scholarly journals Visual MAV Tracker with Adaptive Search Region

2021 ◽  
Vol 11 (16) ◽  
pp. 7741
Author(s):  
Wooryong Park ◽  
Donghee Lee ◽  
Junhak Yi ◽  
Woochul Nam
Keyword(s):  
Real Time ◽  
Computation Time ◽  
Adaptive Strategy ◽  
Adaptive Search ◽  
Fast Computation ◽  
Search Region ◽  
Micro Aerial Vehicle ◽  
Aerial Vehicle ◽  
Online Tracking ◽  
Computation Speed

Tracking a micro aerial vehicle (MAV) is challenging because of its small size and swift motion. A new model was developed by combining compact and adaptive search region (SR). The model can accurately and robustly track MAVs with a fast computation speed. A compact SR, which is slightly larger than a target MAV, is less likely to include a distracting background than a large SR; thus, it can accurately track the MAV. Moreover, the compact SR reduces the computation time because tracking can be conducted with a relatively shallow network. An optimal SR to MAV size ratio was obtained in this study. However, this optimal compact SR causes frequent tracking failures in the presence of the dynamic MAV motion. An adaptive SR is proposed to address this problem; it adaptively changes the location and size of the SR based on the size, location, and velocity of the MAV in the SR. The compact SR without adaptive strategy tracks the MAV with an accuracy of 0.613 and a robustness of 0.086, whereas the compact and adaptive SR has an accuracy of 0.811 and a robustness of 1.0. Moreover, online tracking is accomplished within approximately 400 frames per second, which is significantly faster than the real-time speed.

Real-time bi-directional people counting using an RGB-D camera

Sensor Review ◽  
2021 ◽  
Vol 41 (4) ◽  
pp. 341-349
Author(s):  
Wahyu Rahmaniar ◽  
W.J. Wang ◽  
Chi-Wei Ethan Chiu ◽  
Noorkholis Luthfil Luthfil Hakim
Keyword(s):  
Real Time ◽  
Region Of Interest ◽  
Computation Time ◽  
Depth Image ◽  
Fast Computation ◽  
Content Type ◽  
People Counting ◽  
Rgb Images ◽  
Precision Rate ◽  
Rgb Image

Purpose The purpose of this paper is to propose a new framework and improve a bi-directional people counting technique using an RGB-D camera to obtain accurate results with fast computation time. Therefore, it can be used in real-time applications. Design/methodology/approach First, image calibration is proposed to obtain the ratio and shift values between the depth and the RGB image. In the depth image, a person is detected as foreground by removing the background. Then, the region of interest (ROI) of the detected people is registered based on their location and mapped to an RGB image. Registered people are tracked in RGB images based on the channel and spatial reliability. Finally, people were counted when they crossed the line of interest (LOI) and their displacement distance was more than 2 m. Findings It was found that the proposed people counting method achieves high accuracy with fast computation time to be used in PCs and embedded systems. The precision rate is 99% with a computation time of 35 frames per second (fps) using a PC and 18 fps using the NVIDIA Jetson TX2. Practical implications The precision rate is 99% with a computation time of 35 frames per second (fps) using a PC and 18 fps using the NVIDIA Jetson TX2. Originality/value The proposed method can count the number of people entering and exiting a room at the same time. If the previous systems were limited to only one to two people in a frame, this system can count many people in a frame. In addition, this system can handle some problems in people counting, such as people who are blocked by others, people moving in another direction suddenly, and people who are standing still.

scholarly journals Pengenalan Wajah Secara Real Time Menggunakan Metode Camshift dan Operator Erosi Berdasarkan Citra Wajah

2017 ◽  
Vol 1 (1) ◽  
pp. 8
Author(s):  
Sultoni Sultoni ◽  
Rudy Hariyanto
Keyword(s):  
Real Time ◽  
Good Accuracy ◽  
Facial Recognition ◽  
Computation Time ◽  
Research Topic ◽  
Security System ◽  
Fast Computation ◽  
Detection And Tracking ◽  
Tracking Process ◽  
The Future

Facial recognition is a research topic that is quite a lot done by researchers in recent decades, because many benefits in this study such as security system and survelliance. This research is a development or modification of previous research. Where previous research used camhshift method for detection and tracking, in this research is by performing erosion operators on the detection and tracking process using camshift. Based on the results of the test produced a fairly good accuracy and with a fairly fast computation time. So that the future can be applied to enter attendance attendance system or to masku secret room by doing engineering such as merging with microcontroller and so on, so the benefits can be more felt.

