Modelling and Simulation of a Redundant Agricultural Manipulator with Virtual Prototyping

A. Reddy, V. V. M. J. S. Chembuly, V. Rao
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Abstract

The development of autonomous robots for agricultural applications includes motion planning, fruit picking, and collision avoidance with surrounding environments, and these become challenging tasks. For harvesting applications, robust control of the manipulator is needed for the effective motion of the robot. Several combinations of Proportional(P)- Integrative(I)- Derivative(D) controllers are modelled and a simulation study was performed for trajectory tracking of a redundant manipulator in virtual agricultural environments. The article presents a comprehensive study on kinematic modelling and dynamic control of redundant manipulator for fruit-picking applications in virtual environments. The collisions with surrounding environment were eliminated using ‘bounding box technique’. The joint variables are obtained by constructing Inverse Kinematics (IK) problem and are determined using a classical optimization technique. Different controllers are modelled in the ‘Simulink’ environment and are tuned to generate error-free trajectory tracking during harvesting. The task space locations (TSLs) are considered as via-points, and joint variables at each TSLs are obtained by Sequential Quadratic Programming (SQP) technique. Joint-level trajectories are generated using Quintic and B-spline polynomials. For effective trajectory tracking, torque variations are controlled using the PID and Feedforward (FF) controller. The dynamic simulations of the robot manipulator are performed in Simscape Multibody software. Results show that the during the trajectory tracking of the manipulator, the Feed-forward controller performs best with Quintic polynomial trajectory.
基于虚拟样机的冗余农业机械臂建模与仿真
农业自主机器人的发展包括运动规划、水果采摘和与周围环境的碰撞避免,这些都成为具有挑战性的任务。在收获应用中,为了保证机器人的有效运动,需要对机械手进行鲁棒控制。对比例(P)-积分(I)-导数(D)控制器的几种组合进行了建模,并对虚拟农业环境中冗余机械手的轨迹跟踪进行了仿真研究。本文对虚拟环境中用于水果采摘的冗余机械手的运动学建模和动态控制进行了全面的研究。使用“边界盒技术”消除了与周围环境的碰撞。通过构造逆运动学问题得到关节变量,并用经典的优化方法确定关节变量。不同的控制器在“Simulink”环境中建模,并在收获过程中进行调整以产生无错误的轨迹跟踪。将任务空间位置(TSLs)视为中点,利用序列二次规划(SQP)技术得到每个TSLs上的联合变量。利用五次多项式和b样条多项式生成关节级轨迹。为了实现有效的轨迹跟踪,利用PID和前馈(FF)控制器控制转矩变化。在Simscape Multibody软件中对该机械手进行了动力学仿真。结果表明,在机械臂的轨迹跟踪过程中,前馈控制器对五次多项式轨迹的跟踪效果最好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
6.30
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0.00%
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