A framework for semantics-based situational awareness during mobile robot deployments

作者：Tianshu Ruan, Aniketh Ramesh, Hao Wang, Alix Johnstone-Morfoisse, Gokcenur Altindal, Paul Norman, Grigoris Nikolaou, Rustam Stolkin, Manolis Chiou · 发表于：Frontiers in Robotics and AI · 年份：2025 · DOI：10.3389/frobt.2025.1694123 · 被引用次数：2 · 研究领域：Human-Automation Interaction and Safety、Social Robot Interaction and HRI、Robotics and Automated Systems

Deployment of robots into hazardous environments typically involves a "human-robot teaming" (HRT) paradigm, in which a human supervisor interacts with a remotely operating robot inside the hazardous zone. Situational awareness (SA) is vital for enabling HRT, to support navigation, planning, and decision-making. In this paper, we explore issues of higher-level "semantic" information and understanding in SA. In semi-autonomous or variable-autonomy paradigms, different types of semantic information may be important, in different ways, for both the human operator and an autonomous agent controlling the robot. We propose a generalizable framework for acquiring and combining multiple modalities of semantic-level SA during remote deployments of mobile robots. We demonstrate the framework with an example application of search and rescue (SAR) in disaster-response robotics. We propose a set of "environment semantic indicators" that can reflect a variety of different types of semantic information, such as indicators of risk or signs of human activity (SHA), as the robot encounters different scenes. Based on these indicators, we propose a metric to describe the overall situation of the environment, called "Situational Semantic Richness" (SSR). This metric combines multiple semantic indicators to summarize the overall situation. The SSR indicates whether an information-rich, complex situation has been encountered, which may require advanced reasoning by robots and humans and, hence, the ...