Three different approaches to colour texture analysis are tested on the classification of images from the VisTex and Outex databases. All the methods tested are based on extensions of the cooccurrence matrix method. The first method is a multispectral extension since cooccurrence matrices are computed both between and within the colour bands. The second uses joint colour-texture features: colour features are added to grey scale texture features in the entry of the classifier. The last uses grey scale texture features computed on a previously quantized colour image. Results show that the multispectral method gives the best percentages of good classification (VisTex: 97.9%, Outex: 94.9%). The joint colour-texture method is not far from it (VisTex: 96.8%, Outex: 91.0%), but the quantization method is not very good (VisTex:83.6%, Outex:68.4%). Each method is decomposed to try to understand each one deeper, and computation time is estimated to show that multispectral method is fast enough to be used in most real time applications.

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.

The constantly rising food demand of a steadily increasing world population requires improvement in efficiency, competitiveness, and productivity of current meat and dairy production systems. Thus, robotics‐based approaches have an important role to play, especially in dairy cattle farming, because the intensive grazing systems depend on numerous time‐consuming and tedious operations required to be carried out to assure an optimal cattle feeding as well as utilization of forage resources. These operations range from data acquisition considering the amount and quality of available forage within the paddocks, to carrying out maintenance operations in order to safeguard high yield with required quality and availability of the forage throughout the whole grazing season. This issue is addressed within the ICT‐AGRI project i‐LEED, in which one of the main tasks is to build accurate and feasible trajectories for a scouting and a maintenance robot to fully or partially cover the paddocks, as well as to reach only targeted spots previously located. This paper presents an original and fully operational method for trajectory planning by designing segments of clothoids while taking into account additional dynamic constraints, such as the steering rate capacity of the robot, its speed, and the maximally allowed transverse acceleration. In case of specific points to reach within a paddock, this approach is completed by morphological operations to first define regions and next rank them w.r.t. the minimal length of travel by solving the traveling salesman problem. Based on the kinematic and dynamic properties of the scouting and maintenance robots devoted to the i‐LEED project, the performances of the proposed planning approaches are presented.

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An accurate localization system (Carrier Phase differential GPS receiver) allows the design and implementation of an absolute vehicle guidance system. The preliminary work, presented in this paper, was aimed at validating the use of one GPS receiver in a vehicle guidance system, without any orientation sensor. We designed and implemented a non linear control law to perform a line-following task. Real-time experiments have been carried out on a combine harvester.