Many estimation, planning, and optimal control problems in robotics have an optimization
problem at their core. In most of these optimization problems, the objective to be maximized …

We provide an open-source C++ library for real-time metric-semantic visual-inertial
Simultaneous Localization And Mapping (SLAM). The library goes beyond existing visual …

Direct methods for visual odometry (VO) have gained popularity for their capability to exploit
information from all intensity gradients in the image. However, low computational speed as …

This paper presents a visual-inertial odometry framework that tightly fuses inertial
measurements with visual data from one or more cameras, by means of an iterated …

Simultaneous localization and mapping (SLAM) is one of the fundamental areas of research
in robotics and environment reconstruction. State-of-the-art solutions have advanced …

We present a unified representation for actionable spatial perception: 3D Dynamic Scene
Graphs. Scene graphs are directed graphs where nodes represent entities in the scene (eg …

FlightGoggles is a photorealistic sensor simulator for perception-driven robotic vehicles. The
key contributions of FlightGoggles are twofold. First, FlightGoggles provides photorealistic …

Simultaneous Localization and Mapping (SLAM) is considered to be an essential capability
for intelligent vehicles and mobile robots. However, most of the current lidar SLAM …

We study a visual-inertial navigation (VIN) problem in which a robot needs to estimate its
state using an on-board camera and an inertial sensor, without any prior knowledge of the …

Localization and mapping with heterogeneous multisensor fusion have been prevalent in
recent years. To adequately fuse multimodal sensor measurements received at different time …