scholarly journals Monocular Vision SLAM for Indoor Aerial Vehicles

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Koray Çelik ◽  
Arun K. Somani
Keyword(s):  
Indoor Navigation ◽  
Monocular Vision ◽  
Indoor Environments ◽  
Feature Points ◽  
Monocular Camera ◽  
Aerial Vehicles ◽  
Navigation Strategy ◽  
Aerial Vehicle ◽  
Technological Challenge ◽  
Limited Sensing

This paper presents a novel indoor navigation and ranging strategy via monocular camera. By exploiting the architectural orthogonality of the indoor environments, we introduce a new method to estimate range and vehicle states from a monocular camera for vision-based SLAM. The navigation strategy assumes an indoor or indoor-like manmade environment whose layout is previously unknown, GPS-denied, representable via energy based feature points, and straight architectural lines. We experimentally validate the proposed algorithms on a fully self-contained microaerial vehicle (MAV) with sophisticated on-board image processing and SLAM capabilities. Building and enabling such a small aerial vehicle to fly in tight corridors is a significant technological challenge, especially in the absence of GPS signals and with limited sensing options. Experimental results show that the system is only limited by the capabilities of the camera and environmental entropy.

Search and Rescue Using Multiple Drones in Post-Disaster Situation

2016 ◽  
Vol 04 (01) ◽  
pp. 83-96 ◽  
Author(s):  
Jin Q. Cui ◽  
Swee King Phang ◽  
Kevin Z. Y. Ang ◽  
Fei Wang ◽  
Xiangxu Dong ◽  
...  
Keyword(s):  
Controller Design ◽  
Indoor Navigation ◽  
Search And Rescue ◽  
Urban Search And Rescue ◽  
Robust Controller ◽  
Aerial Vehicles ◽  
Disaster Situation ◽  
Aerial Vehicle ◽  
Post Disaster ◽  
Robust Controller Design

We present the development and application of multiple autonomous aerial vehicles in urban search and rescue missions. The missions are designed by the 2014 International Micro Aerial Vehicle Competition, held in Delft, the Netherlands, August 2014. Different mission tasks are identified for search and rescue missions, such as aerial photography, low altitude flight in urban environment, indoor navigation and rooftop landing. These tasks are all of paramount importance for rescuers in a disaster-hit place. We have designed a team of micro aerial vehicles with specific configurations to meet the mission requirements. A range of key technologies have been developed, including robust controller design, real-time map stitching, indoor navigation and roof-top perching. The proposed solutions are successfully demonstrated in the competition.

scholarly journals A Doorway Detection and Direction (3Ds) System for Social Robots via a Monocular Camera

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2477 ◽  
Author(s):  
Kamal M. Othman ◽  
Ahmad B. Rad
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Navigation System ◽  
Social Robot ◽  
Indoor Navigation ◽  
Indoor Environments ◽  
Robotic Navigation ◽  
Monocular Camera ◽  
Simulation Results ◽  
Novel Algorithm

In this paper, we propose a novel algorithm to detect a door and its orientation in indoor settings from the view of a social robot equipped with only a monocular camera. The challenge is to achieve this goal with only a 2D image from a monocular camera. The proposed system is designed through the integration of several modules, each of which serves a special purpose. The detection of the door is addressed by training a convolutional neural network (CNN) model on a new dataset for Social Robot Indoor Navigation (SRIN). The direction of the door (from the robot’s observation) is achieved by three other modules: Depth module, Pixel-Selection module, and Pixel2Angle module, respectively. We include simulation results and real-time experiments to demonstrate the performance of the algorithm. The outcome of this study could be beneficial in any robotic navigation system for indoor environments.

Improved Vision-Based Algorithm for Unmanned Aerial Vehicles Autonomous Landing

2013 ◽  
Vol 273 ◽  
pp. 560-565 ◽  
Author(s):  
Yun Ji Zhao ◽  
Hai Long Pei
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicles ◽  
Feature Points ◽  
Autonomous Landing ◽  
Detection And Tracking ◽  
Aerial Vehicles ◽  
Camshift Algorithm ◽  
Aerial Vehicle ◽  
Speed Up ◽  
Improved Algorithm

In vision-based autonomous landing system of UAV (Unmanned Aerial Vehicle), the efficiency of object detection and tracking will directly affect the control system. An improved algorithm of SURF (Speed Up Robust Features) will resolve the problem which is inefficiency of the SURF algorithm in the autonomous landing system of UAV. The improved algorithm is composed of three steps: first, detect the region of the target using the Camshift algorithm; second, detect the feature points in the region of the above acquired using the SURF algorithm; third, do the matching between the template target and the region of target in frame. The results of experiments and theoretical analysis testify the efficiency of the algorithm.

scholarly journals Pose Measurement for Unmanned Aerial Vehicle Based on Rigid Skeleton

2021 ◽  
Vol 11 (4) ◽  
pp. 1373
Author(s):  
Jingyu Zhang ◽  
Zhen Liu ◽  
Guangjun Zhang
Keyword(s):  
Measurement Errors ◽  
Structural Characteristics ◽  
Geometric Model ◽  
Formation Flight ◽  
Depth Information ◽  
Feature Points ◽  
Feature Point Extraction ◽  
Aerial Vehicle ◽  
Uav Navigation ◽  
Rigid Skeleton

