The Kalman filter—or, more precisely, the extended Kalman filter (EKF)—is a fundamental
engineering tool that is pervasively used in control and robotics and for various estimation …

The present thesis explores the use of non-linear state errors to devise extended Kalman
filters (EKFs). First we depart from the theory of invariant observers on Lie groups and …

This book studies how autonomous aerial robots physically interact with the surrounding
environment. Intended to promote the advancement of aerial physical interaction, it analyzes …

Localization is the crucial problem for mobile robot navigation. For indoor mobile robot,
since a global positioning system (GPS) is incapable, another promising technique to detect …

Localization in indoor environments is a technique that estimates the robot's pose by fusing
data from onboard motion sensors with readings of the environment, in our case obtained by …

We propose a unifying and versatile framework for a class of discrete time systems whose
state is an element of a general group G, that we call linear observed systems on groups …

We examine the problem of determining the relative time delay between IMU and camera
data streams. The primary difficulty is that the correspondences between measurements …

Accurately measuring the distance traversed by a subject, commonly referred to as
odometry, in indoor environments is of fundamental importance in many applications such …

Relative attitude formation control systems are developed for multiple spacecraft, based on
the line-of-sight measurements between spacecraft in formation. The proposed control …

This paper addresses the problem of calibrating a pair of cameras, a Microsoft Kinect sensor
and an inertial measurement unit (IMU) mounted at the head of a humanoid robot with …