我们展示了一个成功的导航和对接控制系统的约翰迪尔探戈自主割草机，只使用一个摄像头作为输入。这种仅视觉的系统是令人感兴趣的，因为它是廉价的，简单的生产，并且不需要外部传感。这与依赖于集成位置传感器和全球定位系统（GPS）技术的现有系统形成对比。为了产生我们的系统，我们将最先进的目标检测架构You Only Look Once（YOLO）与强化学习（RL）架构Double Deep QNetworks（Double DQN）相结合。目标检测网络识别割草机上的特征，并将其输出传递给RL网络，为其提供低维表示，从而实现快速和鲁棒的训练。最后，RL网络学习如何在自定义仿真环境中将机器导航到所需的位置。当在割草机硬件上进行测试时，该系统能够从任意初始位置和方向以厘米级精度对接。
英文摘要：
We demonstrate a successful navigation and docking control system for the John Deere Tango autonomous mower, using only a single camera as the input. This vision-only system is of interest because it is inexpensive, simple for production, and requires no external sensing. This is in contrast to existing systems that rely on integrated position sensors and global positioning system (GPS) technologies. To produce our system we combined a state-of-the-art object detection architecture, You Only Look Once (YOLO), with a reinforcement learning (RL) architecture, Double Deep QNetworks (Double DQN). The object detection network identifies features on the mower and passes its output to the RL network, providing it with a low-dimensional representation that enables rapid and robust training. Finally, the RL network learns how to navigate the machine to the desired spot in a custom simulation environment. When tested on mower hardware, the system is able to dock with centimeter-level accuracy from arbitrary initial locations and orientations.
STERN: Simultaneous Trajectory Estimation and Relative Navigation for Autonomous Underwater Proximity Operations
Centre for Naval Architecture, KTH Royal Institute of Technology（KTH皇家理工学院海军建筑中心）；Division of Robotics, Perception, and Learning, KTH Royal Institute of Technology（KTH皇家理工学院机器人、感知与学习系）
MoTo: A Zero-shot Plug-in Interaction-aware Navigation for General Mobile Manipulation
Beijing University of Posts and Telecommunications（北京邮电大学）；Tsinghua University（清华大学）；Beijing Key Laboratory of Embodied Intelligence Systems（北京市具身智能系统重点实验室）；Beijing National Research Center for Information Science and Technology（北京信息科学与技术国家研究中心）；Nanyang Technological University（南洋理工大学）
Relative Navigation and Dynamic Target Tracking for Autonomous Underwater Proximity Operations
AI, Robotics and Cybersecurity Center, Örebro University（人工智能、机器人与网络安全中心，奥雷布罗大学）；Centre for Naval Architecture, KTH Royal Institute of Technology（海军工程中心，皇家理工学院）；department of Aeronautics and Astronautics, Massachusetts Institute of Technology（航空与航天系，麻省理工学院）；Division of Robotics, Perception and Learning, KTH Royal Institute of Technology（机器人、感知与学习系，皇家理工学院）
