Tightly Coupled GPS and Dead-Reckoning Navigation for Fleet Management Applications
Related publications (48)
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
Autonomous navigation of small UAVs is typically based on the integration of inertial navigation systems (INS) together with global navigation satellite systems (GNSS). However, GNSS signals can face various forms of interference affecting their continuous ...
The dominant navigation system for small civilian UAVs today is based on integration of inertial navigation system (INS) and global navigation satellite system (GNSS). This strategy works well to navigate the UAV, as long as proper reception of GNSS signal ...
The success of drone missions is incumbent on an accurate determination of the drone pose and velocity, which are collectively estimated by fusing iner- tial measurement unit and global navigation satellite system (GNSS) mea- surements. However, during a G ...
Despite the importance and pervasiveness of Wikipedia as one of the largest platforms for open knowledge, surprisingly little is known about how people navigate its content when seeking information. To bridge this gap, we present the first systematic large ...
The success of drone missions is incumbent on an accurate determination of the drone pose and velocity, which are collectively estimated by fusing inertial measurement unit and global navigation satellite system (GNSS) measurements. However, during a GNSS ...
This paper presents extensions and practical realization of a previously proposed novel approach to navigation and sensor integration for small unmanned aerial vehicles (UAV). The proposed approach employs vehicle dynamic model (VDM) as process model withi ...
Proper modeling of stochastic errors in inertial sensors plays a crucial role in the achievable quality of GNSS-INS integration especially with low-cost inertial sensors. Generalized Method of Wavelet Moments (GMWM) can model the underlying process for suc ...
A realistic rendezvous and docking navigation solution applicable to CubeSats is investigated. The scalability analysis of the ESA Autonomous Transfer Vehicle Guidance, Navigation & Control (GNC) performances and the Russian docking system, shows that the ...
The performance of vehicle dynamic model (VDM)-based navigation largely depends on the accurate determination of aerodynamic coefficients that are unknown a priori. Among different techniques, such as model simulations or experimental analysis in a wind tu ...
The Vehicle Dynamic Model (VDM) based navigation of fixed-wing drones determines the airborne trajectory in conjunction with Inertial Measurement Unit (IMU) sensors. Without Global Navigation Satellite Systems (GNSS) signals, this method estimates navigati ...