Deep Reinforcement Learning for Next-Best-View Planning in Agricultural Applications
Xiangyu Zeng,Tobias Zaenker,Maren Bennewitz,Xiangyu Zeng,Tobias Zaenker,Maren Bennewitz
Automated agricultural applications, i.e., fruit picking require spatial information about crops and, especially, their fruits. In this paper, we present a novel deep reinforcement learning (DRL) approach to determine the next best view for automatic exploration of 3D environments with a robotic arm equipped with an RGB-D camera. We process the obtained images into an octree with labeled regions o...
