Autonomous Navigation of a Center-Articulated and Hydrostatic Transmission Rover using a Modified Pure Pursuit Algorithm in a Cotton Field

Abstract

This study proposes an algorithm that controls an autonomous, multi-purpose, center-articulated hydrostatic transmission rover to navigate along crop rows. This multi-purpose rover (MPR) is being developed to harvest undefoliated cotton to expand the harvest window to up to 50 days. The rover would harvest cotton in teams by performing several passes as the bolls become ready to harvest. We propose that a small robot could make cotton production more profitable for farmers and more accessible to owners of smaller plots of land who cannot afford large tractors and harvesting equipment. The rover was localized with a low-cost Real-Time Kinematic Global Navigation Satellite System (RTK-GNSS), encoders, and Inertial Measurement Unit (IMU)s for heading. Robot Operating System (ROS)-based software was developed to harness the sensor information, localize the rover, and execute path following controls. To test the localization and modified pure-pursuit path-following controls, first, GNSS waypoints were obtained by manually steering the rover over the rows followed by the rover autonomously driving over the rows. The results showed that the robot achieved a mean absolute error (MAE) of 0.04 m, 0.06 m, and 0.09 m for the first, second and third passes of the experiment, respectively. The robot achieved an MAE of 0.06 m. When turning at the end of the row, the MAE from the RTK-GNSS-generated path was 0.24 m. The turning errors were acceptable for the open field at the end of the row. Errors while driving down the row did damage the plants by moving close to the plants’ stems, and these errors likely would not impede operations designed for the MPR. Therefore, the designed rover and control algorithms are good and can be used for cotton harvesting operations.

Applications of Autonomous Navigation Technologies for Unmanned Agricultural Tractors: A Review

“…Trimble real-time extended (RTX) technology facilitates real-time accurate positioning with centimeter-level precision in a quick convergence period [14]. Nowadays, GNSS systems are inexpensive; the RTK-GNSS single-frequency receiver costs only USD800 in the USA [15]. Conversely, according to market investigations in China, a set of agricultural machinery based on the BDS navigation system is currently priced around USD1000 to USD3000.…”

Automation of large pavement test vehicle

“…We have chosen a semi-empirical approach to steering calibration, whereby the linear sensor readings are empirically mapped to steering angle values, but steering angle is further mapped to turning radius via analysis based on the Load Cart geometry. As described in the work of other practitioners calibrating articulated vehicles, steering angle calibration involves recording data reported by the linear potentiometer mounted on the hydraulic ram as the steering angle of the Load Cart changes while turning left and right [6]. Based on the geometry of the Load Cart, including the locations of the mount points of the hydraulic ram and the configuration of the steering struts [7], engineers calculated the theoretical relationship between the linear sensor length and the steering angle, obtaining the relationship shown in blue in Figure 19 below.…”

Research on Path Tracking for an Orchard Mowing Robot Based on Cascaded Model Predictive Control and Anti-Slip Drive Control

“…Among them, control algorithms directly affect the stable operation of lawn-mowing robots and the accuracy of automatic navigation and positioning systems, thereby affecting the efficiency of lawn-mowing and fruit tree production. In recent years, scholars have conducted extensive research on the work efficiency, continuous and stable operation, and path-tracking control of unmanned agricultural machinery in complex operating environments, mainly using model predictive control (MPC), fuzzy control, pure tracking control, PID control, and linear quadratic regulator (LQR) control [3][4][5][6][7][8][9][10]. Yangyang [11] proposed an agricultural machine path-tracking algorithm based on optimal target points.…”