Refactor duplicated code in solver modules

embodichain/lab/sim/solvers/base_solver.py

@@ -76,6 +76,19 @@ class SolverCfg:
     def init_solver(self, device: torch.device, **kwargs) -> "BaseSolver":
         pass
 
+    def _get_tcp_as_numpy(self) -> np.ndarray:
+        """Convert TCP to numpy array.
+
+        This helper method handles the conversion of TCP from torch.Tensor to numpy
+        if needed. Used by subclass init_solver methods to set TCP on the solver.
+
+        Returns:
+            np.ndarray: The TCP as a numpy array.
+        """
+        if isinstance(self.tcp, torch.Tensor):
+            return self.tcp.cpu().numpy()
+        return self.tcp
+
     @classmethod
     def from_dict(cls, init_dict: Dict[str, Any]) -> "SolverCfg":
         """Initialize the configuration from a dictionary."""

embodichain/lab/sim/solvers/differential_solver.py

@@ -89,11 +89,7 @@ def init_solver(
         )
 
         # Set the Tool Center Point (TCP) for the solver
-        if isinstance(self.tcp, torch.Tensor):
-            tcp = self.tcp.cpu().numpy()
-        else:
-            tcp = self.tcp
-        solver.set_tcp(tcp)
+        solver.set_tcp(self._get_tcp_as_numpy())
 
         return solver
 

embodichain/lab/sim/solvers/opw_solver.py

@@ -95,11 +95,7 @@ def init_solver(
         solver = OPWSolver(cfg=self, device=device, **kwargs)
 
         # Set the Tool Center Point (TCP) for the solver
-        if isinstance(self.tcp, torch.Tensor):
-            tcp = self.tcp.cpu().numpy()
-        else:
-            tcp = self.tcp
-        solver.set_tcp(tcp)
+        solver.set_tcp(self._get_tcp_as_numpy())
 
         return solver
 

embodichain/lab/sim/solvers/pink_solver.py

@@ -24,6 +24,10 @@
     lazy_import_pinocchio,
     lazy_import_pink,
 )
+from embodichain.lab.sim.utility.solver_utils import (
+    build_reduced_pinocchio_robot,
+    compute_pinocchio_fk,
+)
 
 from embodichain.utils import configclass, logger
 from embodichain.lab.sim.solvers import SolverCfg, BaseSolver
@@ -111,12 +115,7 @@ def init_solver(self, **kwargs) -> "PinkSolver":
         solver = PinkSolver(cfg=self, **kwargs)
 
         # Set the Tool Center Point (TCP) for the solver
-        if isinstance(self.tcp, torch.Tensor):
-            tcp = self.tcp.cpu().numpy()
-        else:
-            tcp = self.tcp
-
-        solver.set_tcp(tcp)
+        solver.set_tcp(self._get_tcp_as_numpy())
 
         return solver
 
@@ -162,7 +161,7 @@ def __init__(self, cfg: PinkSolverCfg, **kwargs):
         )  # Degrees of freedom of robot joints
 
         # Get reduced robot model
-        self.robot = self._get_reduce_robot()
+        self.robot = build_reduced_pinocchio_robot(self.entire_robot, self.joint_names)
 
         # Initialize Pink configuration
         self.pink_cfg = self.pink.configuration.Configuration(
@@ -207,26 +206,6 @@ def __init__(self, cfg: PinkSolverCfg, **kwargs):
             self.dexsim_to_pink_ordering = None
             self.pink_to_dexsim_ordering = None
 
