Robot Path Planning Based on Improved A* Algorithm

Peng, Jiansheng; Huang, Yiyong; Luo, Guang–Nan

doi:10.1515/cait-2015-0036

Cited by 25 publications

(14 citation statements)

References 2 publications

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“…In the next work, they will ensure these performances in real robotic application. Peng et al [19] developed a new solution to store data in OPEN and CLOSED tables (OPEN_TABLE, CLOSED_TABLE) in order to shorten the operation time of A* algorithm. The operation efficiency was tried to be improved by using a new storing approach and more than 40 % gain was obtained in this study.…”

Section: Literature Reviewmentioning

confidence: 99%

A Hybrid Routing Approach Using Two Searching Layers

Koca

Yetkin

2021

Electrical, Control and Communication Engineering

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This paper considers SUB_GOALs by using basic A* algorithm and Subgoal Graphs in a hybrid approach to execute optimal route. SUB_GOALs identified with pre-searching from basic A* at break points and Subgoal Graphs at corners of obstacles are added to SUB_TABLE to expedite the final searching in the hybrid approach. Map to work on is divided to subregions with decision-making process by using line-of-sight to avoid redundant searching. In the final searching layer, all feasible SUB_GOALs gained from decision-making process in the same subregion are connected to find final solutions of routes. Solutions achieved in the divided subregions are evaluated and combined to discover the final optimal route. The proposed hybrid approach is applied to three different scenarios in various dimensions of maps. In these three scenarios, the shortest route without hitting obstacles is calculated as 46.67, 57.76 and 124.7 units, respectively, and compared with other search algorithms. Simulation results of route planning are demonstrated to exhibit the effectiveness of the proposed hybrid approach.

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Section: Literature Reviewmentioning

confidence: 99%

A Hybrid Routing Approach Using Two Searching Layers

Koca

Yetkin

2021

Electrical, Control and Communication Engineering

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“…On the one hand, a lightweight implementation of the A algorithm [20] acts as the Local Path Planner. Similar to [21], four directions of movement are allowed in the grid. The cells containing obstacles are not connected with the neighboring cells.…”

Section: B Path Planningmentioning

confidence: 99%

A Switching Offloading Mechanism for Path Planning and Localization in Robotic Applications

Spatharakis

Avgeris

Αθανασόπουλος

et al. 2020

2020 International Conferences on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE

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Industry 4.0 applications rely on mobile robotic agents that execute many complex tasks that have strict safety and time requirements. Under this setting, the Edge Computing service delivery model allows the robotic agents to offload their computationally intensive tasks to powerful computing infrastructure in their vicinity. In this study, we propose a novel switching offloading mechanism for such robotic applications. In particular, we design opportunistic offloading strategies for the path planning and localization services of mobile robots. The offloading decision is based on the uncertainty of the robot's pose, the resource availability at the Edge of the network and the difficulty of the path planning. Our switching offloading framework is implemented and evaluated using a robot in a real Edge Computing testbed, where the trade-off between execution time and the successful completion of the robot trajectory is highlighted.

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“…A* algorithm was developed by Hart, Nilsson, and Raphael in 1968 [4], and it was improved to use in many applications, such as, robot path planning in 2D/3D space [40][41][42], pipe design in aeroengine [43] and electromechanical products [44]. It is not simply depth-first or breadth-first search, but optimal-first search.…”

Section: B Improved A* Algorithm For Single Pipe Routing (A*-router)mentioning

confidence: 99%

Ship Pipe Route Design Using Improved A* Algorithm and Genetic Algorithm

Dong

Bian

2020

IEEE Access

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The goal of ship pipe route design (SPRD) is to seek the near-optimal paths that meet various constraints and objectives. Due to the complex construction of routing space, diverse piping constraints, and the large number of pipes, SPRD is one of the most difficult and time-consuming tasks even to a skilled pipe designer. This paper proposes automatic approaches for solving SPRD with A* algorithm and genetic algorithm (GA). Firstly, by simplifying the equipment and decomposing the routing space into grids, the mathematical model of SPRD is created. Then, the improved A* algorithm (A*-Router) for single pipe routing is introduced. The evaluation function, auxiliary tables and algorithm framework of A*-Router are presented. To obtain high-quality and diverse layouts, the improved GA (A*-GA-Router) is formulated by A*-Router and the connection-points strategy. Several new genetic operators of A*-GA-Router are designed to improve the routing performance. For multiple pipes routing, the novel algorithm (Multi-Pipes-Router) which calls A*-GA-Router internally is put forward. It arranges pipes according to the specified routing sequence and can produce parallel layout under the function of GA optimization and connectionpoints strategy. To cope with branch-pipe routing widely existing in engineering, a new pipe router (Branch-Pipe-Router) is put forward using a modified Steiner Tree framework in combination with the proposed single pipe routing algorithms. Compared with the traditional methods based on coevolution, it is more versatile and can effectively balance the layout quality and time efficiency. Finally, the feasibility and effectiveness of the proposed algorithms are demonstrated by the experiments on the designed and actual cases. INDEX TERMS A* algorithm, genetic algorithm (GA), single pipe routing, multiple pipes routing, branch pipe routing, ship pipe route design (SPRD)

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Robot Path Planning Based on Improved A* Algorithm

Cited by 25 publications

References 2 publications

A Hybrid Routing Approach Using Two Searching Layers

A Hybrid Routing Approach Using Two Searching Layers

A Switching Offloading Mechanism for Path Planning and Localization in Robotic Applications

Ship Pipe Route Design Using Improved A* Algorithm and Genetic Algorithm

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