地中海温室自主导航中用于坡度与地形补偿的自适应控制架构

中文摘要 AI 辅助

在温室等复杂动态环境中作业的移动农业机器人，需具备在坡度和纹理各异的地形上稳定移动的能力，微小的地形不规则性便可能引发显著的导航误差。本文提出一种基于所携带 payload（载荷）的新型地形适应策略，以确保精确且鲁棒的轨迹跟踪。该方法基于两点：一是对温室最常见的土壤、混凝土、压实沙、砾石这四类地形进行实验表征；二是利用 IMU（惯性测量单元）直接测量地形坡度，以估算该角度对电机输入的作用力。基于此信息，设计了级联轨迹跟踪方案，外环采用基于模型的预测控制器（MPC），内环采用 PI 控制器。系统通过增益调度方法融入自适应前馈控制，可对坡度与地形类型变化引发的干扰进行调整。仿真结果表明，差速驱动机器人在误差指标和控制信号效率两方面均实现显著提升，凸显了所提方法的有效性与鲁棒性。

英文摘要

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.

发表机构

• Universidad de Almería（阿尔梅里亚大学）
• Technical University of Munich（慕尼黑工业大学）

机构由 AI 辅助整理，请以论文原文为准。