Obstacle detection technique using multi sensor integration for small unmanned aerial vehicle

2017 ◽  
Vol 8 (2) ◽  
pp. 441 ◽  
Author(s):  
Muhammad Faiz Bin Ramli ◽  
Syariful Syafiq Shamsudin ◽  
Ari Legowo
Keyword(s):  
Indoor Environment ◽  
Detection System ◽  
Obstacle Detection ◽  
Sensor Integration ◽  
Feature Points ◽  
Advantages And Disadvantages ◽  
System A ◽  
Small Uav ◽  
Image Capturing ◽  
Aerial Vehicle

<p class="Abstract">Achieving a robust obstacle detection system for small UAV is very challenging. Due to size and weight constraints, very limited detection sensors can be equipped in the system. Prior works focused on a single sensing device which is either camera or range sensors based. However, these sensors have their own advantages and disadvantages in detecting the appearance of the obstacles. In this paper, combination of both sensors based is proposed for a small UAV obstacle detection system. A small Lidar sensor is used as the initial detector and queue for image capturing by the camera. Next, SURF algorithm is applied to find the obstacle sizes estimation by searching the connecting feature points in the image frame. Finally, safe avoidance path for UAV is determined through the exterior feature points from the estimated width of the obstacle. The proposed method was evaluated by conducting experiments in real time with indoor environment. In the experiment conducted, we successfully detect and determine a safe avoidance path for the UAV on 6 different sizes and textures of the obstacles including textureless obstacles.</p>

scholarly journals Sudden Obstacle Appearance Detection by Analyzing Flow Field Vector for Small-Sized UAV

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Muhammad Faiz Ramli ◽  
◽  
Syariful Syafiq Shamsudin ◽  
Mohd Fauzi Yaakub ◽  
◽  
...  
Keyword(s):  
Flow Field ◽  
Detection System ◽  
Wide Spectrum ◽  
Field Vector ◽  
Obstacle Detection ◽  
Physical Size ◽  
High Dependency ◽  
Small Uav ◽  
Aerial Vehicle ◽  
Work Integration

Achieving a reliable obstacle detection and avoidance system that can provide an effective safe avoidance path for small unmanned aerial vehicle (UAV) is very challenging due to its physical size and weight constraints. Prior works tend to employ the vision based-sensor as the main detection sensor but resulting to high dependency on texture appearance while not having a distance sensing capabilities. The previous system only focused on the detection of the static frontal obstacle without observing the environment which may have moving obstacles. On the other hand, most of the wide spectrum range sensors are heavy and expensive hence not suitable for small UAV. In this work, integration of different based sensors was proposed for a small UAV in detecting unpredictable obstacle appearance situation. The detection of the obstacle is accomplished by analysing the flow field vectors in the image frames sequence. The proposed system was evaluated by conducting the experiments in a real environment which consisted of different configuration of the obstacles. The results from the experiment show that the success rate for detecting unpredictable obstacle appearance is high which is 70% and above. Even though some of the introduced obstacles are considered to have poor texture appearances on their surface, the proposed obstacle detection system was still able to detect the correct appearance movement of the obstacles by detecting the edges.

scholarly journals Fall Prevention Shoes Using Camera-Based Line-Laser Obstacle Detection System

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Tzung-Han Lin ◽  
Chi-Yun Yang ◽  
Wen-Pin Shih
Keyword(s):  
Fall Prevention ◽  
Indoor Environment ◽  
Optical Axis ◽  
Detection System ◽  
The Elderly ◽  
Obstacle Detection ◽  
Critical Parameters ◽  
Will Emit ◽  
Inclined Angle ◽  
Different Levels

Fall prevention is an important issue particularly for the elderly. This paper proposes a camera-based line-laser obstacle detection system to prevent falls in the indoor environment. When obstacles are detected, the system will emit alarm messages to catch the attention of the user. Because the elderly spend a lot of their time at home, the proposed line-laser obstacle detection system is designed mainly for indoor applications. Our obstacle detection system casts a laser line, which passes through a horizontal plane and has a specific height to the ground. A camera, whose optical axis has a specific inclined angle to the plane, will observe the laser pattern to obtain the potential obstacles. Based on this configuration, the distance between the obstacles and the system can be further determined by a perspective transformation called homography. After conducting the experiments, critical parameters of the algorithms can be determined, and the detected obstacles can be classified into different levels of danger, causing the system to send different alarm messages.

scholarly journals Real-Time Obstacle Detection System in Indoor Environment for the Visually Impaired Using Microsoft Kinect Sensor

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Huy-Hieu Pham ◽  
Thi-Lan Le ◽  
Nicolas Vuillerme
Keyword(s):  
Visually Impaired ◽  
Indoor Environment ◽  
Detection System ◽  
Obstacle Detection ◽  
Microsoft Kinect ◽  
Kinect Sensor ◽  
Visually Impaired People ◽  
Positive Images ◽  
Indoor Scenarios ◽  
3D Information

