Quad-RRT: A real-time GPU-based global path planner in large-scale real environments

Hidalgo-Paniagua, Alejandro; Bandera, Juan Pedro; Ruiz-de-Quintanilla, Manuel; Bandera, Antonio

doi:10.1016/j.eswa.2018.01.035

Cited by 25 publications

(9 citation statements)

References 10 publications

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“…The probabilistic path planning algorithm is also a commonly-used method, including Probabilistic Roadmaps (Kavraki, Svestka, Latombe, & Overmars, 1994) and RRT (Jaillet, Cortes, & Simeon, 2008;Hidalgo-Paniagua, Bandera, Ruiz-de-Quintanilla, & Bandera, 2018). The basic idea of probabilistic path planning is to randomly select non-collision candidate points in a space, then connect them to generate a path.…”

Section: Literature Reviewmentioning

confidence: 99%

A novel path planning approach for smart cargo ships based on anisotropic fast marching

Yan

Wang

et al. 2020

Expert Systems with Applications

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Section: Literature Reviewmentioning

confidence: 99%

A novel path planning approach for smart cargo ships based on anisotropic fast marching

Yan

Wang

et al. 2020

Expert Systems with Applications

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“…As RRT path planning involves random sampling, its search speed is fast because it does not need to deal with the state space in the system. Moreover, it is not limited to solving high-dimensional constrained space problems, and is therefore often used in the construction of automatic systems path planning [42]. In the field of automatic systems, the RRT algorithm has become a conventional technology to solve the single query motion-planning problem.…”

Section: Path Planning Algorithmsmentioning

confidence: 99%

An Intelligent Waste Removal System for Smarter Communities

Zhang

Wan

et al. 2020

Sustainability

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With the continuous progress of urbanization, the discharge of municipal solid waste has profoundly affected human production/living and social ecological health, and waste disposal has become one of the key issues all over the world. In the context of intelligent technology, this paper innovates the way of waste disposal according to the development direction of a smart city and the requirement of sustainable development strategy. An intelligent urban waste removal system is developed using a ROS (Route Operation System) robot operating system and RRT (Rapid Exploration of Random Trees) path planning algorithm. With a background of data management, the entire process of intelligent automatic waste removal is triggered by automatic communication from individual waste bins to a waste collection vehicle (WCV) where the bin needs to be emptied, and the automatic collection and transportation by the WCV in response. In combination with the IoT (Internet of Things), the system provides scientific data support for the intelligent layout of communities and even urban waste bins to greatly enhance the development of intelligence communities and smart cities.

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“…In order to improve the convergence rate, variant improvements on RRT and RRT * algorithms have been extensively explored [13][14][15]. In [13], the D * Lite Rapidlyexploring Random Tree star (DL-RRT * ) algorithm has been proposed for path replanning in dynamic radioactive environments, which uses the expansion strength of grid search strategy from D * Lite to quickly find a high-quality initial path to accelerate the convergence rate in RRT * .…”

Section: Introductionmentioning

confidence: 99%

“…In the work [14], the authors proposed the Bidirectional RRT (B-RRT) to build two trees rooted at the start and goal configurations, respectively. Reference [15] has extended B-RRT to exploit the possibilities of dynamically dividing up the whole map into four submaps and growing the random tree in every submap using Graphic Processing Unit (GPU) threads. In the other words, Quad-RRT [15] computed four random trees instead of two trees built by bidirectional approaches.…”

Section: Introductionmentioning

confidence: 99%

Biased Sampling Potentially Guided Intelligent Bidirectional RRT^∗ Algorithm for UAV Path Planning in 3D Environment

Zhen

et al. 2019

Mathematical Problems in Engineering

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During the last decade, Rapidly-exploring Random Tree star (RRT∗) algorithm based on sampling has been widely used in the field of unmanned aerial vehicle (UAV) path planning for its probabilistically complete and asymptotically optimal characteristics. However, the convergence rate of RRT∗ as well as B-RRT∗ and IB-RRT∗ is slow for these algorithms perform pure exploration. To overcome the weaknesses above, Biased Sampling Potentially Guided Intelligent Bidirectional RRT∗ (BPIB-RRT∗) algorithm is proposed in this paper, which combines the bidirectional artificial potential field method with the idea of bidirectional biased sampling. The proposed algorithm flexibly adjusts the sampling space, greatly reduces the invalid spatial sampling, and improves the convergence rate. Moreover, the deeply theoretical analysis of the proposed BPIB-RRT∗ algorithm is given regarding its probabilistic completeness, asymptotic optimality, and computational complexity. Finally, compared to the latest UAV path planning algorithms, simulation comparisons are demonstrated to show the superiority of our proposed BPIB-RRT∗ algorithm.

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Quad-RRT: A real-time GPU-based global path planner in large-scale real environments

Cited by 25 publications

References 10 publications

A novel path planning approach for smart cargo ships based on anisotropic fast marching

A novel path planning approach for smart cargo ships based on anisotropic fast marching

An Intelligent Waste Removal System for Smarter Communities

Biased Sampling Potentially Guided Intelligent Bidirectional RRT^∗ Algorithm for UAV Path Planning in 3D Environment

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Quad-RRT: A real-time GPU-based global path planner in large-scale real environments

Cited by 25 publications

References 10 publications

A novel path planning approach for smart cargo ships based on anisotropic fast marching

A novel path planning approach for smart cargo ships based on anisotropic fast marching

An Intelligent Waste Removal System for Smarter Communities

Biased Sampling Potentially Guided Intelligent Bidirectional RRT∗ Algorithm for UAV Path Planning in 3D Environment

Contact Info

Product

Resources

About

Biased Sampling Potentially Guided Intelligent Bidirectional RRT^∗ Algorithm for UAV Path Planning in 3D Environment