We are witnessing the advent of a new era of robots—drones—that can autonomously fly in
natural and man-made environments. These robots, often associated with defence …

This paper presents a complete review of computer vision algorithms and vision-based
intelligent applications, that are developed in the field of the Unmanned Aerial Vehicles …

This letter presents a computationally efficient and robust LiDAR-inertial odometry
framework. We fuse LiDAR feature points with IMU data using a tightly-coupled iterated …

In this paper, we propose a novel LiDAR-Inertial-Visual sensor fusion framework termed R 3
LIVE, which takes advantage of measurement of LiDAR, inertial, and visual sensors to …

In this letter, we propose a robust, real-time tightly-coupled multi-sensor fusion framework,
which fuses measurements from LiDAR, inertial sensor, and visual camera to achieve robust …

LiDAR odometry and mapping (LOAM) has been playing an important role in autonomous
vehicles, due to its ability to simultaneously localize the robot's pose and build high …

This paper describes a collection of optimization algorithms for achieving dynamic planning,
control, and state estimation for a bipedal robot designed to operate reliably in complex …

How do you learn to navigate an Unmanned Aerial Vehicle (UAV) and avoid obstacles? One
approach is to use a small dataset collected by human experts: however, high capacity …

Dynamically changing environments, unreliable state estimation, and operation under
severe resource constraints are fundamental challenges that limit the deployment of small …

We explore the challenges of planning trajectories for quadrotors through cluttered indoor
environments. We extend the existing work on polynomial trajectory generation by …