Any mobility aid for the visually impaired people should be able to accurately detect and warn about nearly obstacles. In this paper, we present a method for support system to detect obstacle in indoor environment based on Kinect sensor and 3D-image processing. Color-Depth data of the scene in front of the user is collected using the Kinect with the support of the standard framework for 3D sensing OpenNI and processed by PCL library to extract accurate 3D information of the obstacles. The experiments have been performed with the dataset in multiple indoor scenarios and in different lighting conditions. Results showed that our system is able to accurately detect the four types of obstacle: walls, doors, stairs, and a residual class that covers loose obstacles on the floor. Precisely, walls and loose obstacles on the floor are detected in practically all cases, whereas doors are detected in 90.69% out of 43 positive image samples. For the step detection, we have correctly detected the upstairs in 97.33% out of 75 positive images while the correct rate of downstairs detection is lower with 89.47% from 38 positive images. Our method further allows the computation of the distance between the user and the obstacles.

Flight Path Planning of Robot for Environmental Measurement Considering Accuracy Assurance

Impact ◽  
2019 ◽  
Vol 2019 (10) ◽  
pp. 90-92
Author(s):  
Kae Doki ◽  
Yuki Funabora ◽  
Shinji Doki
Keyword(s):  
Large Scale ◽  
Highway Bridge ◽  
Climate Research ◽  
Small Uav ◽  
Inspection Process ◽  
Aerial View ◽  
Aerial Vehicle ◽  
Infrastructure Inspection ◽  
Institute Of Technology ◽  
Small Team

Every day we are seeing an increasing number of robots being employed in our day-to-day lives. They are working in factories, cleaning our houses and may soon be chauffeuring us around in vehicles. The affordability of drones too has come down and now it is conceivable for most anyone to own a sophisticated unmanned aerial vehicle (UAV). While fun to fly, these devices also represent powerful new tools for several industries. Anytime an aerial view is needed for a planning, surveillance or surveying, for example, a UAV can be deployed. Further still, equipping these vehicles with an array of sensors, for climate research or mapping, increases their capability even more. This gives companies, governments or researchers a cheap and safe way to collect vast amounts of data and complete tasks in remote or dangerous areas that were once impossible to reach. One area UAVs are proving to be particularly useful is infrastructure inspection. In countries all over the world large scale infrastructure projects like dams and bridges are ageing and in need of upkeep. Identifying which ones and exactly where they are in need of patching is a huge undertaking. Not only can this work be dangerous, requiring trained inspectors to climb these megaprojects, it is incredibly time consuming and costly. Enter the UAVs. With a fleet of specially equipped UAVs and a small team piloting them and interpreting the data they bring back the speed and safety of this work increases exponentially. The promise of UAVs to overturn the infrastructure inspection process is enticing, but there remain several obstacles to overcome. One is achieving the fine level of control and positioning required to navigate the robots around 3D structures for inspection. One can imagine that piloting a small UAV underneath a huge highway bridge without missing a single small crack is quite difficult, especially when the operators are safely on the ground hundreds of meters away. To do this knowing exactly where the vehicle is in space becomes a critical variable. The job can be made even easier if a flight plan based on set waypoints can be pre-programmed and followed autonomously by the UAV. It is exactly this problem that Dr Kae Doki from the Department of Electrical Engineering at Aichi Institute of Technology, and collaborators are focused on solving.

scholarly journals Design of bio-inspired binocular UAV detection system based on improved STC algorithm of scale transformation and occlusion detection

2021 ◽  
Vol 13 ◽  
pp. 175682932110048
Author(s):  
Huajun Song ◽  
Yanqi Wu ◽  
Guangbing Zhou
Keyword(s):  
Detection System ◽  
Rapid Development ◽  
Reference Value ◽  
Scale Transformation ◽  
Hardware System ◽  
Time Requirements ◽  
Aerial Vehicle ◽  
Spatio Temporal ◽  
Small Targets ◽  
Vision Detection

With the rapid development of drones, many problems have arisen, such as invasion of privacy and endangering security. Inspired by biology, in order to achieve effective detection and robust tracking of small targets such as unmanned aerial vehicles, a binocular vision detection system is designed. The system is composed of long focus and wide-angle dual cameras, servo pan tilt, and dual processors for detecting and identifying targets. In view of the shortcomings of spatio-temporal context target tracking algorithm that cannot adapt to scale transformation and easy to track failure in complex scenes, the scale filter and loss criterion are introduced to make an improvement. Qualitative and quantitative experiments show that the designed system can adapt to the scale changes and partial occlusion conditions in the detection, and meets the real-time requirements. The hardware system and algorithm both have reference value for the application of anti-unmanned aerial vehicle systems.

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.

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