Automatic guidance of a four‐wheel‐steering mobile robot for accurate field operations

Abstract

As world population growth requires an increasing level of farm production at the same time that environmental preservation is a priority, the development of new agricultural tools and methods is required. In this framework, the development of robotic devices can provide an attractive solution, particularly in the field of autonomous vehicles. Accurate automatic guidance of mobile robots in farming constitutes a challenging problem for researchers, mainly due to the low grip conditions usually found in such a context. From assisted-steering systems to agricultural robotics, numerous control algorithms have been studied to achieve high-precision path tracking and have reached an accuracy within ±10 cm, whatever the ground configuration and the path to be followed. However, most existing approaches consider classical two-wheel-steering vehicles. Unfortunately, by using such a steering system, only the lateral deviation with respect to the path to be followed can be satisfactorily controlled. Indeed, the heading of the vehicle remains dependent on the grip conditions, and crabwise motions, for example, are systematically observed on a slippery slope, leading to inaccurate field operations. To tackle this drawback, a four-wheel-steering (4WS) mobile robot is considered, enabling servo of both Cariou et al.: Automatic Guidance of a Four-Wheel-Steering Mobile Robot • 505lateral and angular deviations with respect to a desired trajectory. The path tracking control is designed using an extended kinematic representation, allowing account to be taken online of wheel skidding, while a backstepping approach permits management of the 4WS structure. The result is an approach taking advantage of both rear and front steering actuations to fully compensate for sliding effects during path tracking. Moreover, a predictive algorithm is developed in order to address delays induced by steering actuators, compensating for transient overshoots in curves. Experimental results demonstrate that despite sliding phenomena, the mobile robot is able to automatically and accurately achieve a desired path, with lateral and angular errors, respectively, within ±10 cm and ±2 deg, whatever its shape and whatever the terrain conditions. This constitutes a promising result in efforts to define efficient tools with which to tackle tomorrow's agriculture challenge. C 2009 Wiley Periodicals, Inc.

Sliding-Mode Velocity and Yaw Control of a 4WD Skid-Steering Mobile Robot

“…In particular the norm of the velocity vector, measured by the GPS, must be decomposed into its lateral and longitudinal components. This decomposition is made possible by the addition of an observer of the slippage angle [12], the knowledge of this angle and the velocity vector norm allowing us to make a projection on the axes of the robot frame.…”

Slide-Down Prevention for Wheeled Mobile Robots on Slopes

“…Mobile robot navigation on inclined terrains is required in challenging environments typically found in disaster areas (Zhang & Song, 2014), planetary surfaces (Heverly et al, 2013) or agricultural zones (Cariou et al, 2009). Even if special mechanisms have been proposed to improve mobility on steep slopes, such as leg-track hybrid locomotion (Nagatani et al, 2011), plowing tools for loose soil (Loret De Mola Lemus et al, 2014), or an onboard arm pushed against the ground (Serón et al, 2014), many ground robots rely on wheeled locomotion.…”

“…Sliding down can alter the vehicle's maneuvering ability (Singh & Krishna, 2016) or get the robot stuck (Yamauchi et al, 2014). However, this relevant problem has received less attention than traction wheel slippage (Balakrishna & Ghosal, 1995) (Thueer & Siegwart, 2010), tip-over prevention (Morales et al, 2013), or vehicle sideslip (Cariou, et al, 2009) (Inotsume et al, 2013). This paper proposes slide-down prevention for wheeled robots by real-time computation of a straightforward stability margin for a given ground-wheel friction coefficient.…”

Path tracking in forest terrain by an autonomous forwarder

“…Agricultural path tracking addresses, however, mainly straight paths on flat and even, but somewhat soft and slippery grounds (e.g. Pilarski et al 2002;Tillet et al 2008;Cariou et al 2009;Nagasaka et al 2009). In comparison to agriculture, the forest environment is much more challenging for autonomous machine navigation since operation paths are rarely straight or flat and obstacles are common.…”

“…Global positioning systems (GPS) that use satellite signals are commonly employed for virtual paths (e.g. Cariou et al 2009) and are often combined with path identifying sensors (e.g. Nør-remark et al 2008) as each navigational mode has its advantages and disadvantages (Pilarski et al 2002).…”