Over the last decade, the use of autonomous drone systems for surveying, search and
rescue, or last-mile delivery has increased exponentially. With the rise of these applications …

While neural rendering has demonstrated impressive capabilities in 3D scene
reconstruction and novel view synthesis, it heavily relies on high-quality sharp images and …

Accurate and robust localization and map** are essential components for most
autonomous robots. In this paper, we propose a simultaneous localization and map** …

An open research question in robotics is how to combine the benefits of model-free
reinforcement learning (RL)—known for its strong task performance and flexibility in …

Simultaneous localization and map** (SLAM) is a fundamental task for numerous
applications such as autonomous navigation and exploration. Despite many SLAM datasets …

Visual-inertial odometry (VIO) has demonstrated re-markable success due to its low-cost
and complementary sensors. However, existing VIO methods lack the general-ization ability …

Underwater robotic surveys can be costly due to the complex working environment and the
need for various sensor modalities. While underwater simulators are essential, many …

Data-driven methods such as reinforcement and imitation learning have achieved
remarkable success in robot autonomy. However, their data-centric nature still hinders them …