Terrain-Adaptive Control Systems for All-Terrain and Armored Vehicles

All-terrain and armored vehicles (ATVs) are designed to operate in environments where the terrain changes significantly and affects their ‎performance. Traditional control systems don’t adapt to changing environmental conditions, resulting in reduced performance and safety ‎issues. TAC systems solve this by real-time terrain data-driven adaptation of control techniques to improve the performance, mobility, and ‎stability of the vehicle. This project aims to develop and test a new TAC system that adapts to different terrain types, including swampy soil, ‎rugged surfaces, and natural barriers, while maintaining vehicle operational excellence. The proposed TAC system does continuous terrain ‎assessment through sensor data processing and machine learning algorithms that modify the fundamental control elements, which are wheel ‎speeds, torque distribution, and suspension setpoints. Multiple scenario simulations were done through extensive modeling. Experimental ‎data show that TAC improves vehicle stability during off-roading in sandy terrain and rocky surfaces and minimizes mechanical damage ‎from unnecessary slippage and rollover. Military personnel, rescue teams, and exploration teams must use TAC for their missions because ‎TAC helps teams make flexible and instant decisions during unpredictable scenarios‎.