铰接式重载机器人的时间-能量最优轨迹规划研究

Ming Han, Bin Xiong, Jinyue Liu, Dong Yang, Tiejun Li
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引用次数: 0

摘要

关节型重载机器人在建筑环境中的应用越来越广泛。针对此类机器人工作效率低、能耗高的问题,提出了一种结合路径优化和轨迹优化的多目标自适应轨迹规划方法,以提高机器人的工作效率,降低能耗。首先,基于运动学和动力学分析,考虑摩擦因素,构建机器人轨迹能耗模型。然后,根据已知工作空间中关键点的姿态,通过路径点求解方法,考虑关节负载特性,得到关节空间中的最优路径点。在此基础上,建立考虑运行时间和能耗的多目标模型,规划五次 B-样条曲线关节空间的插补轨迹。最后,在机械手关节速度、加速度和扭矩的约束下,利用精英非支配排序遗传算法(NSGA-II)获得最优解,并通过多目标自适应优化方法选择最优权重因子,从而获得最优位置-时间序列。实验结果表明,与五次多项式轨迹优化方法相比,在工作效率相同的情况下,所提方法的能耗降低了 10.90%。本文的研究成果为其他目标轨迹规划提供了一种新的优化思路。
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Research on time-energy optimal trajectory planning of articulated heavy-duty robot
Articulated heavy-duty robots are more and more widely used in the construction environment. Aiming at the problems of low working efficiency and high energy consumption of this kind of robot, a multi-objective adaptive trajectory planning method combining path optimization and trajectory optimization is proposed to improve the working efficiency of the robot and reduce energy consumption. Firstly, based on kinematics and dynamic analysis considering friction, the energy consumption model of robot trajectory is constructed. Then, according to the posture of the key points in the known workspace, the optimal path points in the joint space are obtained by a path point solution method considering the joint load characteristics. On this basis, a multi-objective model considering running time and energy consumption is established to plan the interpolation trajectory of the joint space of the quintic B-spline curve. Finally, constrained by the velocity, acceleration and torque of the joint of the manipulator, the optimal solution is obtained by using the elite non-dominated sorting genetic algorithm (NSGA-II), and the optimal weight factor is selected by a multi-objective adaptive optimization method to obtain the optimal position-time series. The experimental results show that compared with the quintic polynomial trajectory optimization method, the energy consumption of the proposed method is reduced by 10.90% under the same working efficiency. The research results of this paper provide a new optimization idea for other target trajectory planning.
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来源期刊
CiteScore
3.80
自引率
10.00%
发文量
625
审稿时长
4.3 months
期刊介绍: The Journal of Mechanical Engineering Science advances the understanding of both the fundamentals of engineering science and its application to the solution of challenges and problems in engineering.
期刊最新文献
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