[robotics-worldwide] Call for participation IROS08 Workshop on Modeling, Estimation, Path Planning and Control of All Terrain Mobile Robots

Philippe Martinet Philippe.Martinet at lasmea.univ-bpclermont.fr
Wed Jul 2 02:42:01 PDT 2008


Call for Participation and Registration (at the IROS08 site)

IROS’08 Half Day Workshop on Modeling, Estimation, Path Planning and 
Control of All Terrain Mobile Robots

http://wwwlasmea.univ-bpclermont.fr/MEPPC08/Welcome.html 22nd September 
2008


We are pleased to invite you to participate to a Half day workshop on 
“Modeling, Estimation, Path Planning and Control of All Terrain Mobile 
Robots” which will be held during IROS’08 in Nice, 22nd September 2008.

In robotics research, autonomy in general and motion autonomy in 
particular has been a long standing challenge in many fronts. Granting 
mobile robot autonomy demands various technological solutions and their 
functional integration. Some key areas include mobility, perception, 
localization, map building, obstacle avoidance, safety, maintenance etc. 
Vast resources and manpower have been invested worldwide to develop the 
technologies to enable the autonomy of mobile robots. This workshop 
focuses on the state-of-the-art developments on the modeling, 
estimation, and control of all terrain mobile robots. Mobility in 
outdoor unstructured environment remains a critical technology. Precise 
modeling and estimation of the contact between tire and ground, 
localization in unstructured environment, robustness to uncertainties of 
parameters, and precise trajectory tracking in dynamic environment,
represent challenging issues in our scientific community. The proposed 
workshop will summarize the existing results, exchange the ongoing 
researches and address the future directions in these different areas. 
This workshop consists of 6 technical papers of novel research results, 
ranging from slipping/skidding modeling, perturbation estimation, path 
planning, tracking control in the presence of uncertainties, and 
observer designs. The spectrum of these papers addresses the proposed 
topics in a systematic way and great depth. We hope that this workshop 
stimulates more interests and provides more motivations for further 
research and development on intelligent transportation and autonomous 
robotics.

Organizers :

Prof. Danwei Wang

Division of Control and Instrumentation

School of Electrical and Electrical Engineering,
Nanyang Technological University Nanyang Avenue, Singapore 639798
tel : +65 6790 5376, Fax : +65 6793 3318
mel : edwwang at ntu.edu.sg, Home page: http://www.ntu.edu.sg/home/edwwang/



Prof. Philippe Martinet

LASMEA-CNRS Laboratory, Blaise Pascal, University
Campus des Cezeaux, 63177 Aubiere, Cedex, France
tel : +33 473 407 653, Fax : +33 473 407 262
mel : martinet at lasmea.univ-bpclermont.fr,

Home page: http://isrc.skku.edu/~martinet


***********************************************************************************
Program
***********************************************************************************
Mobility and stability of robots on rough terrain: modeling and control
Professor Faiz Ben Amar
Authors : F. Ben-Amar, Ch. Grand, D. Lhomme-Desages, Ph. Bidaud
ISIR, Paris 6, France
amar at robot.jussieu.fr

On rough non-cohesive terrain, mobility or stability of a mobile robot 
could be critical. Then, control and planning processes must be based on 
relevant indexes which qualify these performances or the risk of 
immobility or instability. Basically, the two concepts of mobility and 
stability could be generalized by the one of force transmission between 
the contact frames and a task frame, with unilateral and friction 
constraints. These constraints and that of actuator torques define a 
polyhedral convex cone in task wrench space, which gives a robustness 
measure and a robust motion direction. Some methods directly inspired 
from manipulation or grasping applications will be used here for 
measuring the obstacle clearance of articulated mobile robots or their 
stability on uneven ground surface. These measures are also used for 
motion optimization of kinematically redundant robot such as a hybrid 
wheel-leg robot and an articulated multi-monocycle vehicle. We will also 
develop through the terramechanics theory the relationship between 
mechanical properties of the ground material and the vehicle mobility, 
and show how these results can be used for trajectory tracking in the 
presence of skidding and slipping. In connection with that, the 
identification of ground properties and state parameters estimation such 
as ground velocity will be discussed.

***********************************************************************************
Slipping/skidding estimation of mobile robots in natural rough terrain
Professor Kazuya Yoshida
Authors: Kazuya Yoshida, Keiji Nagatani, Genya Ishigami, and Giulio Reina
Dept. of Aerospace Engineering, Tohoku University, Sendai, Japan
yoshida at astro.mech.tohoku.ac.jp

For a mobile robot, it is critical to detect and compensate for 
slippage, especially when driving in rough terrain environments. Due to 
its highly unpredictable nature, drift largely affects the accuracy of 
localization and navigation systems, even leading to total immobility of 
the vehicle. In this presentation, the authors discuss practical methods 
for effective slipping/skidding estimation and the algorithms for path 
tracking control with on-line compensation of these effects. For the 
slipping/skidding estimation during the traverse of loose terrain, the 
authors developed a couple of methods, both of which use an optical 
camera. One is a method based on the optical flow analysis and the other 
analyses the traces of the wheels marked on the terrain. Both methods 
are validated very useful in practical situations by the experiments 
using a rover test bed.

