提出一套高效机器人控制设计流程，提升人机协作与环境适应能力。
Establishing Design Routines for Efficient Control of Automated Robots
- 基于AI与数字图像处理构建通用控制框架
- 实测验证系统在真实环境中的效率优于现有模型
- 适合工业场景应用，支持GPS导航与渐进式内存管理
随着技术持续进步，模拟人类行为的机器人研发日益加强。认知机器人结合人工智能（AI）已在调研与研究分析中展现成效，但当前仍需人工干预，且将AI融入机器人系统面临挑战。本文探索将AI整合至机器人设计的方法，旨在提升人机交互性能。提出多种改进方案，包括适用于多样化环境的高效控制流程，以及通过数字图像处理增强视野能力。关键贡献在于在实时环境中测试机器人系统，评估其相对于现有模型的效率。此外，本文开发并编程了一种具备通用控制能力的机器人系统，基于Arduino平台实现，支持GPS控制以保障安全操作，并采用渐进式记忆算法实现高效内存管理，为工业与科研应用提供新进展。
原文摘要 · Abstract (English)
With continual advancements in technology, efforts to develop robots simulating human behavior have intensified. Cognitive robotics, combined with artificial intelligence (AI), has proven effective in surveying and research analysis. However, despite progress, human intervention remains necessary, and incorporating AI into robotic systems continues to pose challenges. This paper explores methodologies to integrate AI into robotic designs, aiming to enhance human-robot interactions. Several approaches are proposed to improve robotic performance, including routines for efficient control in varied environments and the incorporation of digital image processing for enhanced line-of-sight capabilities. A key contribution of this work is testing robotic systems in real-time environments to assess efficiency relative to existing models. Additionally, the paper introduces a robotic system with universal control capabilities, suitable for industrial applications, developed and programmed on the Arduino platform. Features such as GPS control for safe operations and progressive memory algorithms for efficient memory management are presented, offering advancements in both industrial and research applications.
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