An Empirical Study of Interaction Bugs in ROS-based Software

2025-07-14

AI Summary

This paper addresses reliability issues—termed iBugs—arising from interaction failures among perception, decision-making, and execution modules in ROS-based robotic systems. We conduct the first systematic empirical study by performing root-cause analysis on 121 real-world interaction bugs drawn from 10 active ROS projects. Based on this analysis, we propose a three-tier interaction bug taxonomy: intra-system, hardware-layer, and environment-layer defects—characterizing their underlying causes and repair patterns. We identify recurrent interaction bug patterns and derive actionable, robustness-oriented design guidelines for ROS developers. Furthermore, our findings establish an empirical foundation and methodological support for developing automated detection and mitigation mechanisms targeting interaction-related failures in robotic software. The study bridges a critical gap in understanding and improving the reliability of modular robotic systems, offering both theoretical insights and practical implications for robotics software engineering.

Technology Category

• Intelligent Robots: Human-Robot Interaction
• Reasoning under Uncertainty: Relational Probabilistic Models
• Knowledge Representation and Reasoning: Diagnosis and Abductive Reasoning

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

Modern robotic systems integrate multiple independent software and hardware components, each responsible for distinct functionalities such as perception, decision-making, and execution. These components interact extensively to accomplish complex end-to-end tasks. As a result, the overall system reliability depends not only on the correctness of individual components, but also on the correctness of their interactions. Failures often manifest at the boundaries between components, yet interaction-related reliability issues in robotics--referred to here as interaction bugs (iBugs)--remain underexplored. This work presents an empirical study of iBugs within robotic systems built using the Robot Operating System (ROS), a widely adopted open-source robotics framework. A total of 121 iBugs were analyzed across ten actively maintained and representative ROS projects. The identified iBugs are categorized into three major types: intra-system iBugs, hardware iBugs, and environmental iBugs, covering a broad range of interaction scenarios in robotics. The analysis includes an examination of root causes, fixing strategies, and the impact of these bugs. Several findingsa are derived that shed light on the nature of iBugs and suggest directions for improving their prevention and detection. These insights aim to inform the design of more robust and safer robotic systems.

Problem

• Study interaction bugs in ROS-based robotic systems
• Analyze root causes and fixes for 121 interaction bugs
• Improve prevention and detection of robotic system failures

Innovation

• Empirical study of ROS interaction bugs
• Categorizes iBugs into three major types
• Analyzes root causes and fixing strategies