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  "story": {
    "story_id": "mp-2026-09-18-010",
    "source_story_id": "tmp-story-skipvla-classical-free-space",
    "edition_id": "mp-2026-09-18-morning-0071",
    "edition_url": "https://themachinepress.com/edition/2026-09-18",
    "position": 10,
    "story_type": "dispatch",
    "section": "robotics",
    "editorial_classification": "editorial",
    "headline": "Classical Planning Skipped the Easy VLA Steps",
    "slug": "classical-planning-skipped-the-easy-vla-steps",
    "dek": "SkipVLA ran the learned policy for contact and a motion planner for free space, completing tasks up to 2.5× faster.",
    "summary": "SkipVLA ran the learned policy for contact and a motion planner for free space, completing tasks up to 2.5× faster.",
    "body_text": "A generalist robot policy is useful when meaning and contact matter, but expensive for every centimeter of free-space travel. SkipVLA reuses a frozen vision-language backbone to predict target poses, sends collision-free motion between them to a classical planner, and queries the VLA only for grasping and placing. Across 13 LIBERO tasks and three physical pick-and-place tasks on a six-degree-of-freedom arm, the hybrid matched task success while cutting completion time by as much as 2.5 times and reducing energy use.",
    "why_it_matters": "SkipVLA ran the learned policy for contact and a motion planner for free space, completing tasks up to 2.5× faster.",
    "limitations": [
      "SkipVLA reuses a frozen vision-language backbone to predict target poses, sends collision-free motion between them to a classical planner, and queries the VLA only for grasping and placing."
    ],
    "importance": 8,
    "canonical_url": "https://themachinepress.com/story/mp-2026-09-18-010/classical-planning-skipped-the-easy-vla-steps",
    "json_url": "https://themachinepress.com/story/mp-2026-09-18-010.json",
    "first_published_at": "2026-09-18T09:00:00.000-04:00",
    "modified_at": "2026-09-18T09:00:00.000-04:00",
    "content_status": "new",
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    "carryover_reason": null,
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        "text": "SkipVLA ran the learned policy for contact and a motion planner for free space, completing tasks up to 2.5× faster.",
        "source_ids": [
          "source-2026-09-18-010"
        ],
        "qualification": "SkipVLA reuses a frozen vision-language backbone to predict target poses, sends collision-free motion between them to a classical planner, and queries the VLA only for grasping and placing."
      }
    ],
    "source_ids": [
      "source-2026-09-18-010"
    ],
    "tags": [
      "VLA",
      "motion planning",
      "robot efficiency"
    ],
    "image_url": null,
    "corrections": []
  },
  "sources": [
    {
      "source_id": "source-2026-09-18-010",
      "title": "arXiv preprint 2609.20648",
      "publisher": "arXiv",
      "url": "https://arxiv.org/abs/2609.20648",
      "canonical_url": "https://arxiv.org/abs/2609.20648",
      "source_type": "primary_research",
      "is_primary_source": true,
      "published_at": "2026-09-17T12:28:31.000-04:00",
      "accessed_at": "2026-09-18T08:26:40.599-04:00",
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  "corrections": [],
  "publisher": {
    "name": "The Machine Press",
    "url": "https://themachinepress.com",
    "description": "A daily newspaper for the age of artificial intelligence."
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  "cite_this_report": {
    "title": "Classical Planning Skipped the Easy VLA Steps",
    "publisher": "The Machine Press",
    "published_at": "2026-09-18T09:00:00.000-04:00",
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