Three dimensional D* algorithm for incremental path planning in uncooperative environment

Majumder, Shibarchi; Prasad, Mani Shankar

doi:10.1109/spin.2016.7566733

Cited by 16 publications

(6 citation statements)

References 5 publications

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“…In the FC-RRT* algorithm, we use the flight cost function and flight constraints to guide the selection of the optimal parent node (Alg. 1, lines [9][10][11][12]. Since this approach considers the threat strength, path length, and flight constraints simultaneously, the planned path is an optimal path that satisfies the path safety and constraints.…”

Section: Fc-rrt* Algorithmmentioning

confidence: 99%

“…Optimal path selection needs to be determined based on the flight performance constraints, the specific mission requirements, and the flight environment constraints [5,6]. Scholars have conducted a lot of research on the UAV path planning problem and proposed a series of algorithms, such as graph-based optimization methods, including the visibility graph (VG) algorithm [7] and Voronoi diagrams [8]; the searching-based methods, including the Dijkstra [9] algorithm, A* algorithm [10] and D* algorithm [11]; the sampling-based methods, such as PRM algorithm [12] and RRT algorithm [13]; the nature-inspired methods, such as genetic algorithm (GA) [14], ant colony optimization (ACO) [15], artificial potential field algorithm [16], particle swarm optimization (PSO) [17] and fluid-based algorithm [18]; and other methods, such as control theory-based methods [19].…”

Section: Introductionmentioning

confidence: 99%

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FC-RRT*: An Improved Path Planning Algorithm for UAV in 3D Complex Environment

Guo

Liu

et al. 2022

IJGI

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In complex environments, path planning is the key for unmanned aerial vehicles (UAVs) to perform military missions autonomously. This paper proposes a novel algorithm called flight cost-based Rapidly-exploring Random Tree star (FC-RRT*) extending the standard Rapidly-exploring Random Tree star (RRT*) to deal with the safety requirements and flight constraints of UAVs in a complex 3D environment. First, a flight cost function that includes threat strength and path length was designed to comprehensively evaluate the connection between two path nodes. Second, in order to solve the UAV path planning problem from the front-end, the flight cost function and flight constraints were used to inspire the expansion of new nodes. Third, the designed cost function was used to guide the update of the parent node to allow the algorithm to consider both the threat and the length of the path when generating the path. The simulation and comparison results show that FC-RRT* effectively overcomes the shortcomings of standard RRT*. FC-RRT* is able to plan an optimal path that significantly improves path safety as well as maintains has the shortest distance while satisfying flight constraints in the complex environment. This paper has application value in UAV 3D global path planning.

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Section: Fc-rrt* Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

FC-RRT*: An Improved Path Planning Algorithm for UAV in 3D Complex Environment

Guo

Liu

et al. 2022

IJGI

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“…The authors state that VI persons were able reach their chosen destination. The post-survey of results showed that the efficiency of such a system can reach 80% by implementing CAMShift [40] and D* [41] algorithms.…”

Section: Camera-based Systemsmentioning

confidence: 99%

Indoor Navigation Systems for Visually Impaired Persons: Mapping the Features of Existing Technologies to User Needs

Plikynas

Žvironas

Budrionis

et al. 2020

Sensors

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Currently, several outdoor navigation and orientation electronic traveling aid (ETA) solutions for visually impaired (VI) people are commercially available or in active development. This paper’s survey of blind experts has shown that after outdoor navigation, the second most important ETA feature for VI persons is indoor navigation and orientation (in public institutions, supermarkets, office buildings, homes, etc.). VI persons need ETA for orientation and navigation in unfamiliar indoor environments with embedded features for the detection and recognition of obstacles (not only on the ground but also at head level) and desired destinations such as rooms, staircases, and elevators. The development of such indoor navigation systems, which do not have Global Positioning System (GPS) locational references, is challenging and requires an overview and evaluation of existing systems with different navigation technologies. This paper presents an evaluation and comparison of state-of-the-art indoor navigation solutions, and the research implications provide a summary of the critical observations, some insights, and directions for further developments. The paper maps VI needs in relation to research and development (R&D) trends using the evaluation criteria deemed most important by blind experts.

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“…Other studies have focused on more generalized 3D environment [23]. In [24], the authors proposed a modification of D* algorithm which incrementally finds path during the flight. The selected path effectively allows drones to avoid obstacles while navigating.…”

Section: Related Workmentioning

confidence: 99%

Low-Altitude Navigation for Multi-Rotor Drones in Urban Areas

et al. 2019

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Multi-rotor drones have witnessed a drastic usage increase in several smart city applications due to their 3D mobility, flexibility, and low cost. Collectively, they can be used to accomplish different short-and long-term missions that require low-altitude motion in urban areas. Therefore, it is important to efficiently manage the operation of the fleet to leverage its use and maximize its application performances. In this paper, we propose to investigate the path routing problem for the multiple drones in urban areas, where obstacles with different heights exist. The objective is to find the best trajectories in this 3D environment while ensuring collision-free navigation. The collision is prevented by three possible alternatives: forcing the drone to statically hover, so its peer can pass first, making it fly at a different altitude, or completely changing its path. Multiple charging stations are made available to allow the drones to recharge their batteries when needed. A mixed integer linear program is first developed to model the problem and achieve optimal navigation of the fleet. Afterward, two heuristic algorithms with different conceptual constructions are designed to solve the trajectory planning problem with faster convergence speed. The selected simulation results illustrate the performance of our framework in realistic 3D maps and show that the designed heuristic approaches provide close performances to the optimal ones. INDEX TERMS Unmanned aerial vehicles (UAVs), fleet path planning, energy management, collision avoidance, smart city.

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Three dimensional D* algorithm for incremental path planning in uncooperative environment

Cited by 16 publications

References 5 publications

FC-RRT*: An Improved Path Planning Algorithm for UAV in 3D Complex Environment

FC-RRT*: An Improved Path Planning Algorithm for UAV in 3D Complex Environment

Indoor Navigation Systems for Visually Impaired Persons: Mapping the Features of Existing Technologies to User Needs

Low-Altitude Navigation for Multi-Rotor Drones in Urban Areas

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