Multi-UAV collaborative system with a feature fast matching algorithm

We present a real-time monocular simultaneous localization and mapping(SLAM)system with a new distributed structure for multi-UAV collaboration tasks.The system is different from other general SLAM systems in two aspects:First,it does not aim to build a global map,but to estimate the latest relative position between nearby vehicles;Second,there is no centralized structure in the proposed system,and each vehicle owns an individual metric map and an ego-motion estimator to obtain the relative position between its own map and the neighboring vehicles'.To realize the above characteristics in real time,we demonstrate an innovative feature description and matching algorithm to avoid catastrophic expansion of feature point matching workload due to the increased number of UAVs.Based on the hash and principal component analysis,the matching time complexity of this algorithm can be reduced from 0(logN)to 0(1).To evaluate the performance,the algorithm is verified on the acknowledged multi-view stereo benchmark dataset,and excellent results are obtained.Finally,through the simulation and real flight experiments,this improved SLAM system with the proposed algorithm is validated.

Bearing-only Visual SLAM for Small Unmanned Aerial Vehicles in GPS-denied Environments

This paper presents a hierarchical simultaneous localization and mapping（SLAM） system for a small unmanned aerial vehicle（UAV） using the output of an inertial measurement unit（IMU） and the bearing-only observations from an onboard monocular camera.A homography based approach is used to calculate the motion of the vehicle in 6 degrees of freedom by image feature match.This visual measurement is fused with the inertial outputs by an indirect extended Kalman filter（EKF） for attitude and velocity estimation.Then,another EKF is employed to estimate the position of the vehicle and the locations of the features in the map.Both simulations and experiments are carried out to test the performance of the proposed system.The result of the comparison with the referential global positioning system/inertial navigation system（GPS/INS） navigation indicates that the proposed SLAM can provide reliable and stable state estimation for small UAVs in GPS-denied environments.