Huang Yinggang, Yang Lifang, Yang Long, Xu Zehua, Li Mengmeng, Shang Zhigang
School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China.
Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, Zhengzhou 450001, China.
Heliyon. 2024 Sep 19;10(19):e38113. doi: 10.1016/j.heliyon.2024.e38113. eCollection 2024 Oct 15.
Research on animal robots utilizing neural electrical stimulation is a significant focus within the field of neuro-control, though precise behavior control remains challenging. This study proposes a parameter-adaptive strategy to achieve accurate path tracking. First, the mapping relationship between neural electrical stimulation parameters and corresponding behavioral responses is comprehensively quantified. Next, adjustment rules related to the parameter-adaptive control strategy are established to dynamically generate different stimulation patterns. A parameter-adaptive path tracking control strategy (PAPTCS), based on fuzzy control principles, is designed for the precise path tracking tasks of pigeon robots in open environments. The results indicate that altering stimulation parameter levels significantly affects turning angles, with higher UPN and PTN inducing changes in the pigeons' motion state. In experimental scenarios, the average control efficiency of this system was 82.165%. This study provides a reference method for the precise control of pigeon robot behavior, contributing to research on accurate target path tracking.
利用神经电刺激的动物机器人研究是神经控制领域的一个重要研究方向，尽管精确的行为控制仍然具有挑战性。本研究提出了一种参数自适应策略以实现精确的路径跟踪。首先，全面量化神经电刺激参数与相应行为反应之间的映射关系。其次，建立与参数自适应控制策略相关的调整规则，以动态生成不同的刺激模式。基于模糊控制原理，设计了一种参数自适应路径跟踪控制策略（PAPTCS），用于鸽子机器人在开放环境中的精确路径跟踪任务。结果表明，改变刺激参数水平会显著影响转弯角度，较高的UPN和PTN会引起鸽子运动状态的变化。在实验场景中，该系统的平均控制效率为82.165%。本研究为鸽子机器人行为的精确控制提供了一种参考方法，有助于精确目标路径跟踪的研究。
