While mainstream robotics pursues metric precision and flawless performance, this paper explores the creative potential of a deliberately "lo-fi" approach. We present the "Semantic Glitch," a soft flying robotic art installation whose physical form, a 3D pixel style cloud, is a "physical glitch" derived from digital archaeology. We detail a novel autonomous pipeline that rejects conventional sensors like LiDAR and SLAM, relying solely on the qualitative, semantic understanding of a Multimodal Large Language Model to navigate. By authoring a bio-inspired personality for the robot through a natural language prompt, we create a "narrative mind" that complements the "weak," historically, loaded body. Our analysis begins with a 13-minute autonomous flight log, and a follow-up study statistically validates the framework's robustness for authoring quantifiably distinct personas. The combined analysis reveals emergent behaviors, from landmark-based navigation to a compelling "plan to execution" gap, and a character whose unpredictable, plausible behavior stems from a lack of precise proprioception. This demonstrates a lo-fi framework for creating imperfect companions whose success is measured in character over efficiency.

翻译：当主流机器人学追求度量精度与无瑕性能时，本文探索了一种刻意采用'低保真'方法的创造潜力。我们提出了'语义故障'——一个软体飞行机器人艺术装置，其物理形态（一种3D像素风格云）源自数字考古学的'物理故障'。我们详细介绍了一种新颖的自主流程，该流程摒弃了如激光雷达与SLAM等传统传感器，仅依靠多模态大语言模型的定性语义理解进行导航。通过自然语言提示为机器人编写受生物启发的个性，我们创建了一个'叙事思维'，以补充其'脆弱'且承载历史意义的躯体。我们的分析始于一段13分钟的自主飞行日志，后续研究通过统计学验证了该框架在编写可量化区别人格方面的鲁棒性。综合分析揭示了涌现行为：从基于地标的导航到引人注目的'计划与执行间隙'，以及一个因缺乏精确本体感知而产生不可预测却合理行为的角色。这展示了一种低保真框架，用于创造不完美的伴侣，其成功以角色特质而非效率衡量。