Bolting operations are critical in industrial assembly and in the maintenance of scientific facilities, requiring high precision and robustness to faults. Although robotic solutions have the potential to improve operational safety and effectiveness, current systems still lack reliable autonomy and fault management capabilities. To address this gap, we propose a control framework for dependable robotized bolting tasks and instantiate it on a specific robotic system. The system features a control architecture ensuring accurate driving torque control and active compliance throughout the entire operation, enabling safe interaction even under fault conditions. By designing a multimodal human-robot interface (HRI) providing real-time visualization of relevant system information and supporting seamless transitions between automatic and manual control, we improve operator situation awareness and fault detection capabilities. A high-level supervisor (SV) coordinates the execution and manages transitions between control modes, ensuring consistency with the supervisory control (SVC) paradigm, while preserving the human operator's authority. The system is validated in a representative bolting operation involving pipe flange joining, under several fault conditions. The results demonstrate improved fault detection capabilities, enhanced operator situational awareness, and accurate and compliant execution of the bolting operation. However, they also reveal the limitations of relying on a single camera to achieve full situational awareness.

翻译：螺栓连接操作在工业装配与科学设施维护中至关重要，需要高精度与强容错性。尽管机器人解决方案具有提升操作安全性与效率的潜力，但现有系统仍缺乏可靠的自主性与故障管理能力。为弥补这一不足，我们提出了一种面向可靠机器人化螺栓连接任务的控制框架，并在特定机器人系统上进行了实例化。该系统采用一种控制架构，确保在整个操作过程中实现精确的驱动扭矩控制与主动柔顺性，即使在故障条件下也能实现安全交互。通过设计一个多模态人机交互界面（HRI），实时可视化相关系统信息并支持自动与手动控制间的无缝切换，我们提升了操作员的情境感知与故障检测能力。一个高层监督器（SV）协调任务执行并管理控制模式间的转换，确保符合监督控制（SVC）范式，同时保留人工操作员的决策权。该系统在涉及管道法兰连接的典型螺栓操作中，于多种故障条件下进行了验证。结果表明，该系统提升了故障检测能力，增强了操作员的情境感知，并实现了螺栓连接操作的精确与柔顺执行。然而，结果也揭示了依赖单一摄像头实现全面情境感知的局限性。