We present the first perception-aware model predictive control framework for quadrotors that
unifies control and planning with respect to action and perception objectives. Our framework …

In this work, we present a perception-aware path-planning pipeline for Unmanned Aerial
Vehicles (UAVs) for navigation in challenging environments. The objective is to reach a …

To reach a given destination safely and accurately, a micro aerial vehicle needs to be able
to avoid obstacles and minimize its state estimation uncertainty at the same time. To achieve …

In this paper, we propose a novel path planning framework for autonomous exploration in
unknown environments using a mobile robot. A graph structure is incrementally constructed …

In this study, we address an exploration problem when constructing complete 3D models in
an unknown environment using a Micro-Aerial Vehicle. Most previous exploration methods …

This work presents a semantic-aware path-planning pipeline for Unmanned Aerial Vehicles
(UAVs) using deep reinforcement learning for vision-based navigation in challenging …

In addition to conventional ground rovers, the Mars 2020 mission will send a helicopter to
Mars. The copter's highresolution data helps the rover to identify small hazards such as …

Highly accurate real‐time localization is of fundamental importance for the safety and
efficiency of planetary rovers exploring the surface of Mars. Mars rover operations rely on …

Various perception-aware planning approaches have attempted to enhance the state
estimation accuracy during maneuvers, while the feature matchability among frames, a …

Information gathering algorithms play a key role in unlocking the potential of robots for
efficient data collection in a wide range of applications. However, most existing strategies …