计算机科学 ›› 2024, Vol. 51 ›› Issue (11A): 240300003-6.doi: 10.11896/jsjkx.240300003
林叶贵, 戴志坚, 何德峰, 邢科新
LIN Yegui, DAI Zhijian, HE Defeng, XING Kexin
摘要： 在全向移动机器人视觉伺服任务过程中,为了解决由特征点的变化、车轮打滑、动态障碍等情况导致的速度突变问题,提出了一种基于神经动力学的quasi-min-max MPC视觉伺服策略。因为视觉误差的突变是引起速度突变的主要原因,所以该策略引入神经动力学模型对视觉误差进行处理,建立基于神经动力学的移动机器人视觉伺服线性参数时变预测模型,采用quasi-min-maxMPC策略获得最优速度解,从而抑制速度的突变,最终保证移动机器人能够以一个平滑的速度到达期望位姿。仿真结果验证了所提策略在抑制速度突变上的有效性。
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