Pose measurement is a necessary technology for UAV navigation. Accurate pose measurement is the most important guarantee for a UAV stable flight. UAV pose measurement methods mostly use image matching with aircraft models or 2D points corresponding with 3D points. These methods will lead to pose measurement errors due to inaccurate contour and key feature point extraction. In order to solve these problems, a pose measurement method based on the structural characteristics of aircraft rigid skeleton is proposed in this paper. The depth information is introduced to guide and label the 2D feature points to eliminate the feature mismatch and segment the region. The space points obtained from the marked feature points fit the space linear equation of the rigid skeleton, and the UAV attitude is calculated by combining with the geometric model. This method does not need cooperative identification of the aircraft model, and can stably measure the position and attitude of short-range UAV in various environments. The effectiveness and reliability of the proposed method are verified by experiments on a visual simulation platform. The method proposed can prevent aircraft collision and ensure the safety of UAV navigation in autonomous refueling or formation flight.

scholarly journals Robust autonomous flight in cluttered environment using a depth sensor

2020 ◽  
Vol 12 ◽  
pp. 175682932092452
Author(s):  
Liang Lu ◽  
Alexander Yunda ◽  
Adrian Carrio ◽  
Pascual Campoy
Keyword(s):  
High Speed ◽  
Point Clouds ◽  
Depth Sensor ◽  
Cluttered Environments ◽  
Industrial Plants ◽  
Cluttered Environment ◽  
Navigation Strategy ◽  
Physical Sensors ◽  
Aerial Vehicle ◽  
Planning Objective

This paper presents a novel collision-free navigation system for the unmanned aerial vehicle based on point clouds that outperform compared to baseline methods, enabling high-speed flights in cluttered environments, such as forests or many indoor industrial plants. The algorithm takes the point cloud information from physical sensors (e.g. lidar, depth camera) and then converts it to an occupied map using Voxblox, which is then used by a rapid-exploring random tree to generate finite path candidates. A modified Covariant Hamiltonian Optimization for Motion Planning objective function is used to select the best candidate and update it. Finally, the best candidate trajectory is generated and sent to a Model Predictive Control controller. The proposed navigation strategy is evaluated in four different simulation environments; the results show that the proposed method has a better success rate and a shorter goal-reaching distance than the baseline method.

scholarly journals A Flow Analysis Using a Water Tunnel of an Innovative Unmanned Aerial Vehicle

2021 ◽  
Vol 11 (13) ◽  
pp. 5772
Author(s):  
Dawid Lis ◽  
Adam Januszko ◽  
Tadeusz Dobrocinski
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Rapid Development ◽  
Lift Coefficient ◽  
Flow Analysis ◽  
Water Tunnel ◽  
Dual Use ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Technical Construction

The purpose of this article is to present and discuss the results of a non-standard unnamed aerial vehicle construction with a constant cross-section square-shaped avionic profile. Based on the model’s in-air observed maneuverability, the research of avionic construction behavior was carried out in a water tunnel. The results show the model’s specific lift capabilities in comparison to classical avionic constructions. The characteristic results of the lift coefficient showed that the unmanned aerial vehicle presents favorable features than classic avionic constructions. The model was created with the prospect of using it in the future for dual-use purposes, where unmanned aerial vehicles are currently experiencing very rapid development. When creating the prototype, the focus was on low production cost, as well as convenience in operation. The development of this type of breakthrough avionic solution, which shows extraordinary maneuverability, may contribute to increasing the popularity and, above all, the availability of unmanned aerial vehicles for the largest possible group of recipients because of high avionic properties in relation to the technical construction complexity.

scholarly journals A new nonlinear lifting line method for aerodynamic analysis and deep learning modeling of small unmanned aerial vehicles

2021 ◽  
Vol 13 ◽  
pp. 175682932110168
Author(s):  
Hasan Karali ◽  
Gokhan Inalhan ◽  
M Umut Demirezen ◽  
M Adil Yukselen
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Deep Learning ◽  
Unmanned Aerial Vehicles ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Computationally Intensive ◽  
Lifting Line ◽  
Lifting Line Method ◽  
Nonlinear Aerodynamic

In this work, a computationally efficient and high-precision nonlinear aerodynamic configuration analysis method is presented for both design optimization and mathematical modeling of small unmanned aerial vehicles. First, we have developed a novel nonlinear lifting line method which (a) provides very good match for the pre- and post-stall aerodynamic behavior in comparison to experiments and computationally intensive tools, (b) generates these results in order of magnitudes less time in comparison to computationally intensive methods such as computational fluid dynamics. This method is further extended to a complete configuration analysis tool that incorporates the effects of basic fuselage geometries. Moreover, a deep learning based surrogate model is developed using data generated by the new aerodynamic tool that can characterize the nonlinear aerodynamic performance of unmanned aerial vehicles. The major novel feature of this model is that it can predict the aerodynamic properties of unmanned aerial vehicle configurations by using only geometric parameters without the need for any special input data or pre-process phase as needed by other computational aerodynamic analysis tools. The obtained black-box function can calculate the performance of an unmanned aerial vehicle over a wide angle of attack range on the order of milliseconds, whereas computational fluid dynamics solutions take several days/weeks in a similar computational environment. The aerodynamic model predictions show an almost 1-1 coincidence with the numerical data even for configurations with different airfoils that are not used in model training. The developed model provides a highly capable aerodynamic solver for design optimization studies as demonstrated through an illustrative profile design example.

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