论文标题
使用实时机器人视觉的独立于对象独立于对象的人对机器人移交
Object-Independent Human-to-Robot Handovers using Real Time Robotic Vision
论文作者
论文摘要
我们提出了一种使用实时机器人视觉和操纵的方法，以安全和与对象无关的人向机器人移交。我们的目标是使用通用对象检测器，快速掌握选择算法以及使用单个抓紧器安装的RGB-D摄像头，因此不依赖外部传感器。机器人通过视觉伺服朝向感兴趣的对象进行控制。高度强调安全性，我们使用了两个感知模块：人体部分分割和手/手指分割。被认为属于人类的像素是从候选人抓住的姿势中滤除的，因此确保机器人可以安全地挑选物体而不会与人类伴侣相撞。掌握选择和感知模块同时实时运行，从而可以监视进度。在使用13个物体的实验中，机器人能够在81.9％的试验中成功从人类身上取出该物体。
We present an approach for safe and object-independent human-to-robot handovers using real time robotic vision and manipulation. We aim for general applicability with a generic object detector, a fast grasp selection algorithm and by using a single gripper-mounted RGB-D camera, hence not relying on external sensors. The robot is controlled via visual servoing towards the object of interest. Putting a high emphasis on safety, we use two perception modules: human body part segmentation and hand/finger segmentation. Pixels that are deemed to belong to the human are filtered out from candidate grasp poses, hence ensuring that the robot safely picks the object without colliding with the human partner. The grasp selection and perception modules run concurrently in real-time, which allows monitoring of the progress. In experiments with 13 objects, the robot was able to successfully take the object from the human in 81.9% of the trials.
