Quadrotor UAV indoor localization using embedded stereo camera

Localization of Small-Size Unmanned Air Vehicles (UAVs) such as the Quadrotors in Global Positioning System (GPS)-denied environment such as indoors has been done using various techniques. Most of the experiment indoors that requires localization of UAVs, used cameras or ultrasonic sensors installed indoor or applied indoor environment modification such as patching (Infra Red) IR and visual markers. While these systems have high accuracy for the UAV localization, they are expensive and have less practicality in real situations. In this paper a system consisting of a stereo camera embedded on a quadrotor UAV (QUAV) for indoor localization was proposed. The optical flow data from the stereo camera then are fused with attitude and acceleration data from our sensors to get better estimation of the quadrotor location. The quadrotor altitude is estimated using Scale Invariant Feature Transform (SIFT) Feature Stereo Matching in addition to the one computed using optical flow. To avoid latency due to computational time, image processing and the quadrotor control are processed threads and core allocation. The performance of our QUAV altitude estimation is better compared to single-camera embedded QUAVs due to the stereo camera triangulation, where it leads to better estimation of the x-y position using optical flow when fused together

Bio-inspired TauPilot for automated aerial 4D docking and landing of Unmanned Aircraft Systems

This paper presents the development and experimental validation of a bio-inspired autopilot, called TauPilot, that is based on the ecological Tau Theory proposed by the psychologist David Lee. Tau theory postulates that animals and humans use the tau (τ) variable (or Time-To-Contact) and simple guidance strategies to prospectively control most of their purposeful movements. This research investigates the feasibility and effectiveness of applying tau theory principles for guiding some crucial maneuvers of Unmanned Aircraft Systems (UAS) such as braking, automated aerial docking, automatic landing and moving target interception. The developed TauPilot includes a tau-Guidance system, a tau-Navigation system and a tau-Controller, resulting in 4D (time as the fourth dimension) GN&C system that has the capability to accurately fit maneuvers or actions into 4D slots using only a universal temporal variable tau. TauPilot has been integrated into two rotorcraft UAS and demonstrated in more than one thousand (about 1114) successful tau-controlled flights

Real-time wind speed estimation and compensation for improved flight

This paper presents the development and experimental validation of a prototype system for online estimation and compensation of wind disturbances onboard small Rotorcraft unmanned aerial systems (RUAS). The proposed approach consists of integrating a small pitot-static system onboard the vehicle and using simple but effective algorithms for estimating the wind speed in real time. The baseline flight controller has been augmented with a feed-forward term to compensate for these wind disturbances, thereby improving the flight performance of small RUAS in windy conditions. The paper also investigates the use of online airspeed measurements in a closed-loop for controlling the RUAS forward motion without the aid of a global positioning system (GPS). The results of more than 80 flights with a RUAS confirm the validity of our approach

Flight control of a small helicopter in unknown wind conditions

This paper presents a novel application of a two-time scale controller, using a disturbance observer, for the hover flight control of a Rotary wing Unmanned Aerial Vehicle (RUAV). Flapping and servo dynamics, important from a practical point of view, are included in the RUAV model. The two-time scale controller takes advantage of the ‘decoupling’ of the translational and rotation dynamics of the rigid body, resulting in a two-level hierarchical control scheme. The inner loop controller (attitude control) tracks the attitude commands generated by the outer loop controller and sets the main rotor thrust vector, while the outer loop controller (position control) tracks the reference position. The proposed controller uses the disturbance observer to approximate the external disturbances such as wind gusts. Hover flight simulation results are presented in this paper using the proposed backstepping-based controller

Three Nested Kalman Filters-Based Algorithm for Real-Time Estimation of Optical Flow, UAV Motion and Obstacles Detection

Abstract-We aim at developing a vision-based autopilot for autonomous small aerial vehicle applications. This paper presents a new approach for the estimation of optical flow, aircraft motion and scene structure (range map), using monocular vision and inertial data. The proposed algorithm is based on 3 Nested Kalman Filters (3NKF) and results in an efficient and robust estimation process. The 3NKF-based algorithm was tested extensively in simulation using synthetic images, and in real-time experiments. Index Terms-Small flying robots, optical flow computation, structure from motion, vision-based autopilot

Editorial for the JFR special issue on low altitude flight of UAVs

This special issue of the Journal of Field Robotics focuses on low altitude flight of UAVs with a particular emphasis on fully implemented systems that were tested in relevant environments or deployed in regular operations

Observing geomorphological change on an evolving coastal sand dune using SLAM-based UAV LiDAR

Following over 20 years of manned airborne LiDAR in the remote sensing of geomorphological change in coastal environments, rapid advancements in unmanned aerial vehicle (UAV) technologies have expanded the possibilities of acquiring very high-resolution data efficiently over spatial-temporal scales not previously feasible. This study employed a new Simultaneous Localisation and Mapping (SLAM)–based LiDAR system (“Hovermap”) across a segment of coastal sand dune of Bribie Island, Queensland, Australia. The study area was identified by the local council as an area of interest over concern that continued erosion at an existing blowout could result in cutting off northern Bribie Island and adversely affect hydrodynamic processes of Pumicestone Passage, its shoreline, and its associated infrastructure. Here, we employed the Hovermap within a multi-temporal design in which four, quarterly, surveys undertaken over a 9-month period from July 2017 to April 2018. On the first survey, a Leica P40 (P40) terrestrial laser scanner (TLS) was also deployed across the study area to facilitate a performance comparison. Hovermap reported a mean point cloud density of 2532 ± 170 pts.·m-2, ground sample distance (GSD) of 0.02 ± 0.001 m, and RMSE of 0.050 ± 0.31 m relative to ground control points (GCPs). Three-dimensional mesh objects were derived from all point clouds obtained and evaluated in terms of elevation and slope with mesh-to-mesh deviations and volumetric change (cubature) analysis examined over consecutive surveys. The Hovermap closely matched results of the P40 with measures of elevation and slope differing by approximately 2% and 7%, respectively. Mean vertical deviation (0.01 ± 0.03 m) and cubature (~ 2.5 m3 net difference) results also showed close agreement. Due to stable wave conditions between the first three surveys, minimal changes in beach topography were observed, whilst pronounced erosion and scarping of the foredune were measured during the final survey. This erosion was evidenced from changes in mean elevation (− 16%), slope (+ 25%), and deviation (+ 86%) relative to the mean measurements over the first three survey dates. In addition, a net loss of approximately -1295 m3 of sand was measured between the final two survey dates (January–April 2018). This is supported by local marine weather data in which a significant increase in local wind speeds (ANOVA, F(1,180) = 6.257, p = 0.013) and wave heights (ANOVA F(1,180) = 41.769, p ≤ 0.001) were recorded over the same interval. The results presented here are first to demonstrate that UAV LiDAR performance was robust in a typical, moderate-energy, sandy beach and is suited for the detection and evaluation of coastal morphologic change at microspatial and temporal scales