分析索尼机器狗的控制代码，提炼出一套核心行为语法。
A Behavioral State Vocabulary in Sony ERS-111 R-CODE
- 通过对比大量代码片段，发现其行为由初始化、感知、循环动作等少数状态构成。
- 这些状态组合可实现从启动到环境决策的渐进式复杂行为。
- 适合资源受限机器人系统，便于模块化构建稳定行为程序。
本文对索尼E-111 AIBO机器人使用的R-CODE样本集进行了整体性行为图谱分析。研究不单独解读每个脚本，而是对比整个语料库中命名状态的共现模式，识别出支撑样本集的核心控制词汇。结果表明，众多表面不同的程序实际上基于一套紧凑的具身化语法，包括初始化、感知、迭代动作、同步与恢复等关键环节。该语法支持行为复杂度的渐进提升：从功能激活与启动规范化，到受控移动、环境决策循环，直至完整的模式化控制。除了历史分析，论文还主张这种基于状态的抽象形式，可作为构建新封装行为模块的中间表示，尤其适用于对确定性控制、直接硬件访问和模块化行为组合有要求的受限本地机器人系统。
原文摘要 · Abstract (English)
This paper presents a corpus-level analysis of generated behavior diagrams derived from Sony's R-CODE sample distribution for the ERS-111 AIBO. Rather than reading each script in isolation, the study compares named states across the corpus to identify the recurring control vocabulary that structures the sample set. The resulting aggregate shows that many superficially different routines are built from a compact embodied grammar centered on initialization, sensing, iterative action, synchronization, and recovery. It further shows that this vocabulary supports a graded scale of rising behavioral complexity, from capability activation and startup regularization to monitored locomotion, environmental decision loops, and fuller mode-based control. In addition to historical analysis, the paper argues that this form of state-based abstraction is useful as an intermediate representation for constructing new encapsulated behavior routines, especially on constrained native robotic systems where deterministic control, direct hardware access, and modular behavioral composition remain important.
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