Helicopter–UAVs search and rescue task allocation considering UAVs operating environment and performance

Zhang, Ming; Li, Wei; Wang, Mengmeng; Li, Songrui; Li, Boquan

doi:10.1016/j.cie.2022.107994

Cited by 31 publications

(11 citation statements)

References 51 publications

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“…Search the set for the nearest five feature points of point pw projected onto the line, and then compute the mean and covariance matrix of these feature points. The corresponding point-to-line residual rε (p w ) is calculated as equation (6).…”

Section: Iterative Optimization Of Fused Feature Factorsmentioning

confidence: 99%

“…By utilizing radio waves for environment perception, LiDAR sensors remain unaffected by variations in lighting, enabling precise pose estimation and high-speed sampling across diverse lighting environments. As a result, it is extensively employed in various robotic applications such as autonomous driving [5], warehouse manipulation and search and rescue [6].…”

Section: Introductionmentioning

confidence: 99%

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Hierarchical fusion based high precision SLAM for solid-state lidar

Xu,

Yu,

Zhang

et al. 2024

Meas. Sci. Technol.

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Solid-state LiDARs have become an important perceptual device for simultaneous localization and mapping (SLAM) due to its low-cost and high-reliability compared to mechanical LiDARs. Nevertheless, existing solid-state LiDARs-based SLAM methods face challenges, including drift and mapping inconsistency, when operating in dynamic environments over extended periods and long distances. To this end, this paper proposes a robust, high-precision, real-time LiDAR-inertial SLAM method for solid-state LiDARs. At the front-end, the raw point cloud is segmented to filter dynamic points in preprocessing process. Subsequently, features are extracted using a combination of Principal Component Analysis (PCA) and Mean Clustering to reduce redundant points and improve data processing efficiency. At the back-end, a hierarchical fusion method is proposed to improve the accuracy of the system by fusing the feature information to iteratively optimize the LiDAR frames, and then adaptively selecting the LiDAR keyframes to be fused with the IMU. The proposed method is extensively evaluated using a Livox Avia solid-state LiDAR collecting datasets on two different platforms. In experiments, the end-to-end error is reduced by 35% and the single-frame operational efficiency is improved by 12% compared to LiLi-OM.

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Section: Iterative Optimization Of Fused Feature Factorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hierarchical fusion based high precision SLAM for solid-state lidar

Xu,

Yu,

Zhang

et al. 2024

Meas. Sci. Technol.

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“…The International Civil Aviation Organization (ICAO) has established guidelines for search and rescue operations following disasters [91]. UAVs should be used to replace humans for field research duties in challenging and hazardous field conditions [92]. Tethered UAVs were utilized to provide lighting in the dark during the rescue operation for China Eastern Airlines' MU5735 accident, and a UAV mobile base station was made available for air-ground communications [93,94].…”

Section: Seek and Rescuementioning

confidence: 99%

Design Configuration and Technical Application of Rotary-Wing Unmanned Aerial Vehicles

Zhao¹,

Li²

2022

MITS

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Due to their advantages in hovering, takeoff and landing adaptability, maneuverability, and other factors, rotary-wing unmanned aerial vehicles (UAVs) are widely applied across many different fields. The UAVs' design and configuration can be quite flexible to fit diverse operation conditions. The major goal of innovations in rotary-wing UAVs is to lower operating risk and expense by optimizing payload and structure layout. This study examines three aspects of rotary-wing UAV design and evolution: the number and arrangement of rotors, hybrid-wing-based UAVs, and configuration and loading structures. The most current advancements of UAV applications in crucial industries, including agriculture, fire rescue, inspection and monitoring, and aerial logistics, are then thoroughly examined. Finally, the authors discussed the prospective uses for rotary-wing UAV design in the future.

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“…Unmanned aerial vehicles (UAVs) have received extensive attention from the engineering community due to their promising potential in military and civilian applications, such as disaster rescue [1,2], intelligent surveillance [3,4], smart agriculture [5][6][7][8], aerial photography [9,10], mapping [11], industry inspection [12,13] logistics [14][15][16], forest fire-fighting [16], and crop disease monitoring [17][18][19], etc.. Numerous types of UAVs have been fabricated and developed as research platforms, among which the quadcopters (also called quadrotors) are the most popular type because of their considerable merits including autonomous flight, easy construction, simple maintenance, low cost, onboard vision, vertical take-off and landing [20], hovering ability, and manoeuvrability.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Neuro-Fuzzy Inference System Based on Sliding Mode Control for Quadcopter Trajectory Tracking with the Presence of External Disturbance

Darwito¹,

Indayu²

2023

JISC

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Objective of this study is to develop a novel, effective, and robust Sliding Mode Control (SMC) method for quadcopters (also called quadrotors) based on Adaptive Neuro-Fuzzy Inference System (ANFIS) for the purposes of enhancing trajectory tracking performance and realizing safe and reliable flight. In the paper, the ANFIS was combined with SMC technology to propose a scheme of adaptive robust controller, which is composed of three sub-controllers, x position controller, y position controller, and z position (altitude) controller. The proposed method can realize position tracking control of quadcopters in the presence of external disturbances. With the help of ANFIS, an adjustable gain rather than a fixed gain was established for the SMC controller, the optimal output could be attained based on a set of rules, and the position control gain was updated by ANFIS, enabling the SMC to adapt to environmental changes. Through modelling, simulation and comparison, experimental data verified that the proposed ANFIS-SMC controller outperformed conventional SMC controller in terms of convergence speed, robustness, accuracy, and stability with a maximum mean error of 0.125 meters in trajectory tracking. Research findings of this paper could contribute to the development of robust and responsive control strategies for Unmanned aerial vehicles (UAVs) trajectory tracking by providing valuable insights into the design of more effective and efficient control systems for UAVs, particularly in the context of dynamic environmental conditions.

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Helicopter–UAVs search and rescue task allocation considering UAVs operating environment and performance

Cited by 31 publications

References 51 publications

Hierarchical fusion based high precision SLAM for solid-state lidar

Hierarchical fusion based high precision SLAM for solid-state lidar

Design Configuration and Technical Application of Rotary-Wing Unmanned Aerial Vehicles

Adaptive Neuro-Fuzzy Inference System Based on Sliding Mode Control for Quadcopter Trajectory Tracking with the Presence of External Disturbance

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