-    def _get_reduce_robot(self) -> "pin.RobotWrapper":
-        """Build a reduced robot model by locking all joints except those in self.joint_names.
-
-        Returns:
-            pin.RobotWrapper: The reduced robot model with specified joints unlocked.
-        """
-        pink_joint_names = self.entire_robot.model.names.tolist()
-
-        # Lock all joints except those in self.joint_names and 'universe'
-        fixed_joint_names = [
-            name
-            for name in pink_joint_names
-            if name not in self.joint_names and name != "universe"
-        ]
-
-        reduced_robot = self.entire_robot.buildReducedRobot(
-            list_of_joints_to_lock=fixed_joint_names
-        )
-        return reduced_robot
-
     def reorder_array(
         self, input_array: List[float], reordering_array: List[int]
     ) -> List[float]:
@@ -393,25 +372,7 @@ def _get_fk(
         Returns:
             torch.Tensor: The homogeneous transformation matrix (4x4) of the end-effector (after applying TCP).
         """
-        if isinstance(qpos, torch.Tensor):
-            qpos_np = qpos.detach().cpu().numpy()
-        else:
-            qpos_np = np.array(qpos)
-
-        qpos_np = np.squeeze(qpos_np)
-        if qpos_np.ndim != 1:
-            raise ValueError(f"qpos shape must be (nq,), but got {qpos_np.shape}")
-
-        self.pin.forwardKinematics(self.robot.model, self.robot.data, qpos_np)
-
-        # Retrieve the pose of the specified link
-        frame_index = self.robot.model.getFrameId(self.end_link_name)
-        joint_index = self.robot.model.frames[frame_index].parent
-        xpos_se3 = self.robot.data.oMi.tolist()[joint_index]
-
-        xpos = np.eye(4)
-        xpos[:3, :3] = xpos_se3.rotation
-        xpos[:3, 3] = xpos_se3.translation.T
-
-        result = np.dot(xpos, self.tcp_xpos)
+        result = compute_pinocchio_fk(
+            self.pin, self.robot, qpos, self.end_link_name, self.tcp_xpos
+        )
         return torch.from_numpy(result)

embodichain/lab/sim/solvers/pinocchio_solver.py

@@ -29,6 +29,11 @@
     lazy_import_casadi,
     # lazy_import_pinocchio_casadi,
 )
+from embodichain.lab.sim.utility.solver_utils import (
+    build_reduced_pinocchio_robot,
+    validate_iteration_params,
+    compute_pinocchio_fk,
+)
 
 
 if TYPE_CHECKING:
@@ -72,12 +77,7 @@ def init_solver(self, **kwargs) -> "PinocchioSolver":
         solver = PinocchioSolver(cfg=self, **kwargs)
 
         # Set the Tool Center Point (TCP) for the solver
-        if isinstance(self.tcp, torch.Tensor):
-            tcp = self.tcp.cpu().numpy()
-        else:
-            tcp = self.tcp
-
-        solver.set_tcp(tcp)
+        solver.set_tcp(self._get_tcp_as_numpy())
 
         return solver
 
@@ -121,7 +121,7 @@ def __init__(self, cfg: PinocchioSolverCfg, **kwargs):
         )  # Degrees of freedom of robot joints
 
         # Build reduced robot model (only relevant joints unlocked)
-        self.robot = self._get_reduce_robot()
+        self.robot = build_reduced_pinocchio_robot(self.entire_robot, self.joint_names)
         self.joint_names = self.robot.model.names.tolist()[
             1:
         ]  # Exclude 'universe' joint
@@ -221,26 +221,6 @@ def __init__(self, cfg: PinocchioSolverCfg, **kwargs):
         self.root_base_xpos[:3, :3] = root_base_pose.rotation
         self.root_base_xpos[:3, 3] = root_base_pose.translation.T
 
-    def _get_reduce_robot(self) -> "pin.RobotWrapper":
-        """Build a reduced robot model by locking all joints except those in self.joint_names.
-
-        Returns:
-            pin.RobotWrapper: The reduced robot model with specified joints unlocked.
-        """
-        all_joint_names = self.entire_robot.model.names.tolist()
-
-        # Lock all joints except those in self.joint_names and 'universe'
-        fixed_joint_names = [
-            name
-            for name in all_joint_names
-            if name not in self.joint_names and name != "universe"
-        ]
-
-        reduced_robot = self.entire_robot.buildReducedRobot(
-            list_of_joints_to_lock=fixed_joint_names
-        )
-        return reduced_robot
-
     def set_tcp(self, tcp: np.ndarray):
         self.tcp = tcp
 
