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Harvesting sequence planning of a harvesting robot based on the principle of minimum energy consumption

机译:基于最小能耗原理的收割机器人收割顺序计划

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According to the operational requirements of citrus harvesting robot, a new harvesting sequence planning method and its intelligent optimization algorithm are proposed based on the existing harvesting sequence planning methods, which realized dynamic planning for inverse kinematics solution selection and sequence planning. The simulation results show that the energy consumption is reduced by the proposed method. By means of harvesting robot, the harvesting sequence planning based on the principle of a??minimum energy consumptiona?? and principle of a??shortest patha?? are carried out respectively, and the energy consumption is counted. The results show, compared with the multi-citrus harvesting algorithm based on the principle of a??shortest patha??, the proposed method based on the principle of a??minimum energy consumptiona?? and dual intelligent optimization algorithm can realize the continuous multi-citrus harvesting, and reduce the energy and time consumption as a whole. The energy consumed by the proposed algorithm is reduced by about 12.5% when the number of harvesting points is 3a??8, and about 23.0% when the number of harvesting points is 9a??12. The average time consumed by the proposed algorithm is reduced by about 13.0% when the number of harvesting points is 3a??8, and about 22.0% when the number of harvesting points is 9a??12.
机译:根据柑桔收割机器人的运行要求,在现有收割顺序规划方法的基础上,提出了一种新的收割顺序规划方法及其智能优化算法,实现了逆运动学方案选择和顺序规划的动态规划。仿真结果表明,该方法降低了能耗。通过收割机器人,基于“最小能耗a”原理进行收割顺序计划。和“最短路径”的原理分别进行,并计算能耗。结果表明,与基于“最小路径a”原理的多柑橘收获算法相比,本文提出的基于“最小能耗a”原理的方法。双重智能优化算法可以实现连续多柑橘的采收,整体上减少了能源和时间的消耗。当收获点的数量为3a≤8时,所提出的算法所消耗的能量减少约12.5%,而当收获点的数量为9a≤12时减少约23.0%。当收获点数为3a≤8时,该算法所消耗的平均时间减少了约13.0%,而当收获点数为9a≤12时则减少了约22.0%。

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