constrained planning, robot segmentation

tests/motion_gen_api_test.py

@@ -14,11 +14,10 @@ import pytest
 import torch
 
 # CuRobo
-from curobo.geom.types import WorldConfig
 from curobo.types.base import TensorDeviceType
 from curobo.types.math import Pose
-from curobo.types.robot import JointState, RobotConfig
-from curobo.util_file import get_robot_configs_path, get_world_configs_path, join_path, load_yaml
+from curobo.types.robot import JointState
+from curobo.util_file import get_robot_configs_path, join_path, load_yaml
 from curobo.wrap.reacher.motion_gen import MotionGen, MotionGenConfig, MotionGenPlanConfig
 
 
@@ -60,3 +59,49 @@ def test_motion_gen_attach_obstacle_offset(motion_gen):
         start_state, [obstacle], world_objects_pose_offset=offset_pose
     )
     assert True
+
+
+def test_motion_gen_lock_js_update():
+    tensor_args = TensorDeviceType()
+    world_file = "collision_table.yml"
+    robot_file = "franka_mobile.yml"
+    robot_config = load_yaml(join_path(get_robot_configs_path(), robot_file))["robot_cfg"]
+    robot_config["kinematics"]["lock_joints"] = {"base_x": 0.0, "base_y": 0.0, "base_z": 0.0}
+    motion_gen_config = MotionGenConfig.load_from_robot_config(
+        robot_config,
+        world_file,
+        tensor_args,
+        use_cuda_graph=True,
+    )
+    motion_gen_instance = MotionGen(motion_gen_config)
+    motion_gen_instance.warmup()
+    retract_cfg = motion_gen_instance.get_retract_config()
+    start_state = JointState.from_position(retract_cfg.view(1, -1))
+
+    kin_state = motion_gen_instance.compute_kinematics(start_state)
+    ee_pose = kin_state.ee_pose.clone()
+
+    # test motion gen:
+    plan_start = start_state.clone()
+    plan_start.position[..., :-2] += 0.1
+    result = motion_gen_instance.plan_single(plan_start, ee_pose)
+
+    assert result.success.item()
+    lock_js = {"base_x": 1.0, "base_y": 0.0, "base_z": 0.0}
+    motion_gen_instance.update_locked_joints(lock_js, robot_config)
+
+    kin_state_new = motion_gen_instance.compute_kinematics(start_state)
+    ee_pose_shift = kin_state_new.ee_pose.clone()
+
+    assert torch.norm(ee_pose.position[..., 0] - ee_pose_shift.position[..., 0]).item() == 1.0
+    assert torch.norm(ee_pose.position[..., 1:] - ee_pose_shift.position[..., 1:]).item() == 0.0
+
+    # test motion gen with new lock state:
+
+    result = motion_gen_instance.plan_single(plan_start, ee_pose_shift)
+    assert result.success.item()
+
+    result = motion_gen_instance.plan_single(
+        plan_start, ee_pose, MotionGenPlanConfig(max_attempts=3)
+    )
+    assert result.success.item() == False