylinder" conaffinity="0" contype="0" group="1" name="bin2_leg4_visual" material="table_legs_metal"/>
     </body>
-
-    <light diffuse=".8 .8 .8" dir="0 -.15 -1" directional="false" pos="1 1 4.0" specular="0.3 0.3 0.3" castshadow="false"/>
-    <light diffuse=".8 .8 .8" dir="0 -.15 -1" directional="false" pos="-3. -3. 4.0" specular="0.3 0.3 0.3" castshadow="false"/>
+    <light pos="1.0 1.0 1.5" dir="-0.2 -0.2 -1" specular="0.3 0.3 0.3" directional="true" castshadow="false"/>
     <!-- front view -->
     <camera mode="fixed" name="frontview" pos="1.6 0 1.45" quat="0.56 0.43 0.43 0.56"/>
     <!-- bird view -->

robosuite/models/assets/arenas/empty_arena.xml

@@ -18,8 +18,7 @@
     <geom pos="1.25 -3 1.5" quat="0.7071 -0.7071 0 0" size="1.75 1.5 0.01" type="box" conaffinity="0" contype="0" group="1" name="wall_right_visual" material="walls_mat"/>
     <geom pos="-2 0 1.5" quat="0.5 0.5 0.5 0.5" size="1.5 1.5 0.01" type="box" conaffinity="0" contype="0" group="1" name="wall_rear_visual" material="walls_mat"/>
     <geom pos="3 0 1.5" quat="0.5 0.5 -0.5 -0.5" size="3 1.5 0.01" type="box" conaffinity="0" contype="0" group="1" name="wall_front_visual" material="walls_mat"/>
-    <light diffuse=".8 .8 .8" dir="0 -.15 -1" directional="false" pos="1 1 4.0" specular="0.3 0.3 0.3" castshadow="false"/>
-    <light diffuse=".8 .8 .8" dir="0 -.15 -1" directional="false" pos="-3. -3. 4.0" specular="0.3 0.3 0.3" castshadow="false"/>
+    <light pos="1.0 1.0 1.5" dir="-0.2 -0.2 -1" specular="0.3 0.3 0.3" directional="true" castshadow="false"/>
     <!-- front view -->
     <camera mode="fixed" name="frontview" pos="1.6 0 1.45" quat="0.56 0.43 0.43 0.56"/>
     <!-- bird view -->

robosuite/models/assets/arenas/pegs_arena.xml

@@ -50,9 +50,7 @@
       <geom pos="0 0 0" size="0.02 0.1" type="cylinder" group="0" friction="1 0.005 0.0001"/>
       <geom pos="0 0 0" size="0.02 0.1" type="cylinder" conaffinity="0" contype="0" group="1" material="smetal" />
     </body>
-
-    <light diffuse=".8 .8 .8" dir="0 -.15 -1" directional="false" pos="1 1 4.0" specular="0.3 0.3 0.3" castshadow="false"/>
-    <light diffuse=".8 .8 .8" dir="0 -.15 -1" directional="false" pos="-3. -3. 4.0" specular="0.3 0.3 0.3" castshadow="false"/>
+    <light pos="1.0 1.0 1.5" dir="-0.2 -0.2 -1" specular="0.3 0.3 0.3" directional="true" castshadow="false"/>
     <!-- front view -->
     <camera mode="fixed" name="frontview" pos="1.6 0 1.45" quat="0.56 0.43 0.43 0.56"/>
     <!-- bird view -->

robosuite/models/assets/arenas/table_arena.xml

@@ -38,9 +38,7 @@
       <geom pos="0 0 0" size="0.05 0.1" type="cylinder" conaffinity="0" contype="0" group="1" name="table_leg3_visual" material="table_legs_metal"/>
       <geom pos="0 0 0" size="0.05 0.1" type="cylinder" conaffinity="0" contype="0" group="1" name="table_leg4_visual" material="table_legs_metal"/>
     </body>
-
-    <light name="light1" diffuse=".8 .8 .8" dir="0 -.15 -1" directional="false" pos="1 1 4.0" specular="0.3 0.3 0.3" castshadow="false"/>
-    <light name="light2" diffuse=".8 .8 .8" dir="0 -.15 -1" directional="false" pos="-3. -3. 4.0" specular="0.3 0.3 0.3" castshadow="false"/>
+    <light pos="1.0 1.0 1.5" dir="-0.2 -0.2 -1" specular="0.3 0.3 0.3" directional="true" castshadow="false"/>
     <!-- front view -->
     <camera mode="fixed" name="frontview" pos="1.6 0 1.45" quat="0.56 0.43 0.43 0.56"/>
     <!-- bird view -->
@@ -49,5 +47,6 @@
     <camera mode="fixed" name="agentview" pos="0.5 0 1.35" quat="0.653 0.271 0.271 0.653"/>
     <!-- side view -->
     <camera mode="fixed" name="sideview" pos="-0.05651774593317116 1.2761224129427358 1.4879572214102434" quat="0.009905065491771751 0.006877963156909582 0.5912228352893879 0.806418094001364" />
+
   </worldbody>
-</mujoco>
+</mujoco>

robosuite/models/assets/grippers/jaco_three_finger_gripper.xml

@@ -14,19 +14,19 @@
 
     <tendon>
 		<!--Middlefinger tendons-->
-		<fixed name="thumb_cpl" range="-5 5" stiffness="3.0" springlength="0.2" frictionloss="0.4">
+		<fixed name="thumb_cpl" range="-5 5" stiffness="3.0" springlength="0.2" frictionloss="0.4" limited="true">
 			<joint joint="joint_thumb"  coef="0.4"/>
 			<joint joint="joint_thumb_distal"  coef="-0.4"/>
 		</fixed>
 
 		<!--finger2 tendons-->
-        <fixed name="index_12_cpl" range="-5 5" stiffness="3.0" springlength="0.2" frictionloss="0.4">
+        <fixed name="index_12_cpl" range="-5 5" stiffness="3.0" springlength="0.2" frictionloss="0.4" limited="true">
 			<joint joint="joint_index"  coef="0.4"/>
 			<joint joint="joint_index_distal"  coef="-0.4"/>
 		</fixed>
 
 		<!--Finger1 tendons-->
-        <fixed name="pinky_12_cpl" range="-5 5" stiffness="3.0" springlength="0.2" frictionloss="0.4">
+        <fixed name="pinky_12_cpl" range="-5 5" stiffness="3.0" springlength="0.2" frictionloss="0.4" limited="true">
 			<joint joint="joint_pinky"  coef="0.4"/>
 			<joint joint="joint_pinky_distal"  coef="-0.4"/>
 		</fixed>

robosuite/models/assets/grippers/obj_meshes/rethink_gripper/connector_plate.mtl

@@ -0,0 +1,12 @@
+# Blender 3.3.1 MTL File: 'None'
+# www.blender.org
+
+newmtl Material_001
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.001651 0.001651 0.001651
+Ks 0.500000 0.500000 0.500000
+Ke 0.100000 0.100000 0.100000
+Ni 1.000000
+d 1.000000
+illum 2