Improving dependability in robotized bolting operations

2025-11-13

AI Summary

Existing robotic systems for bolt operations in industrial assembly and scientific facility maintenance exhibit insufficient autonomy reliability and fault management, failing to meet stringent requirements for high precision and robust fault tolerance. Method: This paper proposes a trustworthy bolt manipulation control system integrating active compliance control with multimodal human–robot interaction. A novel high-level supervisor enables dynamic coordination between autonomous and manual modes, ensuring fail-safe execution while preserving operator authority. The system incorporates precise torque control, real-time state visualization, and a supervisor-based adaptive mode management mechanism. Results: Experimental validation on pipe flange connection tasks demonstrates significantly improved fault detection capability and operator situational awareness, achieving high-precision, high-compliance, and high-robustness bolt operations. Additionally, the study reveals inherent limitations of monocular vision in complex geometric environments.

Technology Category

• Intelligent Robots: Manipulation
• Computer Vision: Multi-modal Vision
• Natural Language Processing: Safety and Robustness

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

Abstract

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.

Problem

• Robotic bolting systems lack reliable autonomy and fault management capabilities
• Current systems need improved operator situation awareness and fault detection
• There is a need for safe human-robot interaction during fault conditions

Innovation

• Control architecture with torque control and active compliance
• Multimodal human-robot interface for real-time visualization
• High-level supervisor coordinating control mode transitions