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基于優(yōu)化人工勢(shì)場(chǎng)法的插秧機(jī)繞障策略研究
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國(guó)家自然科學(xué)基金項(xiàng)目(52172396)


Obstacle Winding Strategy of Rice Transplanter Based on Optimized Artificial Potential Field Method
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    摘要:

    針對(duì)水田中存在的壕溝、田埂,、石塊,、電線桿等障礙物使得插秧機(jī)無(wú)法保證作業(yè)連續(xù)性和插秧直線性等問(wèn)題,設(shè)計(jì)了基于優(yōu)化人工勢(shì)場(chǎng)法的插秧機(jī)繞障路徑規(guī)劃策略,。通過(guò)增加插秧機(jī)實(shí)時(shí)位置與目標(biāo)作業(yè)點(diǎn)的相對(duì)距離作為判斷條件來(lái)動(dòng)態(tài)改變勢(shì)場(chǎng)大小,,同時(shí)設(shè)立了虛擬局部目標(biāo)點(diǎn)來(lái)彌補(bǔ)傳統(tǒng)人工勢(shì)場(chǎng)法目標(biāo)點(diǎn)不可達(dá)和局部最小點(diǎn)的算法缺陷;將插秧機(jī)簡(jiǎn)化為二輪車模型,,建立插秧機(jī)轉(zhuǎn)向系統(tǒng)數(shù)學(xué)模型,,得出插秧機(jī)速度、行駛航向角和前輪轉(zhuǎn)角表達(dá)式,,以橫向偏差與航向偏差作為評(píng)判路徑優(yōu)化效果的因素,。轉(zhuǎn)向控制器以復(fù)合模糊PID算法控制插秧機(jī)的轉(zhuǎn)角,不斷減小理想前輪轉(zhuǎn)角與實(shí)際轉(zhuǎn)角的偏差,,實(shí)現(xiàn)轉(zhuǎn)角最優(yōu)化,;采用超聲波傳感器實(shí)時(shí)檢測(cè)道路障礙物并結(jié)合RTK-GPS實(shí)時(shí)更新位置坐標(biāo),設(shè)計(jì)出插秧機(jī)繞障轉(zhuǎn)向控制策略,。通過(guò)Matlab對(duì)優(yōu)化的人工勢(shì)場(chǎng)法的避障路徑控制策略進(jìn)行仿真,,仿真結(jié)果表明,當(dāng)障礙物不在影響范圍內(nèi),,插秧機(jī)直線追蹤的最大橫向位置偏差為5cm,平均偏差約為2cm,,最大避障橫向偏差小于0.5m,優(yōu)化后的算法具有較好的控制精度,,可避免目標(biāo)點(diǎn)不可達(dá)的問(wèn)題,。基于洋馬VP6E插秧機(jī)作為實(shí)驗(yàn)平臺(tái)進(jìn)行了實(shí)車實(shí)驗(yàn),,實(shí)驗(yàn)結(jié)果表明,,當(dāng)插秧機(jī)以速度0.5、1.0,、1.5m/s行駛時(shí),,左側(cè)繞障的最大橫向偏差均不大于1.2218m,航向偏差最大值為30.1491°,,繞障前后直線追蹤的平均橫向偏差為0.025m,,平均航向偏差為3.12°;右側(cè)繞障的最大橫向偏差均不大于1.2459m,,航向偏差最大值為25.2294°,,繞障前后直線追蹤的平均橫向偏差為0.023m,,平均航向偏差為3.36°,所設(shè)計(jì)的避障方法可滿足插秧機(jī)在農(nóng)藝作業(yè)過(guò)程中的避障要求,,具有很好的可行性與魯棒性,。

    Abstract:

    Aiming at the problems that the obstacles such as ditches, ridges, stones and electric poles in paddy fields make the rice transplanter unable to ensure the continuity of operation and the straightness of rice transplanting, a path planning strategy for rice transplanter around obstacles based on optimized artificial potential field method was designed. The relative distance between the realtime position of the transplanter and the target operation point was added as the judgment condition to dynamically change the size of the potential field. At the same time, a virtual local target point was set up to make up for the algorithm defects of the target point unreachable and local minimum point of the traditional artificial potential field method. The transplanter was simplified into a two wheeled vehicle model, the mathematical model of the steering system of the transplanter was established, and the expressions of the speed, heading angle and front wheel angle of the transplanter were obtained. The lateral deviation and heading deviation were used as the factors to judge the effect of path optimization. The steering controller used the compound fuzzy PID algorithm to control the rotation angle of the transplanter, continuously reduce the deviation between the ideal front wheel rotation angle and the actual rotation angle, and realize the optimization of the rotation angle. Using ultrasonic sensor to detect road obstacles in real time and RTK-GPS to update the position coordinates in real time, the steering control strategy of rice transplanter around obstacles was designed. The obstacle avoidance path control strategy of the optimized artificial potential field method was simulated by Matlab. The results showed that when the obstacles were not within the influence range, the maximum transverse position deviation of the straight-line tracking of the rice transplanter was 5cm, the average deviation was about 2cm, and the maximum obstacle avoidance transverse deviation was less than 0.5m. The optimized algorithm had good control accuracy and can avoid the problem of unreachable target points. Based on Yangma Vp6E rice transplanter as the experimental platform, the real vehicle experiment was carried out. The experimental results showed that when the rice transplanter ran at the speed of 0.5m/s, 1.0m/s and 1.5m/s, the maximum lateral deviation of the left side obstacle was no more than 1.2218m, the maximum heading deviation was 30.1491°, the average lateral deviation of the straight line tracking before and after the obstacle was 0.025m, and the average heading deviation was 3.12°. The maximum lateral deviation of the right side obstacle was not more than 1.2459m, the maximum heading deviation was 25.2294°, the average lateral deviation of straight-line tracking before and after the obstacle was 0.023m, and the average heading deviation was 3.36°. The designed obstacle avoidance method can meet the obstacle avoidance requirements of the transplanter during driving, and had good feasibility and robustness.

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姜龍騰,遲瑞娟,熊澤鑫,馬悅琦,班超,朱曉龍.基于優(yōu)化人工勢(shì)場(chǎng)法的插秧機(jī)繞障策略研究[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2022,53(s1):20-27. JIANG Longteng, CHI Ruijuan, XIONG Zexin, MA Yueqi, BAN Chao, ZHU Xiaolong. Obstacle Winding Strategy of Rice Transplanter Based on Optimized Artificial Potential Field Method[J]. Transactions of the Chinese Society for Agricultural Machinery,2022,53(s1):20-27.

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  • 收稿日期:2022-06-15
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  • 在線發(fā)布日期: 2022-11-10
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