在自动驾驶机器人中编程可调节的活力动力学
Somnath Paramanick1, Arnab Pal2,3, Harsh Soni4
1Department of Physics, Indian Institute of Technology Bombay, Powai, Mumbai, 400076, India.
The European physical journal. E, Soft matter
|May 23, 2024
概括
我们开发了一种机器人设备,能够调整主动动力学,模仿粒子模型,如主动布朗运动. 这种可控制的机器人使用光梯度来导航障碍物,推进活性物质物理学和生物启发的机器人.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 活动物质物理学 活动物质物理学
- 生物物理学的生物物理.
背景情况:
- 活性物质系统表现出由生物生物体启发的复杂动态.
- 控制人工活性物质的运动对于理解基本物理和开发新型应用至关重要.
- 机器人设备为实验性研究活性物质模型提供了一个平台.
研究的目的:
- 设计和实施一种具有可调节活跃动态的自行机器人设备.
- 为了证明机器人能够复制各种活性粒子模型的能力.
- 探索光控制导航和使用随机重定位避开障碍.
主要方法:
- 使用差速驱动机制进行独立的轮速控制.
- 通过将运动的二维方程与活性粒子模型等同来计算机器人的速度.
- 将控制算法编码到机器人的微控制器中.
- 使用粒子跟踪分析机器人轨迹,并与理论预测进行比较.
主要成果:
- 机器人成功地描绘了活跃的布朗,运行和,以及在一系列参数上的布朗动力学.
- 实验轨迹与理论上预测的运动有很好的一致性.
- 机器人动态在不同的模型之间切换,使用光强度作为外部控制参数.
- 机器人通过光梯度驱动的随机重定位演示了高效的障碍物导航.
结论:
- 成功开发了一种可调节的活跃机器人系统,能够模仿各种活跃物质行为.
- 光强度作为有效的外部参数来控制机器人动态,并使导航成为可能.
- 这项工作为研究活性物质物理学和开发生物和自然启发的机器人系统提供了一个平台.
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