Performance Evaluation of an Autonomously Driven Agricultural Vehicle in an Orchard Environment

To address the problems of inefficient agricultural production and labor shortages, there has been active research to develop autonomously driven agricultural machines, using advanced sensors and ICT technology. Autonomously driven speed sprayers can also reduce accidents such as the pesticide poisoning of farmers, and vehicle overturn that frequently occur during spraying work in orchards. To develop a commercial, autonomously driven speed sprayer, we developed a prototype of an autonomously driven agricultural vehicle, and conducted performance evaluations in an orchard environment. A prototype of the agricultural vehicle was created using a rubber-tracked vehicle equipped with two AC motors. A prototype of the autonomous driving hardware consisted of a GNSS module, a motion sensor, an embedded board, and an LTE module, and it was made for less than $1000. Additional software, including a sensor fusion algorithm for positioning and a path-tracking algorithm for autonomous driving, were implemented. Then, the performance of the autonomous driving agricultural vehicle was evaluated based on two trajectories in an apple farm. The results of the field test determined the RMS, and the maximums of the path-following errors were 0.10 m, 0.34 m, respectively.

Badminton Path Tracking Algorithm Based on Computer Vision and Ball Speed Analysis

With the development of artificial intelligence and the rapid development of the computer industry, the practicability of computer vision programs is gradually improved. In this paper, the badminton path tracking algorithm based on computer vision analyzes the badminton trajectory and speed. This paper is aimed at analyzing the image processing technology and path tracking algorithm by using computer vision to obtain relevant data and then exploring the factors of badminton path and ball speed transformation, which provides reference significance for badminton players in future training. The path tracking algorithm is used to predict the rotation angle, the ball speed, and the athlete’s body information during the badminton movement through sensors, and the position information of the moving target is captured based on the visual field tracking and target dynamic tracking. Combined with specific badminton players, we first analyze the angle of each limb and the speed of the racket in the process of movement and record the data. Determine different positioning points for different actions, such as pushing the ball, picking the ball, hooking the ball, and rubbing the hair. In this process, we aim at the connection between the highest point and the lowest point of the badminton trajectory and the ball speed. This process fully combines the theoretical knowledge of the path tracking algorithm. The experimental results show that different service skills have different effects on the trajectory and speed of badminton. In the test of relevant data by using the push and receive skills, the lowest point of the ball served by player A in the first three times is higher than that by player B. The most significant difference between the lowest points of the five times is the second time, with a difference of 0.2 m, and the third time, with a minimum difference of 0.03 m.

Low-Speed Vehicle Path-Tracking Algorithm Based On Model Predictive Control Using QPKWIK Solver

Automated valet parking is a part of autonomous vehicles. Path tracking is a vital capability of autonomous vehicles. In the scenario of automatic valet parking, the existing control algorithm will produce a high tracking error and a high computational burden. This paper proposes a path-tracking algorithm based on model predictive control to adapt to low-speed driving. By using the model predictive control method and vehicle kinematics model, a path tracking controller is designed. Combining the dual algorithm to further optimize the solver, a new QPKWIK solver is proposed. The simulation results show that the solution time of the QPKWIK solver is 25% less than that of the QP solver, and the tracking error is reduced by up to 41% compared with the QP solver. In the parking lot, the tracking performance is tested under four common scenarios, and the experimental results show that this controller has better tracking performance.

INTELLIGENT CONTROL TECHNOLOGY OF AGRICULTURAL GREENHOUSE OPERATION ROBOT BASED ON FUZZY PID PATH TRACKING ALGORITHM

With the development of agricultural automation, applying intelligent algorithms to the navigation control of agricultural work vehicles has important practical significance for improving vehicle navigation accuracy and operation efficiency. In view of the complexity of the agricultural greenhouse environment, this study proposed a fuzzy PID path tracking algorithm based on the traditional vehicle PID control system. This algorithm uses a fuzzy controller to improve the PID control system, thereby realizing the online setting of PID control parameters. In order to verify the effectiveness of the fuzzy PID path tracking algorithm, the improved control system was applied to the tracked vehicle robot of Beijing Forestry University, and the operation performance of the vehicle robot was tested. The research results show that the absolute error rate of vehicle robot distance measurement is less than 1%; the error of the man-machine follow-up test is between 4 and 7 cm, and the measured follow-up distance is slightly less than the safe follow-up distance; the maximum error of the vehicle's fixed-point parking is 0.3 cm; The linear position tracking control has a lateral position deviation of ±3cm, and the vehicle's linear driving control and steering effects are better. The fuzzy PID path tracking algorithm designed this time shows good control performance, which has reference significance for the practical application of agricultural robots.

A new geometry-based secondary path planning for automatic parking

In auto-parking systems, a certain degree of error in the path tracking algorithm is inevitable. This is caused by actuator error, tire slipping, or other factors relevant to and included in the parking process. In such situations, the parking path needs to be updated to finish parking successfully which is referred to as secondary path planning. Herein, a new geometry-based method is proposed to deal with this issue, which can be called the pattern-based method. In this method, a predefined path pattern set consisting of 24 multi-segment patterns is developed first. These patterns are composed of straight lines and arcs and account for constraints due to motion and the immediate environment. Then, a traversal policy is adopted to select the path pattern from the set, and the sequential quadratic programming algorithm is used to determine the optimal parameters that fine-tune the pattern to meet the current constraints. In the simulation section, the effectiveness of the proposed method is demonstrated. Moreover, compared to the search-based method represented by a variation of rapidly exploring random tree*, the proposed method has a higher planning performance.