scholarly journals Cooperative Localization of Drones by using Interval Methods

2020 ◽  
Vol 24 (3) ◽  
pp. 557-572
Author(s):  
Ide Flore Kenmogne ◽  
Vincent Drevelle ◽  
Eric Marchand
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Pose Estimation ◽  
Interval Analysis ◽  
Constraint Propagation ◽  
Interval Methods ◽  
Cooperative Localization ◽  
Position Accuracy ◽  
Aerial Vehicles ◽  
Bounded Error ◽  
Real Robot

In this article we address the problem of cooperative pose estimation in a group of unmanned aerial vehicles (UAV) in a bounded error context. The UAVs are equipped with cameras to track landmarks positions, and a communication and ranging system to cooperate with their neighbours. Measurements are represented by intervals, and constraints are expressed on the robots poses (positions and orientations). Each robot of the group first computes a pose domain using only its sensors measurements using set inversion via interval analysis. Then, through position boxes exchange, positions are cooperatively refined by constraint propagation in the group. Results with real robot data are presented, and show that the position accuracy is improvedthanks to cooperation.

scholarly journals Ultra-wideband based cooperative relative localization algorithm and experiments for multiple unmanned aerial vehicles in GPS denied environments

2017 ◽  
Vol 9 (3) ◽  
pp. 169-186 ◽  
Author(s):  
Kexin Guo ◽  
Zhirong Qiu ◽  
Wei Meng ◽  
Lihua Xie ◽  
Rodney Teo
Keyword(s):  
Kalman Filter ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Extended Kalman Filter ◽  
Ultra Wideband ◽  
Cooperative Localization ◽  
Relative Localization ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Displacement Measurements

This article puts forward an indirect cooperative relative localization method to estimate the position of unmanned aerial vehicles (UAVs) relative to their neighbors based solely on distance and self-displacement measurements in GPS denied environments. Our method consists of two stages. Initially, assuming no knowledge about its own and neighbors’ states and limited by the environment or task constraints, each unmanned aerial vehicle (UAV) solves an active 2D relative localization problem to obtain an estimate of its initial position relative to a static hovering quadcopter (a.k.a. beacon), which is subsequently refined by the extended Kalman filter to account for the noise in distance and displacement measurements. Starting with the refined initial relative localization guess, the second stage generalizes the extended Kalman filter strategy to the case where all unmanned aerial vehicles (UAV) move simultaneously. In this stage, each unmanned aerial vehicle (UAV) carries out cooperative localization through the inter-unmanned aerial vehicle distance given by ultra-wideband and exchanging the self-displacements of neighboring unmanned aerial vehicles (UAV). Extensive simulations and flight experiments are presented to corroborate the effectiveness of our proposed relative localization initialization strategy and algorithm.

scholarly journals POSE ESTIMATION OF UNMANNED AERIAL VEHICLES BASED ON A VISION-AIDED MULTI-SENSOR FUSION

2016 ◽  
Vol XLI-B6 ◽  
pp. 193-199
Author(s):  
G. Abdi ◽  
F. Samadzadegan ◽  
F. Kurz
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Pose Estimation ◽  
Reference Data ◽  
Low Cost ◽  
Navigation Systems ◽  
Motion Model ◽  
Robust Solution ◽  
Working Cycle ◽  
Aerial Vehicles ◽  
Height Data

GNSS/IMU navigation systems offer low-cost and robust solution to navigate UAVs. Since redundant measurements greatly improve the reliability of navigation systems, extensive researches have been made to enhance the efficiency and robustness of GNSS/IMU by additional sensors. This paper presents a method for integrating reference data, images taken from UAVs, barometric height data and GNSS/IMU data to estimate accurate and reliable pose parameters of UAVs. We provide improved pose estimations by integrating multi-sensor observations in an EKF algorithm with IMU motion model. The implemented methodology has demonstrated to be very efficient and reliable for automatic pose estimation. The calculated position and attitude of the UAV especially when we removed the GNSS from the working cycle clearly indicate the ability of the purposed methodology.

scholarly journals Ultra-Wideband Based Pose Estimation for Small Unmanned Aerial Vehicles

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 57526-57535 ◽  
Author(s):  
Michael Strohmeier ◽  
Thomas Walter ◽  
Julian Rothe ◽  
Sergio Montenegro
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Pose Estimation ◽  
Ultra Wideband ◽  
Aerial Vehicles

scholarly journals POSE ESTIMATION OF UNMANNED AERIAL VEHICLES BASED ON A VISION-AIDED MULTI-SENSOR FUSION

2016 ◽  
Vol XLI-B6 ◽  
pp. 193-199 ◽  
Author(s):  
G. Abdi ◽  
F. Samadzadegan ◽  
F. Kurz
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Pose Estimation ◽  
Reference Data ◽  
Low Cost ◽  
Navigation Systems ◽  
Motion Model ◽  
Robust Solution ◽  
Working Cycle ◽  
Aerial Vehicles ◽  
Height Data

GNSS/IMU navigation systems offer low-cost and robust solution to navigate UAVs. Since redundant measurements greatly improve the reliability of navigation systems, extensive researches have been made to enhance the efficiency and robustness of GNSS/IMU by additional sensors. This paper presents a method for integrating reference data, images taken from UAVs, barometric height data and GNSS/IMU data to estimate accurate and reliable pose parameters of UAVs. We provide improved pose estimations by integrating multi-sensor observations in an EKF algorithm with IMU motion model. The implemented methodology has demonstrated to be very efficient and reliable for automatic pose estimation. The calculated position and attitude of the UAV especially when we removed the GNSS from the working cycle clearly indicate the ability of the purposed methodology.

On-board visual navigation system for unmanned aerial vehicles autonomous aerial refueling

2017 ◽  
Vol 233 (4) ◽  
pp. 1193-1203 ◽  
Author(s):  
Yan Xu ◽  
Haibin Duan ◽  
Cong Li ◽  
Yimin Deng
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Pose Estimation ◽  
Navigation System ◽  
Visual Navigation ◽  
Aerial Refueling ◽  
Estimation Algorithms ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Hardware Configuration ◽  
Series Of Experiments

In this paper, an on-board binocular visual navigation system based on unmanned aerial vehicles platform is designed for autonomous aerial refueling. The hardware configuration of the entire platform is introduced. Vision algorithms including target tracking, feature extraction, and pose estimation are employed for measuring the relation between two unmanned aerial vehicles. Two situations are considered under long and short distances to make this procedure flexible. Four pose estimation algorithms are implemented and compared in this research. A series of experiments are conducted to verify the feasibility and effectiveness of aerial refueling on the unmanned aerial vehicle platform.

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