Energy-Based Design of Reconfigurable Micro Aerial Vehicle (MAV) Flight Structures

2012 ◽  
Author(s):  
James Joo ◽  
Gregory Reich ◽  
James Elgersma ◽  
Kristopher Aber
Keyword(s):  
Micro Aerial Vehicle ◽  
Aerial Vehicle ◽  
Energy Based Design

scholarly journals Run Your Visual-Inertial Odometry on NVIDIA Jetson: Benchmark Tests on a Micro Aerial Vehicle

2021 ◽  
pp. 1-1
Author(s):  
Jinwoo Jeon ◽  
Sungwook Jung ◽  
Eungchang Lee ◽  
Duckyu Choi ◽  
Hyun Myung
Keyword(s):  
Micro Aerial Vehicle ◽  
Benchmark Tests ◽  
Aerial Vehicle

scholarly journals Towards the Development of an Automatic UAV-Based Indoor Environmental Monitoring System: Distributed Off-Board Control System for a Micro Aerial Vehicle

2021 ◽  
Vol 11 (5) ◽  
pp. 2347 ◽  
Author(s):  
Jorge Solis ◽  
Christoffer Karlsson ◽  
Simon Johansson ◽  
Kristoffer Richardsson
Keyword(s):  
Control System ◽  
Environmental Monitoring ◽  
Monitoring System ◽  
Target Location ◽  
Flight Time ◽  
Distributed Control System ◽  
Micro Aerial Vehicle ◽  
Environmental Monitoring System ◽  
Rapid Changes ◽  
Aerial Vehicle

This research aims to develop an automatic unmanned aerial vehicle (UAV)-based indoor environmental monitoring system for the acquisition of data at a very fine scale to detect rapid changes in environmental features of plants growing in greenhouses. Due to the complexity of the proposed research, in this paper we proposed an off-board distributed control system based on visual input for a micro aerial vehicle (MAV) able to hover, navigate, and fly to a desired target location without considerably affecting the effective flight time. Based on the experimental results, the MAV was able to land on the desired location within a radius of about 10 cm from the center point of the landing pad, with a reduction in the effective flight time of about 28%.

scholarly journals Methodology for the Correction of the Spatial Orientation Angles of the Unmanned Aerial Vehicle Using Real Time GNSS, a Shoreline Image and an Electronic Navigational Chart

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2810
Author(s):  
Krzysztof Naus ◽  
Piotr Szymak ◽  
Paweł Piskur ◽  
Maciej Niedziela ◽  
Aleksander Nowak
Keyword(s):  
Real Time ◽  
Spatial Orientation ◽  
Orientation Angle ◽  
Satellite System ◽  
Angle Measurement ◽  
Angle Correction ◽  
Lidar Measurements ◽  
Aerial Vehicle ◽  
Marine Applications ◽  
Global Navigation Satellite

Undoubtedly, Low-Altitude Unmanned Aerial Vehicles (UAVs) are becoming more common in marine applications. Equipped with a Global Navigation Satellite System (GNSS) Real-Time Kinematic (RTK) receiver for highly accurate positioning, they perform camera and Light Detection and Ranging (LiDAR) measurements. Unfortunately, these measurements may still be subject to large errors-mainly due to the inaccuracy of measurement of the optical axis of the camera or LiDAR sensor. Usually, UAVs use a small and light Inertial Navigation System (INS) with an angle measurement error of up to 0.5∘ (RMSE). The methodology for spatial orientation angle correction presented in the article allows the reduction of this error even to the level of 0.01∘ (RMSE). It can be successfully used in coastal and port waters. To determine the corrections, only the Electronic Navigational Chart (ENC) and an image of the coastline are needed.

scholarly journals Deep Reinforcement Learning for End-to-End Local Motion Planning of Autonomous Aerial Robots in Unknown Outdoor Environments: Real-Time Flight Experiments

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2534
Author(s):  
Oualid Doukhi ◽  
Deok-Jin Lee
Keyword(s):  
Reinforcement Learning ◽  
Real Time ◽  
Autonomous Navigation ◽  
Control Technique ◽  
Local Motion ◽  
Aerial Robots ◽  
Novel Approach ◽  
Outdoor Environments ◽  
Aerial Vehicle ◽  
High Level

Autonomous navigation and collision avoidance missions represent a significant challenge for robotics systems as they generally operate in dynamic environments that require a high level of autonomy and flexible decision-making capabilities. This challenge becomes more applicable in micro aerial vehicles (MAVs) due to their limited size and computational power. This paper presents a novel approach for enabling a micro aerial vehicle system equipped with a laser range finder to autonomously navigate among obstacles and achieve a user-specified goal location in a GPS-denied environment, without the need for mapping or path planning. The proposed system uses an actor–critic-based reinforcement learning technique to train the aerial robot in a Gazebo simulator to perform a point-goal navigation task by directly mapping the noisy MAV’s state and laser scan measurements to continuous motion control. The obtained policy can perform collision-free flight in the real world while being trained entirely on a 3D simulator. Intensive simulations and real-time experiments were conducted and compared with a nonlinear model predictive control technique to show the generalization capabilities to new unseen environments, and robustness against localization noise. The obtained results demonstrate our system’s effectiveness in flying safely and reaching the desired points by planning smooth forward linear velocity and heading rates.

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