Proportional Controller-Based Algorithm Ensuring Safe Avoidance of Obstacles for Autonomous Tractors

In this study, a proportional controller-based algorithm developed for autonomous tractors to avoid obstacles during agricultural operations such as tillage, seeding, irrigation, harvesting, and fertilization has been integrated with techniques of full cellular decomposition and artificial potential field approaches. Autonomous tractors face various challenges when navigating dynamic and crowded environments. The algorithm provides a robust, accurate, and reliable control framework using real-time sensor data to detect and respond to both moving and stationary obstacles. Its adaptive decision-making capabilities dynamically adjust path planning considering the tractor's kinematics and dynamics, ultimately ensuring collision-free navigation. Simulation results support the effectiveness of the algorithm in various agricultural scenarios, demonstrating its capability to be safely and accurately integrated into modern farming practices with autonomous tractors.