Bottle Detection in the Wild Using Low-Altitude Unmanned Aerial Vehicles

Wang, Jinwang; Guo, Wei; Pan, Tongyan; Yu, Huai; Duan, Lin; Yang, Wen

doi:10.23919/icif.2018.8455565

Cited by 31 publications

(16 citation statements)

References 5 publications

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“…We trained and evaluated our vision system based on our pervious work UAV-BD [26], a bottle image dataset under UAV perspective. It contains about 34, 791 object instances in 25, 407 images labelled by oriented bounding boxes.…”

Section: A Vision System Resultsmentioning

confidence: 99%

Toward Autonomous Rotation-Aware Unmanned Aerial Grasping

Lin,

Wang,

Yang

et al. 2018

Preprint

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Autonomous Unmanned Aerial Manipulators (UAMs) have shown promising potentials to transform passive sensing missions into active 3-dimension interactive missions, but they still suffer from some difficulties impeding their wide applications, such as target detection and stabilization. This letter presents a vision-based autonomous UAM with a 3DoF robotic arm for rotational grasping, with a compensation on displacement for center of gravity. First, the hardware, software architecture and state estimation methods are detailed. All the mechanical designs are fully provided as open-source hardware for the reuse by the community. Then, we analyze the flow distribution generated by rotors and plan the robotic arm's motion based on this analysis. Next, a novel detection approach called Rotation-SqueezeDet is proposed to enable rotationaware grasping, which can give the target position and rotation angle in near real-time on Jetson TX2. Finally, the effectiveness of the proposed scheme is validated in multiple experimental trials, highlighting it's applicability of autonomous aerial grasping in GPS-denied environments.

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Section: A Vision System Resultsmentioning

confidence: 99%

Toward Autonomous Rotation-Aware Unmanned Aerial Grasping

Lin,

Wang,

Yang

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…We trained and evaluated our vision system based on our pervious work UAV-Bottle Detection (BD) [32], a bottle image dataset under UAV perspective. It contains about 34,791 object instances in 25,407 images labeled by oriented bounding boxes.…”

Section: Methodsmentioning

confidence: 99%

Development of an Autonomous Unmanned Aerial Manipulator Based on a Real-Time Oriented-Object Detection Method

Lin

Wang

Peng

et al. 2019

Sensors

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Autonomous Unmanned Aerial Manipulators (UAMs) have shown promising potential in mobile 3-dimensional grasping applications, but they still suffer from some difficulties impeding their board applications, such as target detection and indoor positioning. For the autonomous grasping mission, the UAMs need ability to recognize the objects and grasp them. Considering the efficiency and precision, we present a novel oriented-object detection method called Rotation-SqueezeDet. This method can run on embedded-platforms in near real-time. Besides, this method can give the oriented bounding box of an object in images to enable a rotation-aware grasping. Based on this method, a UAM platform was designed and built. We have given the formulation, positioning, control, and planning of the whole UAM system. All the mechanical designs are fully provided as open-source hardware for reuse by the community. Finally, the effectiveness of the proposed scheme was validated in multiple experimental trials, highlighting its applicability of autonomous aerial rotational grasping in Global Positioning System (GPS) denied environments. We believe this system can be deployed to many potential workplaces which need UAM to accomplish difficult manipulation tasks.

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“…In this connection, Convolutional Neural Networks (CNNs) are typically employed for image processing, and they are data hungry [48]. In recent years, researchers have produced various drone-based aerial datasets to address data availability issues for different applications: among others, UAV-Bottle Dataset (UAV-BD) dataset [49] to detect the waste bottles, UAV Mosaicking and Change Detection (UMCD) dataset [50] to improve the algorithms for both change detection and mosaicking on low-altitude aerial video sequences, Okutama-Action [51] for human action detection are worth to mention. We analyzed the main drone-based datasets related to traffic monitoring applications, which we summarize in the Table 3.…”

Section: A Datasetsmentioning

confidence: 99%

A Systematic Review of Drone Based Road Traffic Monitoring System

et al. 2022

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Drone deployment has become crucial in a variety of applications, including solutions to traffic issues in metropolitan areas and highways. On the other hand, data collected via drones suffers from several problems, including a wide range of object scales, angle variations, truncation, and occlusion. To process and manipulate visual data from the drones, a variety of image processing algorithms have been employed, each with a distinct aim. Additionally, recent breakthroughs in the field of Artificial Intelligence, particularly deep learning, have attracted broad interest and are being applied to many domains in the framework of smart cities, including road traffic monitoring. The purpose of this study is to conduct a systematic review of drone-based traffic monitoring systems from a deep learning perspective. This work focuses on vehicle detection, tracking, and counting, since they are fundamental building blocks towards founding solutions for traffic congestion, flow rate and vehicle speed estimation. Additionally, drone-based datasets are examined, which face issues and problems caused by the diversity of features inherent of drone devices. The review analysis presented in this work summarizes the literature solutions provided and deployed so far and discusses future research trends in establishing a comprehensive traffic monitoring system in support of the development of smart cities INDEX TERMS deep learning, drone, smart city, traffic monitoring, uav.

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Bottle Detection in the Wild Using Low-Altitude Unmanned Aerial Vehicles

Cited by 31 publications

References 5 publications

Toward Autonomous Rotation-Aware Unmanned Aerial Grasping

Toward Autonomous Rotation-Aware Unmanned Aerial Grasping

Development of an Autonomous Unmanned Aerial Manipulator Based on a Real-Time Oriented-Object Detection Method

A Systematic Review of Drone Based Road Traffic Monitoring System

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