2019
DOI: 10.1007/978-981-13-9155-2_17
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Implementation of Dubin Curves-Based RRT* Using an Aerial Image for the Determination of Obstacles and Path Planning to Avoid Them During Displacement of the Mobile Robot

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Cited by 4 publications
(3 citation statements)
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“…But existing approaches for the Dubins case can be carried over to the generalized case without much difficulty in view of the similarity between Dubins curve and its high order generalization. For example, many literatures have combined RRT (rapidly-exploring random tree) and Dubins curve to solve the path planning problem of mobile robot in the presence of obstacles, for example, previous studies [26,27]. In this algorithm, the structure of the tree is determined by the RRT* algorithm, whereas each branch of the tree is (part of) a Dubins curve.…”
Section: Simulation Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…But existing approaches for the Dubins case can be carried over to the generalized case without much difficulty in view of the similarity between Dubins curve and its high order generalization. For example, many literatures have combined RRT (rapidly-exploring random tree) and Dubins curve to solve the path planning problem of mobile robot in the presence of obstacles, for example, previous studies [26,27]. In this algorithm, the structure of the tree is determined by the RRT* algorithm, whereas each branch of the tree is (part of) a Dubins curve.…”
Section: Simulation Resultsmentioning
confidence: 99%
“…Next, we make the problem harder by removing some symmetries from Equation (26), that is, we are going to solve the set of AEs…”
Section: The Algebraic Equations Arose In the Mppmentioning
confidence: 99%
“…In a recent study for unknown environments, an aerial-ground collaborative approach was considered (Zoto et al, 2020). For a similar research problem, navigation of unmanned vehicles using a drone to identify obstacles and execute a global path planner based on rapidly evolving random trees (RRT) using dubin curves was studied (Daniel Tenezaca et al, 2020). A recent research study further proposed a path planning algorithm for partially observed environments based on Task And Motion Planning (TAMP) by using Rapidly exploring Random Graphs (RRGs) and belief space graph methods (Phiquepal et al, 2022).…”
Section: Literature Review About Autonomous Navigation In Forestrymentioning
confidence: 99%