Autonomous Tractor Control Navigation in Forest Environments

Abstract

This study focuses on the role of autonomous control systems in robotics, focusing on how robot controls the actuator movements after meticulous information processing and decision-making within the robotic framework ROS. To go on this experimental challenge, a diesel tractor was modified into a versatile experimental platform capable of autonomous navigation and control. At the center of this tractor is the sensory module term1ed "Sentry," which consists of a network of interconnected sensors that have been methodically integrated to enable comprehensive ambient perception. The sensors use advanced technologies like 3D 360º LiDAR for spatial mapping, thermal cameras for object detection, RGBD cameras for visual perception, a microcontroller for control, GPS+RTK for precise positioning and a Jetson Xavier for high-performance computing. The experimental assessments done in this work covered a wide range of scenarios, from simulated environments with controlled variables to real-world terrains rife with uncertainty and variability. Valuable insights were gained by analyzing the resulting data, revealing light on the system's operation, performance, and efficacy under various scenarios.

Keywords

• mobile robot
• pid controller
• ros
• sensor fusion