Safety-guaranteed and Goal-oriented Semantic Sensing, Communication, and Control for Robotics

2026-03-13

AI Summary

This work addresses the critical gap in existing goal-oriented semantic communication methods, which often neglect the stringent safety requirements inherent in robotic systems. Focusing on wirelessly connected robots, this study pioneers a systematic integration of safety constraints into a goal-oriented semantic communication framework, establishing a joint optimization mechanism that spans perception, communication, and control. The proposed approach maximizes task effectiveness while rigorously ensuring operational safety, and is applicable to representative scenarios such as robotic arm grasping, drone tracking, and multi-robot exploration. Experimental results demonstrate that, in a drone-based target tracking task, the method improves both safety compliance and tracking success rates by over 2× and 4.5×, respectively, compared to existing approaches.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Natural Language Processing: Safety and Robustness
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

Wirelessly-connected robotic system empowers robots with real-time intelligence by leveraging remote computing resources for decision-making. However, the data exchange between robots and base stations often overwhelms communication links, introducing latency that undermines real-time response. To tackle this, goal-oriented semantic communication (GSC) has been introduced into wirelessly-connected robotic systems to extract and transmit only goal-relevant semantic representations, enhancing communication efficiency and task effectiveness. However, existing GSC approaches focused primarily on optimizing effectiveness metrics while overlooking safety requirements, which should be treated as the top priority in real-world robotic systems. To bridge this gap, we propose safety-guaranteed and goal-oriented semantic communication for wirelessly-connected robotic system, aiming to maximize the robotic task effectiveness subject to practical operational safety requirements. We first summarize the general safety requirements and effectiveness metrics across typical robotic tasks, including robot arm grasping, unmanned aerial vehicle (UAV)-assisted tasks, and multi-robot exploration. We then systematically analyze the unique safety and effectiveness challenges faced by wirelessly-connected robotic system in sensing, communication, and control. Based on these, we further present potential safety-guaranteed and goal-oriented sensing, communication, and control solutions. Finally, a UAV target tracking case study validates that our proposed GSC solutions can significantly improve safety rate and tracking success rate by more than 2 times and 4.5 times, respectively.

Problem

• goal-oriented semantic communication
• safety guarantees
• wirelessly-connected robotic systems
• robotic safety
• task effectiveness

Innovation

• Safety-guaranteed
• Goal-oriented semantic communication
• Wirelessly-connected robotics
• Semantic sensing and control
• Task effectiveness