Fixes grid origins in TerrainImporter to match Isaac Sim cloner

CONTRIBUTORS.md

@@ -43,6 +43,7 @@ Guidelines for modifications:
 * René Zurbrügg
 * Ritvik Singh
 * Rosario Scalise
+* Shafeef Omar
 
 ## Acknowledgements
 

source/extensions/omni.isaac.orbit/config/extension.toml

@@ -1,7 +1,7 @@
 [package]
 
 # Note: Semantic Versioning is used: https://semver.org/
-version = "0.15.1"
+version = "0.15.2"
 
 # Description
 title = "ORBIT framework for Robot Learning"

source/extensions/omni.isaac.orbit/docs/CHANGELOG.rst

@@ -1,6 +1,22 @@
 Changelog
 ---------
 
+0.15.2 (2024-03-21)
+~~~~~~~~~~~~~~~~~~~
+
+Fixed
+^^^^^
+
+* Fixed the env origins in :meth:`_compute_env_origins_grid` of :class:`omni.isaac.orbit.terrain.TerrainImporter`
+  to match that of Isaac Sim cloner in :class:`omni.isaac.cloner.GridCloner`.
+
+Added
+^^^^^
+
+* Added unit test to ensure consistency between environment origins generated by IsaacSim's Grid Cloner and those
+  produced by the TerrainImporter.
+
+
 0.15.1 (2024-03-19)
 ~~~~~~~~~~~~~~~~~~~
 

source/extensions/omni.isaac.orbit/omni/isaac/orbit/terrains/terrain_importer.py

@@ -347,14 +347,16 @@ def _compute_env_origins_curriculum(self, num_envs: int, origins: torch.Tensor)
         return env_origins
 
     def _compute_env_origins_grid(self, num_envs: int, env_spacing: float) -> torch.Tensor:
-        """Compute the origins of the environments in a grid based on configured spacing."""
+        """Compute the origins of the environments in a grid based on configured spacing"""
         # create tensor based on number of environments
         env_origins = torch.zeros(num_envs, 3, device=self.device)
         # create a grid of origins
-        num_cols = np.floor(np.sqrt(num_envs))
-        num_rows = np.ceil(num_envs / num_cols)
-        xx, yy = torch.meshgrid(torch.arange(num_rows), torch.arange(num_cols), indexing="xy")
-        env_origins[:, 0] = env_spacing * xx.flatten()[:num_envs] - env_spacing * (num_rows - 1) / 2
-        env_origins[:, 1] = env_spacing * yy.flatten()[:num_envs] - env_spacing * (num_cols - 1) / 2
+        num_rows = np.ceil(num_envs / int(np.sqrt(num_envs)))
+        num_cols = np.ceil(num_envs / num_rows)
+        ii, jj = torch.meshgrid(
+            torch.arange(num_rows, device=self.device), torch.arange(num_cols, device=self.device), indexing="ij"
+        )
+        env_origins[:, 0] = -(ii.flatten()[:num_envs] - (num_rows - 1) / 2) * env_spacing
+        env_origins[:, 1] = (jj.flatten()[:num_envs] - (num_cols - 1) / 2) * env_spacing
         env_origins[:, 2] = 0.0
         return env_origins

source/extensions/omni.isaac.orbit/test/terrains/test_grid_cloner.py

@@ -0,0 +1,104 @@
+# Copyright (c) 2022-2024, The ORBIT Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+"""
+This script checks whether the env origins generated by the TerrainImporter for flat
+ground and Isaac SimGrid Cloner are the same.
+"""
+
+from __future__ import annotations
+
+"""Launch Isaac Sim Simulator first."""
+
+from omni.isaac.orbit.app import AppLauncher
+
+# launch omniverse app
+app_launcher = AppLauncher(headless=True)
+simulation_app = app_launcher.app
+
+"""Rest everything follows."""
+
+import torch
+import unittest
+
+import omni.isaac.core.utils.prims as prim_utils
+import omni.isaac.core.utils.stage as stage_utils
+from omni.isaac.cloner import GridCloner
+
+import omni.isaac.orbit.sim as sim_utils
+from omni.isaac.orbit.terrains import TerrainImporter, TerrainImporterCfg
+
+
+def get_grid_cloner_env_origins(num_envs: int = 1, env_spacing: float = 3.0):
+    """Get env_origins generated by IsaacSim GridCloner (grid_cloner.py)."""
+    cloner = GridCloner(spacing=env_spacing)
+    cloner.define_base_env("/World/envs")
+    envs_prim_paths = cloner.generate_paths("/World/envs/env", num_paths=num_envs)
+    prim_utils.define_prim("/World/envs/env_0")
+    isaac_sim_env_origins = torch.tensor(
+        cloner.clone(source_prim_path="/World/envs/env_0", prim_paths=envs_prim_paths, replicate_physics=True),
+        device="cuda:0",
+        dtype=torch.float32,
+    )
+
+    return isaac_sim_env_origins
+
+
+def get_terrain_importer_env_origins(num_envs: int = 1, env_spacing: float = 3.0):
+    """Get env_origins generated by TerrainImporter (_compute_env_origins_grid())."""
+    terrain_importer_cfg = TerrainImporterCfg(
+        num_envs=num_envs,
+        env_spacing=env_spacing,
+        prim_path="/World/ground",
+        terrain_type="plane",
+        terrain_generator=None,
+    )
+    terrain_importer = TerrainImporter(terrain_importer_cfg)
+    return terrain_importer.env_origins
+
+
+class TestGridCloner(unittest.TestCase):
+    """Test for grid cloning."""
+
+    def setUp(self):
+        """Create a blank new stage for each test."""
+        # Create a new stage
+        stage_utils.create_new_stage()
+        # Load kit helper
+        self.sim = sim_utils.SimulationContext(sim_utils.SimulationCfg(dt=0.005))
+
+    def tearDown(self):
+        """Stops simulator after each test."""
+        # stop simulation
+        self.sim.stop()
+        # clear the stage
+        self.sim.clear_instance()
+
+    """
+    Tests
+    """
+
+    def test_env_origins(self):
+        """Test env origins generated by TerrainImporter & IsaacSim GridCloner to check consistency."""
+        # fix env spacing for convenience
+        env_spacing = 2.17
+        # iterate over different number of environments
+        for num_envs in [1, 4, 7, 12]:
+            with self.subTest(num_envs=num_envs):
+                with sim_utils.build_simulation_context(auto_add_lighting=True) as sim:
+                    grid_cloner_origins = get_grid_cloner_env_origins(num_envs, env_spacing)
+                    terrain_origins = get_terrain_importer_env_origins(num_envs, env_spacing)
+                    self.assertTrue(torch.all(terrain_origins == grid_cloner_origins))
+
+                    sim.reset()
+                    for _ in range(5):
+                        sim.step()
+
+
+if __name__ == "__main__":
+    # run main
+    unittest.main(verbosity=2, exit=False)
+    # close sim app
+    simulation_app.close()