Robust and Efficient Trajectory Replanning Based on Guiding Path for Quadrotor Fast Autonomous Flight

Zhao, Yinghao; Li, Yan; Chen, Yu; Dai, Junhu; Liu, Yuxuan

doi:10.3390/rs13050972

Cited by 21 publications

(15 citation statements)

References 54 publications

(90 reference statements)

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“…The target point is set to (100 × 100) 𝑚 2 . In the 3D field, we set the flight planning space's size is (100 × 100 × 400) 𝑚 3 , just like the model of the Figure 2. The start point is set to (0 m, 0 m, 0 m).…”

Section: Application Of New Algorithm In 3d Path Planningmentioning

confidence: 99%

“…In recent years, a series of path planning algorithms have been proposed. In order to improve the stability and efficiency of path planning methods in complex environments, the literature [3] presented a RETRBG algorithm, a robust and efficient trajectory replanning method based on the guiding path. The literature [4] introduced CPP method based on a Region Optimal Decomposition (ROD), which achieved good results when applied to the path planning of UAV in a port environment.…”

Section: Introductionmentioning

confidence: 99%

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A parallel particle swarm optimization and enhanced sparrow search algorithm for unmanned aerial vehicle path planning

Wang

2022

Preprint

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The path planning problem is that Unmanned aerial vehicle (UAV) needs to plan a feasible path from the starting point to the end point in a specific environment. But it cannot get satisfactory results using ordinary algorithms, to solve this problem, a hybrid algorithm named as PESSA is proposed, where particle swarm optimization (PSO) and an enhanced sparrow search algorithm (ESSA) work in parallel. In the ESSA, the random jump of the producer’s position is strengthened to guarantee the global search ability, each scrounger keeps learning from the optimal experience of the producers, and for the sparrow with the optimal position, when it perceives the danger, the difference between the best individual and the worst individual will be imposed to speed up the search process. And then, the elite reverse search strategy was added to increase the diversity of the population. In this paper, the performance of PESSA is verified by 10 basic functions, the experimental results illustrate that PESSA is better compared with other twelve algorithms. Finally, the proposed PESSA is applied in 4 different scenarios including two groups of 2D environments and two groups of 3D environments. The results show that the PESSA algorithm can acquire more feasible and effective route than compared algorithms.

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Section: Application Of New Algorithm In 3d Path Planningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A parallel particle swarm optimization and enhanced sparrow search algorithm for unmanned aerial vehicle path planning

Wang

2022

Preprint

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“…d θ is used to help the method to find a smoother path. We refer the reader to [10], [29], [31] for more details about kinodynamic path searching and for the path optimization.…”

Section: Guided Kinodynamic Path Searchingmentioning

confidence: 99%

FAEP: Fast Autonomous Exploration Planner for UAV Equipped with Limited FOV Sensor

Zhao¹,

Li²,

Chen³

et al. 2022

Preprint

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Autonomous exploration is one of the important parts to achieve the autonomous operation of Unmanned Aerial Vehicles (UAVs). To improve the efficiency of the exploration process, a fast and autonomous exploration planner (FAEP) is proposed in this paper. We firstly design a novel frontiers exploration sequence generation method to obtain a more reasonable exploration path, which considers not only the flight-level but frontier-level factors into TSP. According to the exploration sequence and the distribution of frontiers, a two-stage heading planning strategy is proposed to cover more frontiers by heading change during an exploration journey. To improve the stability of path searching, a guided kinodynamic path searching based on a guiding path is devised. In addition, a dynamic start point selection method for replanning is also adopted to increase the fluency of flight. We present sufficient benchmark and real-world experiments. Experimental results show the superiority of the proposed exploration planner compared with typical and state-of-the-art methods.

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“…Simultaneous localization and mapping (SLAM) [1] is a crucial technology to achieve the autonomous perception of intelligent robots for applications such as augmented reality, indoor navigation, and autonomous vehicles [2][3][4]. It enables the robot's positional estimation and scene construction in unknown environments by analyzing its onboard sensors.…”

Section: Introductionmentioning

confidence: 99%

DGS-SLAM: A Fast and Robust RGBD SLAM in Dynamic Environments Combined by Geometric and Semantic Information

Long

et al. 2022

Remote Sensing

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Visual Simultaneous Localization and Mapping (VSLAM) is a prerequisite for robots to accomplish fully autonomous movement and exploration in unknown environments. At present, many impressive VSLAM systems have emerged, but most of them rely on the static world assumption, which limits their application in real dynamic scenarios. To improve the robustness and efficiency of the system in dynamic environments, this paper proposes a dynamic RGBD SLAM based on a combination of geometric and semantic information (DGS-SLAM). First, a dynamic object detection module based on the multinomial residual model is proposed, which executes the motion segmentation of the scene by combining the motion residual information of adjacent frames and the potential motion information of the semantic segmentation module. Second, a camera pose tracking strategy using feature point classification results is designed to achieve robust system tracking. Finally, according to the results of dynamic segmentation and camera tracking, a semantic segmentation module based on a semantic frame selection strategy is designed for extracting potential moving targets in the scene. Extensive evaluation in public TUM and Bonn datasets demonstrates that DGS-SLAM has higher robustness and speed than state-of-the-art dynamic RGB-D SLAM systems in dynamic scenes.

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Robust and Efficient Trajectory Replanning Based on Guiding Path for Quadrotor Fast Autonomous Flight

Cited by 21 publications

References 54 publications

A parallel particle swarm optimization and enhanced sparrow search algorithm for unmanned aerial vehicle path planning

A parallel particle swarm optimization and enhanced sparrow search algorithm for unmanned aerial vehicle path planning

FAEP: Fast Autonomous Exploration Planner for UAV Equipped with Limited FOV Sensor

DGS-SLAM: A Fast and Robust RGBD SLAM in Dynamic Environments Combined by Geometric and Semantic Information

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