Christophe Cariou

High accuracy path tracking for vehicles in presence of sliding: Application to farm vehicle automatic guidance for agricultural tasks

When designing an accurate automated guidance system for vehicles, a major problem is sliding and pseudo-sliding effects. This is especially the case in agricultural applications, where five-centimetre accuracy with respect to the desired trajectory is required, although the vehicles are moving on slippery ground.It has been established that RTK GPS was a very suitable sensor to achieve automated guidance with such high precision: several control laws have been designed for vehicles equipped with this sensor, and provide the expected guidance accuracy as long as the vehicles do not slide. In previous work, further control developments have been proposed to take sliding into account: guidance accuracy in slippery environments has been shown to be preserved, except transiently at the beginning/end of curves. In this paper, the design of this control law is first recalled and discussed. A Model Predictive Control method is then applied in order to preserve accuracy of guidance even during these curvature transitions. Finally, the overall control scheme is implemented, and improvements with respect to previous guidance laws are demonstrated through full-scale experiments.

Automatic Guidance of a Farm Tractor Relying on a Single CP-DGPS

Precision agriculture involves very accurate farm vehicle control along recorded paths, which are not necessarily straight lines. In this paper, we investigate the possibility of achieving this task with a CP-DGPS as the unique sensor. The vehicle heading is derived according to a Kalman state reconstructor, and a nonlinear velocity independent control law is designed, relying on chained systems properties. Field experiments, demonstrating the capabilities of our guidance system, are reported and discussed.

Model Predictive Control for Vehicle Guidance in Presence of Sliding: Application to Farm Vehicles Path Tracking

One of the major current developments in agricultural machinery aims at providing farm vehicles with automatic guidance capabilities. With respect to standard mobile robots applications, two additional difficulties have to be addressed: firstly, since farm vehicles operate on fields, sliding phenomena inevitably occurs. Secondly, due to large inertia of these vehicles, small delays introduced by low-level actuators may have noticeable effects. These two phenomena may lower considerably the accuracy of path following control laws. In this paper, a vehicle extended kinematic model is first built in order to account for sliding phenomena. These latter effects are then taken into account within guidance laws, relying upon nonlinear control techniques. Finally, a Model Predictive Control strategy is developed to reduce the effects induced by actuation delays and vehicle large inertia. Capabilities of this control scheme is demonstrated via full scale experiments carried out with a farm tractor, whose realtime localization is achieved relying uniquely upon a RTK GPS sensor.

Adaptive control for car like vehicles guidance relying on RTK GPS: rejection of sliding effects in agricultural applications

Numerous agricultural applications require very accurate guidance of farm vehicles. Current works have established that RTK GPS was a very suitable sensor in order to meet the expected precision: several control laws have been designed for vehicles equipped with such a sensor, and satisfactory results have been achieved as long as vehicles do not slide. Nevertheless, in actual working conditions (sloping fields, entering into curves on a wet land, etc.), sliding inevitably occurs. In this paper, we design a nonlinear adaptive control law in order to preserve guidance precision in presence of sliding: realtime sliding estimation is used to correct vehicle evolution. Field experiments, demonstrating the capabilities of that control scheme are reported and discussed.

Adaptive and Predictive Path Tracking Control for Off-road Mobile Robots

A major problem in the design of control laws dedicated to mobile robots appears when the classical hypothesis of rolling without sliding wheels is violated. It is generally the case for off-road vehicles as adherence conditions are often not satisfactory and sliding can then cease to be negligible. Consequently theoretical performance is impaired and the vehicle is no longer accurately controlled. It is particularly harmful with respect to path tracking tasks, where a loss of accuracy in rough terrain can generate a hazardous situation. Previous work based on the assumption of rolling without sliding has shown very satisfactory results with respect to that task when sliding is not preponderant. It has also made it possible to pinpoint and study the effects of sliding when it appears to be non-negligible. To preserve path tracking accuracy with respect to this phenomenon, a new control law based on an extended kinematic model (updated on-line via an adaptive method) is proposed and discussed. Such control is very efficient when adherence conditions are constant, but overshoots can appear when an abrupt variation is recorded (which is especially the case at the beginning/ end of curves due to low level delays and inertial effects). A model predictive control approach is then added to limit such transient phases in cases where a curved path is followed. The paper is organized as follows: the extended kinematic model is presented as well as the observation of unmeasured parameters required to feed it. A nonlinear control law can then be designed and the results obtained are discussed. Finally, the model predictive control approach is integrated and the overall control scheme is presented. The capabilities of the approach described in this paper are then discussed through full scale experiments.