@@ -290,25 +270,10 @@ def set_iteration_params(
         Returns:
             bool: True if all parameters are valid and set, False otherwise.
         """
-        # TODO: Check which parameters are no longer needed.
         # Validate parameters
-        if pos_eps <= 0:
-            logger.log_warning("Pos epsilon must be positive.")
-            return False
-        if rot_eps <= 0:
-            logger.log_warning("Rot epsilon must be positive.")
-            return False
-        if max_iterations <= 0:
-            logger.log_warning("Max iterations must be positive.")
-            return False
-        if dt <= 0:
-            logger.log_warning("Time step must be positive.")
-            return False
-        if damp < 0:
-            logger.log_warning("Damping factor must be non-negative.")
-            return False
-        if num_samples <= 0:
-            logger.log_warning("Number of samples must be positive.")
+        if not validate_iteration_params(
+            pos_eps, rot_eps, max_iterations, dt, damp, num_samples
+        ):
             return False
 
         # Set parameters if all are valid
@@ -620,25 +585,6 @@ def _get_fk(
         Returns:
             np.ndarray: The resulting end-effector pose as a (4, 4) homogeneous transformation matrix.
         """
-        if isinstance(qpos, torch.Tensor):
-            qpos_np = qpos.detach().cpu().numpy()
-        else:
-            qpos_np = np.array(qpos)
-
-        qpos_np = np.squeeze(qpos_np)
-        if qpos_np.ndim != 1:
-            raise ValueError(f"qpos shape must be (nq,), but got {qpos_np.shape}")
-
-        self.pin.forwardKinematics(self.robot.model, self.robot.data, qpos_np)
-
-        # Retrieve the pose of the specified link
-        frame_index = self.robot.model.getFrameId(self.end_link_name)
-        joint_index = self.robot.model.frames[frame_index].parent
-        xpos_se3 = self.robot.data.oMi.tolist()[joint_index]
-
-        xpos = np.eye(4)
-        xpos[:3, :3] = xpos_se3.rotation
-        xpos[:3, 3] = xpos_se3.translation.T
-
-        result = np.dot(xpos, self.tcp_xpos)
-        return result
+        return compute_pinocchio_fk(
+            self.pin, self.robot, qpos, self.end_link_name, self.tcp_xpos
+        )

embodichain/lab/sim/solvers/pytorch_solver.py

@@ -23,6 +23,7 @@
 from embodichain.utils import configclass, logger
 from embodichain.lab.sim.solvers import SolverCfg, BaseSolver
 from embodichain.lab.sim.solvers.qpos_seed_sampler import QposSeedSampler
+from embodichain.lab.sim.utility.solver_utils import validate_iteration_params
 
 if TYPE_CHECKING:
     from typing import Self
@@ -90,11 +91,7 @@ def init_solver(
         solver = PytorchSolver(cfg=self, device=device, **kwargs)
 
         # Set the Tool Center Point (TCP) for the solver
-        if isinstance(self.tcp, torch.Tensor):
-            tcp = self.tcp.cpu().numpy()
-        else:
-            tcp = self.tcp
-        solver.set_tcp(tcp)
+        solver.set_tcp(self._get_tcp_as_numpy())
 
         return solver
 
@@ -227,23 +224,9 @@ def set_iteration_params(
             bool: True if all parameters are valid and set, False otherwise.
         """
         # Validate parameters
-        if pos_eps <= 0:
-            logger.log_warning("Pos epsilon must be positive.")
-            return False
-        if rot_eps <= 0:
-            logger.log_warning("Rot epsilon must be positive.")
-            return False
-        if max_iterations <= 0:
-            logger.log_warning("Max iterations must be positive.")
-            return False
-        if dt <= 0:
-            logger.log_warning("Time step must be positive.")
-            return False
-        if damp < 0:
-            logger.log_warning("Damping factor must be non-negative.")
-            return False
-        if num_samples <= 0:
-            logger.log_warning("Number of samples must be positive.")
+        if not validate_iteration_params(
+            pos_eps, rot_eps, max_iterations, dt, damp, num_samples
+        ):
             return False
 
         # Set parameters if all are valid

embodichain/lab/sim/solvers/srs_solver.py

@@ -93,11 +93,7 @@ def init_solver(
         solver = SRSSolver(cfg=self, num_envs=num_envs, device=device, **kwargs)
 
         # Set the Tool Center Point (TCP) for the solver
-        if isinstance(self.tcp, torch.Tensor):
-            tcp = self.tcp.cpu().numpy()
-        else:
-            tcp = self.tcp
-        solver.set_tcp(tcp)
+        solver.set_tcp(self._get_tcp_as_numpy())
 
         return solver