External effects such as shocks and temperature variations affect the calibration of visual-
inertial sensor systems and thus they cannot fully rely on factory calibrations. Re-calibrations …

We present a dataset for evaluating the performance of visual-inertial odometry (VIO)
systems employing an onboard light source. The dataset consists of 39 sequences …

We describe a trajectory optimization framework that maximizes observability of one or more
user-chosen states in a nonlinear system. Our framework is based on a novel metric for …

Calibration of multi-camera systems is essential for lifelong use of vision-based headsets
and autonomous robots. In this work, we present an information-based framework for online …

Wide-area 3D data generation for complex urban environments often needs to leverage a
mixed use of data collected from both air and ground platforms, such as from aerial surveys …

We present a new approach to assisted intrinsic and extrinsic calibration with an
observability-aware visual–inertial calibration system that guides the user through the …

Capsule endoscopes have gained popularity over the last decade as minimally invasive
devices for diagnosing gastrointestinal abnormalities such as colorectal cancer. While this …

We propose an uncertainty-based sensor fusion framework for visual-inertial odometry,
which is the task of estimating relative motion using images and measurements from inertial …

In this paper we derive a new capability for robots to measure relative direction, or Angle-of-
Arrival (AOA), to other robots, while operating in non-line-of-sight and unmapped …

In this paper, we develop the analytical framework for a novel Wireless signal-based
Sensing capability for Robotics (WSR) by leveraging a robots' mobility in 3D space. It allows …