- 基于 kinect2 获取移动机器人所需要的图像和深度信息。通过比较目前比较流行的深度图像获取方法，采用比较成熟的微软 kinect2 传感器同时获得深度信息和彩色图像。针对在某些情况下，深度相机可能无法提供某些像素的正确值，采用绘制轮廓的方法降低对深度信息获取的影响。
- 根据室内跟随机器人的应用场景，采用深度学习中的 YOLOv3 方法对目标进行识别。YOLOv3 有着高精度和实时性强的特点，给了跟随机器人更多的可能性。
- 基于人工势场法实现机器人移动的控制策略。为了提高鲁棒性，实验并测试对应参数的阈值，提高移动机器人在动态场景的自主移动能力。
kinect2_yolov3_ros's Introduction
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