We propose a meta-language-based approach enabling Large Language Models (LLMs) to reliably generate structured, machine-readable artifacts referred to as Meta-Languagedefined Structures (MLDS) adapted to domain requirements, without adhering strictly to standard formats like JSON or XML.By embedding explicit schema instructions within prompts, we evaluated the method across diverse use cases, including automated Virtual Reality environment generation and automotive security modeling.Our experiments demonstrate that the meta-language approach significantly improves LLM-generated structure compliance, with an 88% validation rate across 132 test scenarios.Compared to traditional methods using LangChain and Pydantic, our MLDS method reduces setup complexity by approximately 80%, despite a marginally higher error rate.Furthermore, the MLDS artifacts produced were easily editable, enabling rapid iterative refinement.This flexibility greatly alleviates the "blank page syndrome" by providing structured initial artifacts suitable for immediate use or further human enhancement, making our approach highly practical for rapid prototyping and integration into complex industrial workflows.

Autonomous low-cost mobility of robots has been a challenging problem for quite a long time. In this paper the typical problems of sonar based autonomous navigation and the authors' solutions to overcome them are discussed. The authors have created, robust modules for sonar data fusion and safe steering which significantly improve known methods. There are furthermore robot control behaviors which offer specific competence to solve high-level tasks. These behaviors build a hierarchical architecture but have the ability to assess their respective task and autonomously suggest a different, more competent behavior to continue. Thus, the behaviors work together as distributed competencies. The concept described here is being evaluated in a system on the authors' experimental robot ROAMER. The available modules already operate robustly in cluttered office environments.>