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.
In the development of automated manipulators for fruit and vegetable picking technologies, the challenge of ensuring an efficient, stable, and loss-free picking process has been a complex problem. In such an environment, manipulators require the most efficient and robust control for effective operations. In this paper, a serial 9-DOF redundant manipulator (1P8R) is proposed with various controllers for trajectory tracking problems in agricultural applications. The dynamic analysis of redundant manipulator has been carried out using the Recursive Newton-Euler method. The joint configurations of the robot are determined using optimization techniques for specific Task Space Locations (TSLs) by avoiding obstacles. The process of generating joint trajectories has been implemented by considering the cubic polynomial function. For the task of controlling the robot trajectory tracking in the virtual agricultural environment, different combinations of Proportional (P), Integrative (I), Derivative (D), and Feed-Forward (FF) controllers are employed, and a comparative analysis has been performed among these controllers. To verify the performance of the manipulator, simulations are carried out in a virtual environment using Simulink software. Results show that the robot is able to reach specific TSL accurately with better control and it is found that the implementation of Feed-Forward and PID-CTC controllers has better performance in a complex environment.
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