Analysing Explanation-Related Interactions in Collaborative Perception-Cognition-Communication-Action
Marc Roig Vilamala, Jack Furby, Julian de Gortari Briseno, Mani Srivastava, Alun Preece, Carolina Fuentes Toro
- Year
- 2024
- Access
- Open access
Abstract
Effective communication is essential in collaborative tasks, so AI-equipped robots working alongside humans need to be able to explain their behaviour in order to cooperate effectively and earn trust. We analyse and classify communications among human participants collaborating to complete a simulated emergency response task. The analysis identifies messages that relate to various kinds of interactive explanations identified in the explainable AI literature. This allows us to understand what type of explanations humans expect from their teammates in such settings, and thus where AI-equipped robots most need explanation capabilities. We find that most explanation-related messages seek clarification in the decisions or actions taken. We also confirm that messages have an impact on the performance of our simulated task.
Keywords
Related papers
How to Relieve Distribution Shifts in Semantic Segmentation for Off-Road Environments
Ji-Hoon Hwang, Daeyoung Kim, Hyung-Suk Yoon +2 more
2026
Point cloud registration for non-destructive, high-resolution coating thickness measurement from 3D scans
Simon Duenser, Ivo Aschwanden, Raamadaas Krishnadas +2 more
Robotics and Computer-Integrated Manufacturing · 2026
Uncertainty-guided evolvable recognition framework for industrial robots via prototype-based fuzzy inference and evidence fusion
Yanrun Zhou, Zihao Lei, Guangrui Wen +4 more
Robotics and Computer-Integrated Manufacturing · 2026
Toward the intelligent robotics era: Multimodal flexible haptic sensors for advanced perception systems
Sili Ding, Feng Xu, Jie Chen +3 more
Progress in Materials Science · 2026