How Should a Robot Configure Its Laser Scanner for Inspection?
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Abstract (arXiv)
Robotic inspection relies on accurate sensing to acquire high-fidelity geometric measurements for defect detection and metrology. While prior work has focused on robot motion and viewpoint planning, how to configure sensing parameters remains largely underexplored, despite their decisive impact on measurement quality. We propose SenseHD, a robotic sensing system that formulates scanner configuration as an instruction-conditioned sensing decision. Instead of predicting precise parameter values, SenseHD treats sensing parameters as discrete sensing actions and selects stable sensing regimes through hyperdimensional associative memory. Experiments on a real robotic inspection platform demonstrate that SenseHD robustly selects appropriate sensing configurations and significantly improves inspection reliability, while remaining lightweight and efficient compared to baseline methods.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 8 of its 18 references that are in the map. First posted on arXiv 19 Jun 2026.
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References · 8
- 2015Deep Residual Learning for Image Recognitioncited by 51,809
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
- 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
- 2025Qwen3-VL Technical Reportcited by 2,534
- 2024YOLO-World: Real-Time Open-Vocabulary Object Detectioncited by 498
- 2016Revisiting Active Perceptioncited by 90
- 2020Classification using Hyperdimensional Computing: A Reviewcited by 60
- 2019Camera Exposure Control for Robust Robot Vision with Noise-Aware Image Quality Assessmentcited by 10
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