Sideslip angles observer for vehicle guidance in sliding conditions: application to agricultural path tracking tasks

Automatic devices dedicated to vehicle guidance in off-road conditions are necessarily confronted with sliding phenomenon, since it may considerably damage the accuracy of the following task. Control laws taking explicitly into account such a phenomenon have already been designed in previous work. They can actually improve the guidance accuracy. However their efficiency is highly dependent on the sliding parameters estimation (since these parameters cannot be provided by a direct measurement). In this paper, an observer-like estimator is designed, providing sideslip angles from a single exteroceptive sensor, namely a real time kinematic GPS (RTK-GPS). Improvements in guidance accuracy, with respect to previous estimation approaches, is demonstrated through full scale experiments, addressing agricultural applications

Automatic guidance of a farm tractor along curved paths, using a unique CP-DGPS

Precision agriculture involves very accurate farm vehicle control along recorded paths, which are not necessarily straight lines. We investigate the possibility of achieving this task with CP-DGPS (carrier phase differential GPS) as the unique sensor. The vehicle heading is derived according to a Kalman state reconstructor, and a nonlinear velocity independent control law is designed, relying on chained systems properties. Field experiments, demonstrating the capabilities of our guidance system, are reported and discussed.

A new nonlinear control for vehicle in sliding conditions: application to automatic guidance of farm vehicles using RTK GPS

Since Global Navigation Satellite systems are able to supply very accurate coordinates of a point (about 2 cm with a RTK GPS), such a sensor is very suitable to design vehicle guidance system. It is especially the case in agricultural tasks where a centimeter precision is often required (seeding, spraying,...). To answer to growing high precision agriculture principle demand, several control laws for automated vehicle guidance relying on this sensor have been developed. Such guidance systems are able to supply an acceptable steering accuracy as long as vehicle does not slide (path tracking on even ground with good adherence properties...), what alas inevitably occurs in agricultural tasks. Several principles are here presented to steer vehicle whatever properties of ground and path to be followed are. In this paper a new extended kinematic model with sliding accounted is presented which allows describing vehicle dynamics in all guidance conditions. Via this model a new nonlinear control law can be designed, which integrates sliding effects. Its capabilities are investigated through simulations and experimental tests.

Autonomous maneuver of a farm vehicle with a trailed implement: motion planner and lateral-longitudinal controllers

This paper addresses the problem of path generation and motion control for the autonomous maneuver of a farm vehicle with a trailed implement in headland. A reverse turn planner is firstly investigated, based on primitives connected together to easily generate the reference motion. Then, both steering and speed control algorithms are presented to accurately guide the vehicle-trailer system. They are based on a kinematic model extended with additional sliding parameters and on model predictive control approaches. Real world experiments have been carried out on a low friction terrain with an experimental mobile robot pulling a trailer. At the end of each row, the reverse turn is automatically generated to connect the next reference track, and the maneuver is autonomously performed by the vehicle-trailer system. Reported experiments demonstrate the capabilities of the proposed algorithms.

Path following of a vehicle-trailer system in presence of sliding: Application to automatic guidance of a towed agricultural implement

This paper addresses the problem of sliding parameter estimation and lateral control of an off-road vehicle-trailer system. The aim is to accurately guide the position of the trailer with respect to a planned trajectory, whatever ground conditions and trajectory shape. Relevant sliding parameter estimation is first proposed, based on the kinematic model of the system extended with side slip angles. Then, a vehicle steering control algorithm is presented to move away the vehicle from the reference trajectory in order for the trailer to achieve accurate path tracking. Reported experiments demonstrate the capabilities of the proposed algorithms.