Visual Navigation in Real-World Indoor Environments Using End-to-End Deep Reinforcement Learning

Visual navigation is essential for many applications in robotics, from manipulation, through mobile robotics to automated driving. Deep reinforcement learning (DRL) provides an elegant map-free approach integrating image processing, localization, and planning in one module, which can be trained and therefore optimized for a given environment....

Robust Navigation Framework for Proximity Operations around Uncooperative Spacecraft: A monocular vision-based navigation approach using deep learning

Autonomous vision-based navigation is a crucial element for space applications involving a potentially uncooperative target, such as proximity operations for on-orbit servicing or active debris removal. Due to low mass and power characteristics, monocular vision sensors are an attractive choice for onboard vision-based navigation systems. This...

Vision-Based Reinforcement Learning for the guidance of an AR Drone 2

Reinforcement Learning (RL) has been applied to teach quadcopters guidance tasks. Most applications rely on position information from an absolute reference<br/>system such as Global Positioning System (GPS). The dependence on "absolute<br/>position" information is a general limitation in the autonomous flight of Unmanned Aerial Vehicles (UAVs)....