A comprehensive survey on non‐cooperative collision avoidance for micro aerial vehicles: Sensing and obstacle detection

Lü, Liang; Fasano, Giancarmine; Carrio, Adrian; Lei, Maolin; Bavle, Hriday; Campoy, Pascual

doi:10.1002/rob.22189

Cited by 10 publications

(1 citation statement)

References 152 publications

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“…To avoid intruder aircrafts that may pose a potential threat, sensing technologies are necessary for advanced preparation. According to how the information is transmitted, sensing technologies for DAA can be classified into two categories: cooperative and noncooperative [5,6]. The sensors utilized in cooperative methods include vehicle-to-vehicle communication, automatic dependent surveillance broadcast (ADS-B), and RID.…”

Section: Airborne Sensing Technologies and Collision Avoidance Strate...mentioning

confidence: 99%

Vision-Based Mid-Air Object Detection and Avoidance Approach for Small Unmanned Aerial Vehicles with Deep Learning and Risk Assessment

Lai,

Lin

2024

Remote Sensing

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With the increasing demand for unmanned aerial vehicles (UAVs), the number of UAVs in the airspace and the risk of mid-air collisions caused by UAVs are increasing. Therefore, detect and avoid (DAA) technology for UAVs has become a crucial element for mid-air collision avoidance. This study presents a collision avoidance approach for UAVs equipped with a monocular camera to detect small fixed-wing intruders. The proposed system can detect any size of UAV over a long range. The development process consists of three phases: long-distance object detection, object region estimation, and collision risk assessment and collision avoidance. For long-distance object detection, an optical flow-based background subtraction method is utilized to detect an intruder far away from the host. A mask region-based convolutional neural network (Mask R-CNN) model is trained to estimate the region of the intruder in the image. Finally, the collision risk assessment adopts the area expansion rate and bearing angle of the intruder in the images to conduct mid-air collision avoidance based on visual flight rules (VFRs) and conflict areas. The proposed collision avoidance approach is verified by both simulations and experiments. The results show that the system can successfully detect different sizes of fixed-wing intruders, estimate their regions, and assess the risk of collision at least 10 s in advance before the expected collision would happen.

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Section: Airborne Sensing Technologies and Collision Avoidance Strate...mentioning

confidence: 99%

Vision-Based Mid-Air Object Detection and Avoidance Approach for Small Unmanned Aerial Vehicles with Deep Learning and Risk Assessment

Lai,

Lin

2024

Remote Sensing

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Three‐dimensional mapping and immersive human–robot interfacing utilize Kinect‐style depth cameras and virtual reality for agricultural mobile robots

Wang,

Zhang,

Zhou

et al. 2024

Journal of Field Robotics

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Navigation and autonomous operation in farmland or greenhouse environments present significant challenges for agricultural mobile robots on account of unstructured scene conditions and complex task requirements. The immersive interfaces based on human–robot interaction have been extensively developed, which bridge the high‐level decision of human beings and the precise sensing and high motion ability of robots. In this study, we propose a human–robot interaction framework based on three‐dimensional mapping and virtual reality (VR) visualization. On the construction client, dense three‐dimensional point‐cloud maps are created based on the simultaneous localization and mapping real‐time appearance‐based mapping algorithm with a Kinect‐style depth camera. Subsequently, point‐cloud filtering and mesh creation methods are introduced for postprocessing the map models. A data communication network is employed to transmit the optimized models to the VR‐based exploration client. Utilizing VR visualization, the operator can gain an intuitive and comprehensive understanding of the environments to be explored. The three‐dimensional agricultural scenes are mapped into VR models through the system, which can combine the physical worlds with the VR spaces in a better manner. Compared with the video streaming‐based method for three‐dimensional mapping, the map models with colors and textures are entirely displayed in the VR headset, thus providing robust and global human–robot interaction interfaces and enhancing the immersive exploration for human beings to a considerable extent. Experimental results indicate that the three‐dimensional map models exhibit relatively sufficient construction integrity and yield favorable optimization effects. Additionally, according to a user questionnaire survey, immersive VR‐based interfaces can be more effectively utilized for the three‐dimensional mapping of mobile robots. Research evidence and results demonstrate that our proposed system framework offers positive assistance and support for enhancing human–robot interaction and executing specific robotic tasks in unstructured field agricultural environments. Code implementation and related data sets are shared at the link https://github.com/WangDongBUAA/Mapping_Interfacing.

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A low-cost vision system for online reciprocal collision avoidance with UAVs

Estevez,

Nuñez,

Lopez-Guede

et al. 2024

Aerospace Science and Technology

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A comprehensive survey on non‐cooperative collision avoidance for micro aerial vehicles: Sensing and obstacle detection

Cited by 10 publications

References 152 publications

Vision-Based Mid-Air Object Detection and Avoidance Approach for Small Unmanned Aerial Vehicles with Deep Learning and Risk Assessment

Vision-Based Mid-Air Object Detection and Avoidance Approach for Small Unmanned Aerial Vehicles with Deep Learning and Risk Assessment

Three‐dimensional mapping and immersive human–robot interfacing utilize Kinect‐style depth cameras and virtual reality for agricultural mobile robots

A low-cost vision system for online reciprocal collision avoidance with UAVs

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