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基于改進A*與DWA算法融合的溫室機器人路徑規(guī)劃
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國家自然科學基金項目(31871527)


Path Planning of Greenhouse Robot Based on Fusion of Improved A* Algorithm and Dynamic Window Approach
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    摘要:

    根據(jù)溫室環(huán)境下移動機器人作業(yè)的實時路徑規(guī)劃要求,提出一種基于改進A*算法與動態(tài)窗口法相結(jié)合的溫室機器人路徑規(guī)劃算法。針對傳統(tǒng)A*算法搜索算法拐點過多的問題,對關(guān)鍵點選取策略進行改進,融合動態(tài)窗口法,構(gòu)建全局最優(yōu)路徑評價函數(shù),采用超聲傳感器進行局部避障,實現(xiàn)實時最優(yōu)的路徑規(guī)劃。仿真實驗結(jié)果證明,與傳統(tǒng)A*、Dijkstra、RRT算法相比,基于改進A*算法的路徑更為平滑和高效。真實環(huán)境下實驗表明,移動機器人能夠?qū)崿F(xiàn)自主導航,跟蹤誤差保持在0.22m以內(nèi)、定位誤差不大于0.28m,能夠滿足實際需求。

    Abstract:

    Path planning is the premise of greenhouse robot operation, and an optimal continuous barrier free path is planned with great significance. An algorithm based on the combination of improved A* algorithm and dynamic window approach was proposed to solve real-time path planning of mobile robot in greenhouse. The core was based on the search algorithm of traditional A* algorithm. Aiming at the problem of too many inflexion points, the key point selection strategy was improved. The dynamic window method was integrated to construct a global optimal path evaluation function. Local obstacle avoidance was achieved through ultrasonic sensors to achieve real-time optimal path planning. The simulation results showed that compared with the traditional A*, Dijkstra, RRT algorithms, the improved A* algorithm had a smoother path and higher efficiency, which was conducive to the motion control of the robot in the greenhouse, which showed the effectiveness of the algorithm. Considering the size of the robot, the grid map of the real environment was expanded to ensure the safety of the path. The experimental results showed that the fusion algorithm can satisfy the smoothness of path and effectively avoid obstacles. The mobile robot can achieve autonomous navigation, and the tracking error was kept within 0.22m, and the positioning error was no more than 0.28m, which met the actual needs. The research result had an important reference value for the application of greenhouse mobile robot navigation.

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勞彩蓮,李鵬,馮宇.基于改進A*與DWA算法融合的溫室機器人路徑規(guī)劃[J].農(nóng)業(yè)機械學報,2021,52(1):14-22. LAO Cailian, LI Peng, FENG Yu. Path Planning of Greenhouse Robot Based on Fusion of Improved A* Algorithm and Dynamic Window Approach[J]. Transactions of the Chinese Society for Agricultural Machinery,2021,52(1):14-22.

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  • 收稿日期:2020-03-13
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  • 在線發(fā)布日期: 2021-01-10
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