***********************************************************************************
Integrated estimation for Wheel Mobile Robot posture, velocities, and 
wheel skidding & slipping perturbations
Professor Danwei Wang
Authors: Changboon Low and Danwei Wang CIM, Nanyang Technological 
University, Singapore
edwwang at ntu.edu.sg

This paper presents estimation schemes for high update rate Wheel Mobile 
Robot (WMR) posture, velocities, and perturbation estimation using 
Real-time Kinematic global positioning system (RTK-GPS) and inertial 
sensors for WMR control in the presence of wheel skidding and slipping. 
Outdoor estimation systems based on Kalman Filtering combines the 
inertial sensors with centimeter accuracy RTK-GPS measurements to 
provide essential posture, velocities, and perturbation information. The 
main contribution of this paper is in designing estimation systems to 
deal with WMR control problems in the presence of wheel skidding and 
slipping. The experimental results suggest that with careful modelling 
of WMR, the estimation schemes are able to provide reliable and 
high-update rate information for WMR control applications in the 
presence of wheel skidding and slipping.

***********************************************************************************
Advanced path tracking control for off road mobile robot
Research scientist Roland Lenain
Authors: R. Lenain, C. Cariou, B Thuilot, P. Martinet Cemagref, 
Clermont-Ferrand, France
roland.lenain at cemagref.fr

The growing social needs in terms of environmental and efficiency issues 
make the development of automated mobile robot in a off road context 
more and more important. Nevertheless, the accurate control of such 
robots in natural environment requires to take into account several 
uncertain phenomenon linked in particular to the varying grip conditions 
and different delays. If complex models are available to address such 
problems, the numerous and varying parameters make them hardly tractable 
for an efficient use. In this paper, an adaptive and predictive control 
algorithm, based on an extended kinematics model and dedicated to 
wheeled-steered mobile robots in off-road conditions is proposed for 
high accurate path tracking applications. The effects of variable low 
grip conditions are accounted in a kinematic representation thanks to 
additional variables updated by an observer. This allows the application 
of an adaptive back-stepping control approach able to preserve the 
accuracy of the path tracking despite of harsh grip conditions for a two 
or four steering wheel vehicle. In addition, a predictive curvature 
control allows to compensate the large delays in the actuator used on 
off road heavy vehicle. The relevance of theoretical developments 
detailed in that paper are investigated through full scale experiments 
on both an agricultural tractor (two steering wheels) and a Robucar 
device (four steering wheels).

***********************************************************************************
Adaptive rover behavior based on experiment - An ongoing research
Professor Roland Siegwart
Authors: Ambroise Krebs, Cedric Pradalier, Roland Siegwart

Autonomous Systems Lab Institute of Robotics and Intelligent Systems, 
ETH Zürich, Switzerland
rsiegwart at ethz.ch

Due to the fundamental nature of exploration in rough-terrain, a rover 
accomplishing this task is naturally confronted with an unknown 
environment. It is especially true regarding its interaction with the 
soil, as the nature of it is uncertain. This work aims at creating a 
strategy to allow the rover to learn from its interaction with the 
terrains encountered, with the goal of optimizing its behavior. In 
practice, the information characterizing the terrains, obtained form 
remote sensors (such as camera), is associated with local sensors (e.g. 
IMU), characterizing the rover-terrain interaction. Correspondence 
between those data is learned and used, through the path planner E*, to 
influence the rover trajectory. The CRAB platform is used in this 
project for the implementation and testing of this approach.

***********************************************************************************
Robust Observers and Unknown Input Observers for estimation, diagnosis 
and control of vehicle dynamics
Professor Nassir M'Sirdi
Authors: N. K. M'Sirdi, B. Jaballah, A. Naamane and H. Messaoud
LSIS, Marseille, France
nacer.msirdi at lsis.org

Car accidents occur for several reasons which may involve the driver or 
components of the vehicle or environment. Such situations appear when 
the vehicle is driven beyond the adherence or stability limits. The 
vehicle controllability in its environment along the road admissible 
trajectories still remain an important open problem. Therefore, it is 
extremely important to detect (on time) a tendency towards instability 
or faults. This must be done without adding expensive sensors, so robust 
observers are needed to estimate input variables like contact forces, 
adherence or road profile and characteristics or tire parameters and 
variables (stiffness, forces, velocities, wheel slip and radius). Tire 
forces can be represented by the nonlinear (stochastic) functions of 
wheel slip. The deterministic tire models encountered are complicated 
and depend on several factors (as load, tire pressure, environmental 
characteristics, etc.). This makes on-line estimation of forces and 
parameters difficult for vehicle control applications and detection and 
diagnosis for driving monitoring and surveillance. In this paper we 
propose robust sliding mode observers to tackle problems due to unknown 
inputs and uncertainties of modeling interactions with environment. In a 
first stage sliding mode observers are proposed to estimate contact 
forces assuming steady state or very slowly varing rolling conditions 
(force derivative is approximately null). Secondly force variations are 
assumed slow enough to permit adaptation of linearized contact 
interaction model and step by step estimations are developped. Global 
and partial state observations are considered before contact forces (or 
inputs) estimations. Then we consider, in a third part, application of 
triangular state observers and strutured estimation procedures to get 
inputs estimations. In the latter case, high order sliding mode 
observers will be good means to deduce velocities and accelerations. 
These observers will be shown also as robust to unknown inputs and 
efficient for estimation of road profile and the contact adherences. 
They can be used (with control) to enhances the road safety and lead 
better vehicle adherence and maneuvers ability.


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