{"ID":2884689,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.06207","arxiv_id":"2508.06207","title":"Toward Context-Aware Exoskeleton Assistance: Integrating Computer Vision Payload Estimation with a User-Centric Optimization Space","abstract":"Back-support exoskeletons (BSEs) mitigate musculoskeletal strain, yet their efficacy depends on precise, context-aware modulation. This paper introduces a user-centric optimization framework and a vision-based adaptive control strategy for industrial BSEs. First, we constructed a multi-metric optimization space, integrating electromyography reduction, perceived discomfort, and user preference, through baseline experiments with 12 subjects. This revealed a non-linear relationship between optimal assistance and payload. Second, we developed a predictive computer vision pipeline using a Vision Transformer (DINOv2) to estimate payloads before lifting, effectively overcoming actuation latency. Validation with 12 subjects confirmed the system's robustness, achieving over 82% estimation accuracy. Crucially, the adaptive controller reduced peak back muscle activation by up to 23% compared to static baselines while optimizing user comfort. These results validate the proposed framework, demonstrating that pre-lift environmental perception and user-centric optimization significantly enhance physical assistance and human-robot interaction in industrial settings.","short_abstract":"Back-support exoskeletons (BSEs) mitigate musculoskeletal strain, yet their efficacy depends on precise, context-aware modulation. This paper introduces a user-centric optimization framework and a vision-based adaptive control strategy for industrial BSEs. First, we constructed a multi-metric optimization space, integr...","url_abs":"https://arxiv.org/abs/2508.06207","url_pdf":"https://arxiv.org/pdf/2508.06207v2","authors":"[\"Andrea Dal Prete\",\"Seyram Ofori\",\"Chan Yon Sin\",\"Ashwin Narayan\",\"Ding Shuo\",\"Francesco Braghin\",\"Marta Gandolla\",\"Haoyong Yu\"]","published":"2025-08-08T10:39:40Z","proceeding":"cs.RO","tasks":"[\"cs.RO\"]","methods":"[\"Vision Transformer\",\"Transformer\"]","has_code":false}