title: ScanBot: Towards Intelligent Surface Scanning in Embodied Robotic
    Systems
summary: We introduce ScanBot, a novel dataset designed for instruction-conditioned,
  high-precision surface scanning in robotic systems. In contrast to existing
  robot learning datasets that focus on coarse tasks such as grasping,
  navigation, or dialogue, ScanBot targets the high-precision demands of
  industrial laser scanning, where sub-millimeter path continuity and parameter
  stability are critical. The dataset covers laser scanning trajectories executed
  by a robot across 12 diverse objects and 6 task types, including full-surface
  scans, geometry-focused regions, spatially referenced parts, functionally
  relevant structures, defect inspection, and comparative analysis. Each scan is
  guided by natural language instructions and paired with synchronized RGB,
  depth, and laser profiles, as well as robot pose and joint states. Despite
  recent progress, existing vision-language action (VLA) models still fail to
  generate stable scanning trajectories under fine-grained instructions and
  real-world precision demands. To investigate this limitation, we benchmark a
  range of multimodal large language models (MLLMs) across the full
  perception-planning-execution loop, revealing persistent challenges in
  instruction-following under realistic constraints.
paper_authors._id: 6833ed0f924393051ae89d09
paper_authors.name: Zhiling Chen
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-05-26T08:09:23.482Z
paper_authors._id: 661b42ee2b14565c7af4ff73
paper_authors.avatarUrl: /avatars/a58ced9fd5f3e86ef5ebb43ce1a7af29.svg
paper_authors.fullname: zhiling chen
paper_authors.type: user
paper_authors.user: ed1son
paper_authors._id: 6833ed0f924393051ae89d0a
paper_authors.name: Yang Zhang
paper_authors._id: 6833ed0f924393051ae89d0b
paper_authors.name: Fardin Jalil Piran
paper_authors._id: 6833ed0f924393051ae89d0c
paper_authors.name: Qianyu Zhou
paper_authors._id: 6833ed0f924393051ae89d0d
paper_authors.name: Jiong Tang
paper_authors._id: 6833ed0f924393051ae89d0e
paper_authors.name: Farhad Imani
paper_authors.status: extracted_pending
paper_authors.statusLastChangedAt: 2025-05-26T17:59:31.038Z
paper_authors._id: 6834ab8de2a34a2f37676c4b
paper_authors.avatarUrl: /avatars/aa95bbf53a9c55e9148fdfb8d62e57e8.svg
paper_authors.fullname: Farhad Imani
paper_authors.type: user
paper_authors.user: FarhadImani1
paper_title: ScanBot: Towards Intelligent Surface Scanning in Embodied Robotic
    Systems
paper_summary: We introduce ScanBot, a novel dataset designed for instruction-conditioned,
  high-precision surface scanning in robotic systems. In contrast to existing
  robot learning datasets that focus on coarse tasks such as grasping,
  navigation, or dialogue, ScanBot targets the high-precision demands of
  industrial laser scanning, where sub-millimeter path continuity and parameter
  stability are critical. The dataset covers laser scanning trajectories executed
  by a robot across 12 diverse objects and 6 task types, including full-surface
  scans, geometry-focused regions, spatially referenced parts, functionally
  relevant structures, defect inspection, and comparative analysis. Each scan is
  guided by natural language instructions and paired with synchronized RGB,
  depth, and laser profiles, as well as robot pose and joint states. Despite
  recent progress, existing vision-language action (VLA) models still fail to
  generate stable scanning trajectories under fine-grained instructions and
  real-world precision demands. To investigate this limitation, we benchmark a
  range of multimodal large language models (MLLMs) across the full
  perception-planning-execution loop, revealing persistent challenges in
  instruction-following under realistic constraints.
paper_ai_summary: The ScanBot dataset, focusing on instruction-conditioned high-precision robotic surface scanning, showcases challenges for vision-language action models in achieving precise scanning trajectories under real-world constraints.
paper_ai_keywords: ScanBot instruction-conditioned high-precision surface scanning robotic systems laser scanning sub-millimeter path continuity parameter stability multimodal large language models vision-language action models perception-planning-execution loop