Galati Rocco, Reina Giulio
Department of Engineering for Innovation, University of Salento, Lecce, Italy.
Front Robot AI. 2019 Jun 21;6:46. doi: 10.3389/frobt.2019.00046. eCollection 2019.
This paper presents a novel approach for terrain characterization based on a tracked skid-steer vehicle with a passive independent suspensions system. A set of physics-based parameters is used to characterize the terrain properties: drive motor electrical currents, the equivalent track, the power spectral density for the vertical accelerations and motor currents. Based on this feature set, the system predicts the type of terrain that the robot traverses. A wide set of experimental results acquired on various surfaces are provided to verify the study in the field, proving its effectiveness for application in autonomous robots.
本文提出了一种基于带有被动独立悬架系统的履带式滑移转向车辆的地形特征描述新方法。使用一组基于物理的参数来表征地形特性:驱动电机电流、等效履带、垂直加速度和电机电流的功率谱密度。基于此特征集,系统预测机器人所穿越的地形类型。提供了在各种表面上获得的大量实验结果,以验证该领域的研究,证明其在自主机器人中的应用有效性。