High precision control of tracked field robots in the presence of unknown traction coefficients
Accurate steering through crop rows that avoids crop damage is one of the most important tasks for agricultural robots utilized in various ﬁeld operations, such as monitoring, mechanical weeding, or spraying. In practice, varying soil conditions can result in off-track navigation due to unknown traction coefﬁcients so that it can cause crop damage. To address this problem, this paper presents the development, application, and experimental results of a real-time receding horizon estimation and control (RHEC) framework applied to a fully autonomous mobile robotic platform to increase its steering accuracy. Recent advances in cheap and fast microprocessors, as well as advances in solution methods for nonlinear optimization problems, have made nonlinear receding horizon control (RHC) and receding horizon estimation (RHE) methods suitable for ﬁeld robots that require high frequency(milliseconds)updates. Areal-timeRHECframeworkisdevelopedandappliedtoafully autonomous mobile robotic platform designed by the authors for in-ﬁeld phenotyping applications in Sorghum ﬁelds. Nonlinear RHE is used to estimate constrained states and parameters, and nonlinearRHCisdesignedbasedonanadaptivesystemmodelwhichcontainstime-varying parameters. The capabilities of the real-time RHEC framework are veriﬁed experimentally, and the results show an accurate tracking performance on a bumpy and wet soil ﬁeld. The mean values of the Euclidean errorandrequiredcomputationtimeoftheRHECframeworkarerespectivelyequalto0.0423mand 0.88 milliseconds.