机器人解决算法在图形结构上的语义构成
Sven Schneider1,2, Nico Hochgeschwender3, Herman Bruyninckx2,4,5
1Department of Computer Science, Institute for AI and Autonomous Systems, Hochschule Bonn-Rhein-Sieg, Sankt Augustin, Germany.
Frontiers in robotics and AI
|February 13, 2025
概括
本研究介绍了基于模型的机器人软件开发方法,使得可适应的机器人系统可以从可重复使用的块组成算法. 它专注于动力学和动力学,从象征合成生成复杂机器人的高效代码.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 软件工程 软件工程 软件工程
- 计算数学 计算数学 计算数学
背景情况:
- 代码重复和缺乏适应性阻碍了机器人软件开发.
- 复杂的机器人系统需要系统的算法组成.
研究的目的:
- 介绍机器人软件的基于模型的设计,实施,部署和执行方法.
- 通过系统的算法组成,使机器人能够自主调整他们的软件.
主要方法:
- 利用通用和特定领域的计算构建块用于算法合成.
- 采用语义网络标准,用于符号算法合成和高效的代码生成.
- 专注于基于图形结构的数值解法器,特别是动力学和动力学算法.
主要成果:
- 一种方法和工具,可以防止代码重复,提高软件的适应性.
- 在一个过度操作的移动机器人上展示了应用,它有两个冗余的手臂.
- 成功的符号合成和高效的代码生成复杂的算法.
结论:
- 拟议的方法方便创建可适应和可重复使用的机器人软件.
- 基于模型的设计和符号合成对于开发复杂的机器人算法是有效的.
- 该方法支持多种算法,包括动力学,动态学和概率网络消息传递.
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