梳理机器人测试现状，揭示其与传统软件测试的差异与挑战
Before Autonomy Takes Control: Software Testing in Robotics
- 基于247篇论文分析机器人测试方法与软件测试理论的对应关系
- 指出机器人测试面临环境不确定性、硬件交互复杂等核心难点
- 为机器人与软件工程领域提供测试研究的共性问题与未来方向
机器人系统是复杂且安全关键的软件系统，亟需全面测试。然而，相比传统软件，机器人软件测试难度更高，主要因其需紧密耦合硬件、应对运行环境中的不确定性、处理扰动并实现高度自主。由于机器人操作空间巨大，预先识别潜在故障极为困难。本文通过对247篇机器人测试相关论文进行综合分析，将其与软件测试理论相对应，系统梳理了当前机器人软件测试的研究现状，并通过实例说明。研究揭示了现有测试方法在覆盖性、可重复性与自动化方面的局限，明确了跨领域协作的关键挑战。最后提出若干开放性问题与经验教训，旨在为机器人与软件工程两个领域的研究者提供共同参考。
原文摘要 · Abstract (English)
Robotic systems are complex and safety-critical software systems. As such, they need to be tested thoroughly. Unfortunately, robot software is intrinsically hard to test compared to traditional software, mainly since the software needs to closely interact with hardware, account for uncertainty in its operational environment, handle disturbances, and act highly autonomously. However, given the large space in which robots operate, anticipating possible failures when designing tests is challenging. This paper presents a mapping study by considering robotics testing papers and relating them to the software testing theory. We consider 247 robotics testing papers and map them to software testing, discussing the state-of-the-art software testing in robotics with an illustrated example, and discuss current challenges. Forming the basis to introduce both the robotics and software engineering communities to software testing challenges. Finally, we identify open questions and lessons learned.
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