CTF定位策略下基于多特征的智能机器人目标跟踪

针对复杂环境下机器人目标跟踪问题,提出由粗到精定位策略下基于多特征的智能机器人目标跟踪方法.该方法首先利用射频识别系统实现目标粗定位,然后采用自适应模板匹配算法、改进核函数的连续自适应均值飘移算法及扩展卡尔曼滤波算法提取目标头肩形状、衣服颜色与运动特征,实现精确定位.最后根据人机运动状态设计基于模糊规则的智能调速控制器,实时自动调整机器人的基准线速度与转弯增益,以稳定跟随运动目标.实验结果表明,该方法能有效保持人机之间的安全距离,对遮挡、相近颜色背景干扰及目标突然转弯的跟踪问题有较强的鲁棒性.

Human Tracking Based on Multi Feature for Intelligent Robot Under the CTF Locating Strategy

To realize a human tracking task in a cluttered environment, a method of multi feature based human tracking under the CTF(coarse to fine) locating strategy was proposed. The proposed method located the target from a RFID system coarsely. Then, the silhouette of the head shoulder, the cloth color and motion feature were extracted to locate the target accurately by using the processing techniques including adaptive template matching algorithm, improved Camshift and Extended Kalman Filter. At last, an intelligent gear shift controller based on fuzzy rules considering the motion state of the target and the robot was utilized to drive the robot. The experimental results show that the presented method can keep the robot in a suitable distance from the target and handle the problem of occlusion, a sudden turn, and complicated background. Key words：