生物灵感动物机器人ANIBOT中的乱和恒温
Kevin Castillo1, Madeline Parker1, Nathan Reyes1
1Department of Mathematics, San Diego State University, 5500 Campanile Drive, San Diego, 92182, CA, USA.
Bulletin of mathematical biology
|February 21, 2026
概括
中央模式生成器 (CPG) 网络中的外部干扰可能会扰乱 ANIBOT 机器人的运动. 然而,大多数步态都表现出恒常性弹性,有些干扰甚至可以创建新的运动模式.
科学领域:
- 神经科学是一个神经科学.
- 机器人技术 机器人技术 机器人技术
- 复杂的系统复杂的系统.
背景情况:
- 中央模式生成器 (CPG) 是神经回路控制节奏行为,如移动.
- ANIBOT是一台以生物系统为灵感的四足机器人,使用CPG模型.
- 恒温,即保持稳定的内部条件的能力,对生物和人工系统至关重要.
研究的目的:
- 为了研究外部干扰对CGG网络的影响在恒温的背景下.
- 分析ANIBOT的移动模式对网络障碍的弹性.
- 探索神经网络中因疾病引起的模式形成现象.
主要方法:
- 对CPG网络进行分析和计算建模.
- 适用于恒常状态的数学框架的应用,包括输入-输出函数.
- 模拟干扰,包括网络连接变化,内部动态和电子噪声.
主要成果:
- CPG相位动力学控制ANIBOT的运动模式 (行走,跳跃,步,束,节奏,).
- 除了步行和跳跃,大多数步态表现出对干扰的完美平静反应.
- 外部干扰可以诱导在未被干扰的系统中不存在的新型运动模式.
结论:
- CPG网络表现出显著的恒温能力,可以维持运动模式,抵御外部干扰.
- 障碍诱导的模式形成是这些乱的CPG网络的一个显著特征.
- 这些发现对设计强大的生物灵感机器人和理解神经控制有意义.
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