用机器人+AI协作检测混凝土裂缝，更准更快更安全。
An Exploratory Study on Crack Detection in Concrete through Human-Robot Collaboration
- 用移动机器人搭载AI视觉算法自动找裂缝
- 协作模式下检测准确率提升，操作员负担降低
- 适合核电站等高危环境的智能巡检
核设施结构检测对保障运行安全与完整性至关重要。传统人工检测存在安全风险高、认知负荷大、易受人体局限导致误判等问题。近年来，人工智能（AI）与机器人技术的进步为更安全、高效、精准的检测方法提供了可能。本文探索将AI辅助视觉裂缝检测集成至移动Jackal机器人平台的人机协作（HRC）模式。实验结果表明，该协作方式提升了检测准确性，减轻了操作员工作负担，相比传统人工方法展现出潜在更优的表现。
原文摘要 · Abstract (English)
Structural inspection in nuclear facilities is vital for maintaining operational safety and integrity. Traditional methods of manual inspection pose significant challenges, including safety risks, high cognitive demands, and potential inaccuracies due to human limitations. Recent advancements in Artificial Intelligence (AI) and robotic technologies have opened new possibilities for safer, more efficient, and accurate inspection methodologies. Specifically, Human-Robot Collaboration (HRC), leveraging robotic platforms equipped with advanced detection algorithms, promises significant improvements in inspection outcomes and reductions in human workload. This study explores the effectiveness of AI-assisted visual crack detection integrated into a mobile Jackal robot platform. The experiment results indicate that HRC enhances inspection accuracy and reduces operator workload, resulting in potential superior performance outcomes compared to traditional manual methods.
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