Add support for older warp versions (<1.0.0)

CHANGELOG.md

@@ -10,6 +10,14 @@ its affiliates is strictly prohibited.
 -->
 # Changelog
 
+## Latest Commit
+
+### BugFixes & Misc.
+- Add support for older warp versions (<1.0.0) as it's not possible to run older isaac sim with
+newer warp versions.
+- Add override option to mpc dataclass.
+- Fix bug in ``PoseCost.forward_pose()`` which caused ``torch_layers_example.py`` to fail.
+
 ## Version 0.7.3
 
 ### New Features

README.md

@@ -19,7 +19,11 @@ Use [Discussions](https://github.com/NVlabs/curobo/discussions) for questions on
 Use [Issues](https://github.com/NVlabs/curobo/issues) if you find a bug.
 
 
-For business inquiries, please visit our website and submit the form: [NVIDIA Research Licensing](https://www.nvidia.com/en-us/research/inquiries/)
+cuRobo's collision-free motion planner is available for commercial applications as a
+MoveIt plugin: [Isaac ROS cuMotion](https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_cumotion)
+
+For business inquiries of this python library, please visit our website and submit the form: [NVIDIA Research Licensing](https://www.nvidia.com/en-us/research/inquiries/)
+
 
 ## Overview
 
@@ -44,9 +48,9 @@ If you found this work useful, please cite the below report,
 
 ```
 @misc{curobo_report23,
-      title={cuRobo: Parallelized Collision-Free Minimum-Jerk Robot Motion Generation}, 
-      author={Balakumar Sundaralingam and Siva Kumar Sastry Hari and Adam Fishman and Caelan Garrett 
-              and Karl Van Wyk and Valts Blukis and Alexander Millane and Helen Oleynikova and Ankur Handa 
+      title={cuRobo: Parallelized Collision-Free Minimum-Jerk Robot Motion Generation},
+      author={Balakumar Sundaralingam and Siva Kumar Sastry Hari and Adam Fishman and Caelan Garrett
+              and Karl Van Wyk and Valts Blukis and Alexander Millane and Helen Oleynikova and Ankur Handa
               and Fabio Ramos and Nathan Ratliff and Dieter Fox},
       year={2023},
       eprint={2310.17274},

examples/torch_layers_example.py

@@ -85,10 +85,13 @@ def get_features(self, q: torch.Tensor, x_des: Optional[Pose] = None):
             kin_state.ee_quaternion,
         ]
         if x_des is not None:
-            pose_distance = self._robot_world.pose_distance(x_des, kin_state.ee_pose)
+            pose_distance = self._robot_world.pose_distance(
+                x_des, kin_state.ee_pose, resize=True
+            ).view(-1, 1)
             features.append(pose_distance)
             features.append(x_des.position)
             features.append(x_des.quaternion)
+
         features = torch.cat(features, dim=-1)
 
         return features
@@ -114,17 +117,25 @@ def forward(self, q: torch.Tensor, x_des: Pose):
 
     def loss(self, x_des: Pose, q: torch.Tensor, q_in: torch.Tensor):
         kin_state = self._robot_world.get_kinematics(q)
-        distance = self._robot_world.pose_distance(x_des, kin_state.ee_pose)
-        d_sdf = self._robot_world.collision_constraint(kin_state.link_spheres_tensor.unsqueeze(1))
-        d_self = self._robot_world.self_collision_cost(kin_state.link_spheres_tensor.unsqueeze(1))
+        distance = self._robot_world.pose_distance(x_des, kin_state.ee_pose, resize=True)
+        d_sdf = self._robot_world.collision_constraint(
+            kin_state.link_spheres_tensor.unsqueeze(1)
+        ).view(-1)
+        d_self = self._robot_world.self_collision_cost(
+            kin_state.link_spheres_tensor.unsqueeze(1)
+        ).view(-1)
         loss = 0.1 * torch.linalg.norm(q_in - q, dim=-1) + distance + 100.0 * (d_self + d_sdf)
         return loss
 
     def val_loss(self, x_des: Pose, q: torch.Tensor, q_in: torch.Tensor):
         kin_state = self._robot_world.get_kinematics(q)
-        distance = self._robot_world.pose_distance(x_des, kin_state.ee_pose)
-        d_sdf = self._robot_world.collision_constraint(kin_state.link_spheres_tensor.unsqueeze(1))
-        d_self = self._robot_world.self_collision_cost(kin_state.link_spheres_tensor.unsqueeze(1))
+        distance = self._robot_world.pose_distance(x_des, kin_state.ee_pose, resize=True)
+        d_sdf = self._robot_world.collision_constraint(
+            kin_state.link_spheres_tensor.unsqueeze(1)
+        ).view(-1)
+        d_self = self._robot_world.self_collision_cost(
+            kin_state.link_spheres_tensor.unsqueeze(1)
+        ).view(-1)
         loss = 10.0 * (d_self + d_sdf) + distance
         return loss
 

setup.cfg

@@ -50,7 +50,7 @@ install_requires =
   torch>=1.10
   trimesh
   yourdfpy>=0.0.53
-  warp-lang>=0.11.0
+  warp-lang>=0.9.0
   scipy>=1.7.0
   tqdm
   wheel