在布尔网络机器人中的感觉运动环适应
Michele Braccini1, Yuri Gardinazzi2,3,4, Andrea Roli1,5
1Department of Computer Science and Engineering, University of Bologna, 47521 Cesena, Italy.
Sensors (Basel, Switzerland)
|June 19, 2024
概括
这项研究表明,微型机器人如何通过调整它们的感觉运动循环来适应新环境. 这种灵感来自于恒温的适应能力,使得简单的机器人能够在各种条件下保持功能.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 网络学就是网络学.
- 控制系统 控制系统
背景情况:
- 微型机器人为探索危险环境和应急响应提供了潜力.
- 适应特定环境对于微型机器人的功能至关重要.
- 有限的机载计算需要简单,灵活的控制机制,如感觉电机循环.
研究的目的:
- 为了探索微型机器人的自适应行为,使用调制的感觉-运动循环.
- 调查网络静止原则在机器人控制中的应用.
- 使微型机器人能够根据环境条件调整他们的行为.
主要方法:
- 装备机器人与布尔网络进行控制.
- 通过调整效应器连接和环境相互作用来调节感觉电机循环.
- 模拟适应机制来评估性能.
- 分析通过环境反来维持机器人恒温的能力.
主要成果:
- 基于随机布尔网络的控制器可以调整为适应性平衡.
- 机器人在不同的模拟环境中证明了持续的平衡.
- 拟议的机制允许调整感官运动循环以影响机器人的行为.
结论:
- 该研究提出了一种可行的方法来设计微机器人的自适应控制器.
- 这项工作是迈向能够在多样化和不可预测的环境中自主操作的微型机器人的一步.
- 这些发现支持对强大的机器人系统使用简单的,恒温的控制机制.
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