Path Tracking Control for Autonomous Harvesting Robots Based on Improved Double Arc Path Planning Algorithm
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Path Tracking Control for Autonomous Harvesting Robots Based on Improved Double Arc Path Planning Algorithm Lihui Wang 1
&
Mingjie Liu 1
Received: 16 March 2020 / Accepted: 4 September 2020 # Springer Nature B.V. 2020
Abstract Focusing on the problems of big overshoot and long convergence time due to the large initial heading error, a new path tracking control strategy for autonomous harvesting robots based on improved double arc path planning is designed. Firstly, the improved double arc path planning algorithm includes global path planning and local planning. The shortest path distance is taken as the goal, so the optimal tangent arc path from the initial point to the reference straight line can be automatically planned by the global path planning. Due to the problems such as control delay in harvesting robot, the global path cannot be effectively tracked. By analyzing the influence of the non-mutable steering angle and control delay on path tracking, a new local path planning algorithm is proposed. Then, the two preview points obtained in global planning can be optimized dynamically, and the actual reliability of the algorithm can be enhanced. Secondly, the error compensation model is designed to compensate the installation error of the positioning antenna in real time, to satisfy the simplified condition of the two-wheeled vehicle model. Finally, by combining the large angle steering control method and the pure pursuit algorithm, a new hybrid control strategy is designed to solve the steering angle, and the path tracking function of harvesting robots is realized. Experiment results demonstrate that the hybrid control strategy can reduce the oscillation of driving path, enhance the convergence, then, improve working quality and efficiency of robots. Keywords Autonomous harvesting robot . Double arc . Path tracking . Pure pursuit . Control strategy
1 Introduction The autonomous operation of agricultural harvesting robots can improve working quality and efficiency and reduce the labor intensity of drivers [1]. It is one of the hot topics in the intelligence research of agricultural equipment. Path tracking is a key part in intelligent harvesting robot’s autonomous operation [2]. To enhance the performance of path tracking, it is urgent to design a control strategy with fast convergence, high control precision and strong stability [3, 4]. With excellent control strategy, the steering angle from the current pose to the desired path can be calculated quickly, and then path tracking function can be achieved. Currently, the main control strategies include proportion integration differentiation (PID) control, pure pursuit algorithm, fuzzy logic control and MPC method [5–8]. Auday
* Lihui Wang [email protected] 1
School of Instrument Science and Engineering, Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, Southeast University, Nanjing 210096, China
Al-Mayyahi et al. of the University of Sussex in the United Kingdom designed a path tracking algorithm based on fra
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