Collision Detection of Small Paddy-Field Robots with Soft Obstacles Based on Wavelet Analysis of Estimated Collision Force

This study investigates a method for collision detection caused by soft and deformable obstacles, such as soil and plants (soft obstacles). Field robots must operate while interacting with the soft obstacles in their environments. However, previous studies on collision detection have primarily focused on hard obstacles, such as rocks and artificial structures, and research addressing soft obstacles has been limited. Because soft obstacles absorb impact forces, collision detection using conventional methods is challenging, and determining the collision time is even more difficult. To address these challenges, this study proposes a method that estimates the states, including unknown collision forces, using an extended Kalman filter. A wavelet transform is then applied to the estimated values to detect collisions. The effectiveness of the proposed method was validated using experimental data obtained from a water tank.