update curobo sphere fit

[matafela]

Description

visualization: motion_generator.planner.visualize_collision_models(control_part) （only support curobo)

TODO:

• curobo planner use dexsim sphere fit.
• curobo world

Type of change

• Enhancement (non-breaking change which improves an existing functionality)

Checklist

• I have run the black . command to format the code base.
• I have made corresponding changes to the documentation
• I have added tests that prove my fix is effective or that my feature works
• Dependencies have been updated, if applicable.

[greptile-apps]

Greptile Summary

The PR replaces cuRobo’s configurable sphere/world fitting with DexSim MorphIt robot spheres and tensor-backed ESDF voxel worlds, and adds collision-model visualization.

• Removes the obsolete benchmark auto_gen.fit_type settings, resolving the previously reported constructor failure.
• Adds versioned voxel-world caching, dynamic voxel obstacle handling, and multi-environment scene cloning.
• Updates documentation, examples, benchmark suites, and planner tests for the new collision representation.

Confidence Score: 5/5

The PR appears safe to merge because the previously reported benchmark configuration failure is resolved and no blocking failure remains.

No blocking failure remains.

Important Files Changed

Filename	Overview
embodichain/lab/sim/planners/curobo/curobo_planner.py	Integrates versioned voxel-scene generation and caching, runtime robot configuration, scene cloning, and collision-model visualization; the previously incompatible benchmark option has been removed from the suites.
embodichain/lab/sim/planners/curobo/curobo_yaml.py	Replaces cuRobo sphere/world fitting with DexSim MorphIt and VisACD-backed voxel generation and adds visualization helpers.
scripts/benchmark/motion_generation/suites/smoke.yaml	Removes the obsolete fit_type value while preserving supported sphere-fitting settings.
scripts/benchmark/motion_generation/suites/coverage.yaml	Removes the obsolete fit_type value while preserving supported sphere-fitting settings.
tests/sim/planners/test_curobo_planner.py	Updates planner tests for fixed MorphIt fitting, voxel collision scenes, cache behavior, and visualization.
tests/sim/planners/test_curobo_integration.py	Updates integration coverage for the revised cuRobo collision-model pipeline.

Flowchart

%%{init: {'theme': 'neutral'}}%%
flowchart LR
  A[Robot URDF and link meshes] --> B[DexSim MorphIt sphere fitting]
  B --> C[Versioned robot YAML cache]
  D[RigidObject meshes and poses] --> E[VisACD convex decomposition]
  E --> F[ESDF voxel generation]
  F --> G[Versioned tensor cache]
  C --> H[cuRobo MotionPlanner]
  G --> H
  H --> I[Collision-aware trajectory]
  C --> J[Collision-model visualization]
  G --> J

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_{Reviews (3): Last reviewed commit: "update" | Re-trigger Greptile}

[Copilot]

Pull request overview

This PR updates EmbodiChain’s cuRobo planner integration to use DexSim’s MorphIt sphere fitting for both robot-link and world obstacle collision spheres, and adds runtime support for cuRobo V2 sphere obstacles by registering an analytic sphere SDF into cuRobo’s Warp-based collision checker. It also adds cached collision-model visualization utilities, updates documentation, and expands the test suite to cover the new behavior (including temporarily disabling cuRobo self-collision checking).

Changes:

• Switch sphere fitting for robot/world YAML generation from cuRobo’s fitter to DexSim MorphIt with fixed convex-hull limits.
• Add analytic sphere obstacle storage + cuRobo runtime hooks so sphere scene obstacles are actually checked at runtime.
• Add visualization helpers for cached robot/world collision spheres and extend tests/docs accordingly.

Reviewed changes

Copilot reviewed 6 out of 6 changed files in this pull request and generated 4 comments.

Show a summary per file

File	Description
tests/sim/planners/test_curobo_planner.py	Adds tests for DexSim MorphIt fitting, runtime sphere registration/validation, self-collision disabling, and visualization.
examples/sim/planners/curobo_planner.py	Updates the demo to use sphere obstacle representation and optionally visualize cached collision models.
embodichain/lab/sim/planners/curobo/curobo_yaml.py	Switches YAML generation sphere fitting to DexSim + Open3D and adds collision-model visualization utilities.
embodichain/lab/sim/planners/curobo/curobo_sphere_data.py	Introduces analytic sphere obstacle storage and Warp SDF helpers for cuRobo’s generic collision checker.
embodichain/lab/sim/planners/curobo/curobo_planner.py	Wires in runtime sphere support registration, disables self-collision checks, validates runtime sphere loading, and adds visualization entrypoint.
docs/source/overview/sim/planners/curobo_planner.md	Documents DexSim MorphIt usage, runtime sphere support, visualization, and the temporary self-collision disablement.

