通过自适应控制补偿坡度与地形变化,提升温室机器人导航精度。
An Adaptive Control Architecture for Slope and Terrain Compensation in Autonomous Navigation in Mediterranean Greenhouses

- 基于负载与惯性测量单元(IMU)实时感知地形坡度
- 采用模型预测+比例积分的级联控制,误差显著降低
- 适用于复杂温室环境,适合农业机器人开发者参考
在复杂动态的温室环境中,移动农业机器人需在不同坡度和表面材质下稳定行驶,微小地形不规则即可能引发严重导航偏差。本文提出一种基于载荷的新型地形适应策略,结合温室常见土壤、混凝土、压实沙和碎石的实验表征,以及通过惯性测量单元(IMU)直接测量地形坡度,估算坡度对电机输入的影响力。据此设计了级联轨迹跟踪架构:外环为模型预测控制器(MPC),内环为比例积分(PI)控制器,并引入增益调度的自适应前馈控制,以应对坡度与地面类型变化带来的扰动。仿真结果表明,该系统在轨迹跟踪误差和控制信号效率方面均有显著提升,验证了方法的有效性与鲁棒性。
原文摘要 · Abstract (English)
The ability to move stably over terrain with varying slopes and textures is essential for mobile agricultural robots operating in complex and dynamic environments such as greenhouses, where small terrain irregularities can lead to significant navigation errors. This article presents a novel terrain-adaptation strategy based on the carried payload, ensuring accurate and robust trajectory tracking. The proposed approach is based on: (i) the experimental characterization of the most common types of greenhouse soil, concrete, compacted sand, and gravel, and (ii) the direct measurement of terrain slope using the IMU, in order to estimate the force with which this angle affects the motor input. Based on this information, a cascade trajectory-tracking scheme has been designed, consisting of a model-based predictive controller (MPC) in the outer loop and a PI controller in the inner loop. The system incorporates an adaptive feedforward control through gain scheduling approach, capable of adjusting to disturbances caused by variations in slope and terrain type. Simulation results demonstrate that the differential-drive robot achieves a significant improvement both in error indices and in control signal efficiency, highlighting the effectiveness and robustness of the proposed approach.
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