基于梯度自适应极值搜索算法的趋光控制研究

Research on Phototaxis Control Based on Gradient Adaptive Extremum Seeking Algorithm

摘要:

源定位已成为国内外研究的热点问题,为了在实验室环境下研究移动机器人的趋光性,对源定位理论方法进行了研究,设计了地面移动机器人光源定位平台,通过该平台来验证趋光理论的可行性。首先,利用对角线控制策略和梯度自适应极值搜索算法分别进行趋光实验,完成移动机器人对光源的定位。其次,使用MeanShift目标跟踪算法跟踪移动机器人的运动轨迹。最后,绘制出光源强度分布等值线并分析了移动机器人的运动轨迹。相比于对角线控制策略,梯度自适应极值搜索算法根据当前区域梯度值自适应调整反馈增益参数,提高了源定位效率,并在光源定位平台验证了该算法的有效性和稳定性。

Abstract:

Source seeking become a hot issue at home and abroad, in order to study the phototaxis of mobile robots in the laboratory, research on source seeking theory methods, design a mobile robot platform, verify the feasibility of the phototaxis theory by this platform. Firstly, using diagonal control strategy and gradient adaptive extremum search algorithm, the phototaxis experiments are carried out, respectively, to complete the light source seeking of mobile robot. Secondly, MeanShift target tracking algorithm is used to track the moving trajectory of mobile robot. Finally, draw the contours of light source intensity distribution and analyze the motion trajectory of the mobile robot. Compared with the diagonal control strategy, the gradient adaptive extremum seeking algorithm adjusts the feedback gain parameters according to the current regional gradient value, which improve the efficiency of source seeking, and verify the effectiveness and stability of the algorithm on the platform.