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[Copilot]

Pull request overview

Copilot reviewed 10 out of 10 changed files in this pull request and generated no new comments.

Suppressed comments (2)

examples/sim/planners/curobo_planner.py:465

• The comment block says this is a "W1-specific IK diagnostic", but the compute_ik(...) call now runs unconditionally for all robots, so the comment is misleading. Also, leaving commented-out debugger lines (ipdb.set_trace) in an example reads like leftover debug scaffolding.

    # if robot_type == "w1":
    # Keep the W1-specific IK diagnostic batched so it remains useful when
    # checking solver and cuRobo reachability across multiple environments.
    # import ipdb; ipdb.set_trace()
    init_qpos = torch.tensor(

embodichain/lab/sim/planners/curobo/curobo_planner.py:1563

• torch.load(..., weights_only=True) is used without a compatibility fallback. Elsewhere in the codebase (e.g. embodichain/lab/sim/planners/neural_planner.py:_safe_torch_load) the project falls back to weights_only=False when running on older PyTorch versions or when weights_only=True cannot deserialize the file. Without a fallback, loading an existing world cache will raise on those setups and break planner init.

        cache_path = os.path.join(cache_dir, f"world_{cache_key}.pt")
        if not auto.force and os.path.exists(cache_path):
            logger.log_info(f"cuRobo voxel world cache hit: {cache_path}")
            scene_data = torch.load(cache_path, map_location="cpu", weights_only=True)
        else:

[Copilot]

Pull request overview

Copilot reviewed 10 out of 10 changed files in this pull request and generated no new comments.

Suppressed comments (5)

examples/sim/planners/curobo_planner.py:467

• Commented-out debug code (ipdb.set_trace()) and a commented conditional were added to the example. Leaving these in the repo makes the example harder to follow and risks reintroducing debug statements later.

    # if robot_type == "w1":
    # Keep the W1-specific IK diagnostic batched so it remains useful when
    # checking solver and cuRobo reachability across multiple environments.
    # import ipdb; ipdb.set_trace()
    init_qpos = torch.tensor(
        robot.cfg.init_qpos, dtype=torch.float32, device=robot.device
    )

embodichain/lab/sim/planners/curobo/curobo_planner.py:1563

• torch.load(..., weights_only=True) is used without a compatibility fallback. Because EmbodiChain does not pin a minimum PyTorch version (and older versions don't support weights_only), this can raise TypeError and break cuRobo world-cache reuse. The codebase already uses a try/fallback pattern (e.g. embodichain/lab/sim/planners/neural_planner.py:_safe_torch_load).

        if not auto.force and os.path.exists(cache_path):
            logger.log_info(f"cuRobo voxel world cache hit: {cache_path}")
            scene_data = torch.load(cache_path, map_location="cpu", weights_only=True)
        else:

embodichain/lab/sim/planners/curobo/curobo_planner.py:1581

• deepcopy(scene_data) will deep-copy the cached voxel tensors, which can be extremely expensive in CPU memory/time before they are moved to GPU. Since you only need a device-mapped runtime view, prefer a shallow copy of the dict and rebuild the per-voxel entries while moving feature_tensor to self._curobo_device.

        runtime_data = deepcopy(scene_data)
        for voxel in runtime_data.get("voxel", {}).values():
            voxel["feature_tensor"] = voxel["feature_tensor"].to(
                device=self._curobo_device, dtype=torch.float16
            )
        return self._bindings.Scene.create(runtime_data)

docs/source/overview/sim/planners/curobo_planner.md:242

• The documentation says planner.visualize_collision_models(...) shows an "Open3D overlay" and instructs readers to close an Open3D window, but the implementation overlays temporary actors in the DexSim scene and blocks on a terminal input() prompt. This mismatch will confuse users.

For an Open3D overlay of the live robot/obstacle meshes and the exact spheres
read back from those YAML caches, call
`planner.visualize_collision_models(control_part)`. Robot sphere centers are
transformed by the simulator's live link poses. The interactive cuRobo example
calls this once after planner initialization; close the Open3D window to continue.

embodichain/lab/sim/planners/curobo/curobo_yaml.py:179

• The generate_curobo_robot_yaml docstring lists ImportError only for DexSim/Open3D, but the function also imports cuRobo (UrdfRobotParser) and will raise ImportError if cuRobo is missing. The raised-exception documentation should match actual imports.

    Raises:
        ImportError: If DexSim or Open3D is not installed.
        RuntimeError: If CUDA is unavailable or no spheres could be fitted.