Benoit Thuilot

Position based visual servoing: keeping the object in the field of vision

Visual servoing requires an object in the field of view of the camera, in order to control the robot evolution. Otherwise, the virtual link is broken and the control loop cannot continue to be closed. In this paper, a novel approach is presented in order to guarantee that the object remains in the field of view of the camera during the whole robot motion. It consists in tracking an iteratively computed trajectory. A position based modeling adapted to a moving target object is established, and is used to control the trajectory. A nonlinear decoupling approach is then used to control the robot. Experiments, demonstrating the capabilities of this approach, have been conducted on a Cartesian robot connected to a real time vision system, with a CCD camera mounted on the end effector of the robot.

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.

A hybrid strategy for the feedback stabilization of nonholonomic mobile robots

A hybrid strategy for the control of nonholonomic mobile robots is proposed and assessed, using both theoretical arguments and simulation experiments. The control law is a discontinuous state feedback that combines the advantages of time-invariant smooth feedback control far from the target and of time-varying smooth feedback control close to the target, while avoiding their respective drawbacks.<<ETX>>

Outdoor autonomous navigation using monocular vision

In this paper, a complete system for outdoor robot navigation is presented. It uses only monocular vision. The robot is first guided on a path by a human. During this learning step, the robot records a video sequence. From this sequence, a three dimensional map of the trajectory and the environment is built. When this map has been computed, the robot is able to follow the same trajectory by itself. Experimental results carried out with an urban electric vehicle are shown and compared to the ground truth.

Trajectory tracking control of farm vehicles in presence of sliding

In automatic guidance of agriculture vehicles, lateral control is not the only requirement. Lots of research works have been focused on trajectory tracking control which can provide high longitudinal-lateral control accuracy. Satisfactory results have been reported as soon as vehicles move without sliding. But unfortunately pure rolling constraints are not always satisfied especially in agriculture applications where working conditions are rough and not expectable. In this paper the problem of trajectory tracking control of autonomous farm vehicles in presence of sliding is addressed. To take sliding effects into account, two variables which characterize sliding effects are introduced into the kinematic model based on geometric and velocity constrains in presence of sliding. With linearization approximation a refined kinematic model is obtained in which sliding appears as additive unknown parameters to the ideal kinematic model. By integrating parameter adaptation technique with backstepping method, a stepwise procedure is proposed to design a robust adaptive controller. It is theoretically proven that for the farm vehicles subjected to sliding, the longitudinal-lateral deviations can be stabilized near zero and the orientation errors converge into a neighborhood near the origin. To be more realistic for agriculture applications, an adaptive controller with projection mapping is also proposed. Simulation results show that the proposed (robust) adaptive controllers can guarantee high trajectory tracking accuracy regardless of sliding.

Bifurcation and chaos in a simple passive bipedal gait

This paper proposes an analysis of the behavior of perhaps the simplest biped robot: the compass gait model. It has been shown previously that such a robot can walk down a slope indefinitely without any actuation. Passive motions of this nature are of particular interest since they may lead us to strategies for controlling active walking machines as well as to a better understanding of human locomotion. We show here that, depending on the parameters of the system, passive compass gait may exhibit 1-periodic, 2/sup n/-periodic and chaotic gaits proceeding from cascades of period-doubling bifurcations. Since compass equations are quite involved (they combine nonlinear differential and algebraic equations in a 4-dimensional space), our investigations rely, in part, on numerical simulations.

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.

Adaptable Robot Formation Control: Adaptive and Predictive Formation Control of Autonomous Vehicles

The ability to use cooperative small vehicles is of interest in many applications. From material transportation to farming operations, the use of small machines achieving small tasks, but able to work together to complete larger tasks, permits us to rely on a unique kind of vehicle. To be efficient, such a point of view requires the vehicles to be, at least partially, autonomous and their motion must be accurately coordinated for the tasks to be properly achieved. This article proposes a control framework dedicated to the accurate control of a fleet of mobile robots operating in formation. Decentralized control relying on interrobot communication has been favored. To ensure a high relative positioning, adaptive and predictive control techniques are considered, allowing us to account for the influence of several phenomena (such as dynamic perturbations or bad grip conditions) depreciating the relevance of classical approaches based on ideal robots and ideal contact conditions assumptions.