Integrated Planning and Control for Quadrotor Navigation in Presence of Suddenly Appearing Objects and Disturbances

Liu, Wenyi; Ren, Yunfan; Zhang, Fu

doi:10.1109/lra.2023.3311358

Cited by 4 publications

(2 citation statements)

References 24 publications

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“…During the last few years, several open-sourced solutions for inside forest flying have been proposed in the literature. Most of the solutions use either Lidar (Liu et al, 2022;Ren et al, 2022;Liu et al, 2024;Ahmad et al, 2022) or camera (Zhou et al, 2022;Campos-Macías et al, 2021) to create a 3D grid map for collisionfree path trajectory planning and track the position of the drone in local coordinate system. Some of these methods support also autonomous navigation for swarms of drones (Zhou et al, 2022;Ahmad et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Autonomous robotic drone system for mapping forest interiors

Karjalainen,

Koivumäki,

Hakala

et al. 2024

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. During the last decade, the use of drones in forest monitoring and remote sensing has become highly popular. While most of the monitoring tasks take place in high altitudes and open air, in the last few years drones have also gained interest in under-canopy data collection. However, flying under the forest canopy is a complex task since the drone can not use Global Navigation Satellite Systems (GNSS) for positioning and it has to continually avoid obstacles, such as trees, branches, and rocks, on its path. For that reason, drone-based data collection under the forest canopy is still mainly based on manual control by human pilots. Autonomous flying in GNSS-denied obstacle-rich environment has been an actively researched topic in the field of robotics during the last years and various open-sourced methods have been published in the literature. However, most of the research is done purely from the point-of-view of robotics and only a few studies have been published in the boundary of forest sciences and robotics aiming to take steps towards autonomous forest data collection. In this study, a prototype of an autonomous under-canopy drone is developed and implemented utilizing state-of-the-art open-source methods. The prototype is utilizing the EGO-Planner-v2 trajectory planner for autonomous obstacle avoidance and VINS-Fusion for Visual-inertial-odometry based GNSS-free pose estimation. The flying performance of the prototype is evaluated by performing multiple test flights with real hardware in two different boreal forest test plots with medium and difficult densities. Furthermore, the first results of the forest data collecting performance are obtained by post-processing the data collected with a low-cost stereo camera during one test flight to a 3D point cloud and by performing diameter breast at height (DBH) estimation. In the medium-density forest, all seven test flights were successful, but in the difficult test forest, one of eight test flights failed. The RMSE of the DBH estimation was 3.86 cm (12.98 %).

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Section: Introductionmentioning

confidence: 99%

Autonomous robotic drone system for mapping forest interiors

Karjalainen,

Koivumäki,

Hakala

et al. 2024

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…However, they did not compare their work with less computationally demanding [76] or more accurate and robust [78]. The same group proposed [82], where a linear MPC generates control actions within the safety constraints in 2 to 3.5 s. They have shown that MPC computation at 100 Hz improves the quadrotor's response speed to dynamic obstacles and disturbance rejection ability to external disturbances.…”

mentioning

confidence: 99%

Historical and Current Landscapes of Autonomous Quadrotor Control: An Early-Career Researchers’ Guide

Asignacion,

Satoshi

2024

Drones

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The rising demand for autonomous quadrotor flights across diverse applications has led to the introduction of novel control strategies, resulting in several comparative analyses and comprehensive reviews. However, existing reviews lack a comparative analysis of experimental results from published papers, resulting in verbosity. Additionally, publications featuring comparative studies often demonstrate biased comparisons by either selecting suboptimal methodologies or fine-tuning their own methods to gain an advantageous position. This review analyzes the experimental results of leading publications to identify current trends and gaps in quadrotor tracking control research. Furthermore, the analysis, accomplished through historical insights, data-driven analyses, and performance-based comparisons of published studies, distinguishes itself by objectively identifying leading controllers that have achieved outstanding performance and actual deployment across diverse applications. Crafted with the aim of assisting early-career researchers and students in gaining a comprehensive understanding, the review’s ultimate goal is to empower them to make meaningful contributions toward advancing quadrotor control technology. Lastly, this study identifies three gaps in result presentation, impeding effective comparison and decelerating progress. Currently, advanced control methodologies empower quadrotors to achieve a remarkable flight precision of 1 cm and attain flight speeds of up to 30 m/s.

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Design of Robust H_∞ Guaranteed Cost Controller of Quadrotor UAV for Set-Point Tracking

Lee,

Hyun,

Kim

et al. 2024

IEEE Access

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Integrated Planning and Control for Quadrotor Navigation in Presence of Suddenly Appearing Objects and Disturbances

Cited by 4 publications

References 24 publications

Autonomous robotic drone system for mapping forest interiors

Autonomous robotic drone system for mapping forest interiors

Historical and Current Landscapes of Autonomous Quadrotor Control: An Early-Career Researchers’ Guide

Design of Robust H_∞ Guaranteed Cost Controller of Quadrotor UAV for Set-Point Tracking

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Integrated Planning and Control for Quadrotor Navigation in Presence of Suddenly Appearing Objects and Disturbances

Cited by 4 publications

References 24 publications

Autonomous robotic drone system for mapping forest interiors

Autonomous robotic drone system for mapping forest interiors

Historical and Current Landscapes of Autonomous Quadrotor Control: An Early-Career Researchers’ Guide

Design of Robust H∞ Guaranteed Cost Controller of Quadrotor UAV for Set-Point Tracking

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Product

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Design of Robust H_∞ Guaranteed Cost Controller of Quadrotor UAV for Set-Point Tracking