2008 IEEE/RSJ International Conference on Intelligent RObots and Systems

IROS08 Workshop on Modeling, Estimation, Path Planning and Control of All Terrain Mobile Robots

Half Day Workshop

September 22th 2008, Nice, France

Proceedings

Contact : Professor Philippe Martinet
LASMEA-CNRS Laboratory, Blaise Pascal, University
Campus des Cezeaux
63177 Aubiere, Cedex, France
tel : +33 473 407 653, Sec : +33 473 407 261, Fax : +33 473 407 262
mel : martinet@lasmea.univ-bpclermont.fr, Home page: http://isrc.skku.edu/~martinet

Contact : Professor Danwei Wang
Division of Control and Instrumentation School of Electrical and Electrical Engineering, Block S2
Nanyang Technological University Nanyang Avenue, Singapore 639798
tel : +65 6790 5376, Fax : +65 6793 3318
mel : edwwang@ntu.edu.sg, Home page: http://www.ntu.edu.sg/home/edwwang/

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.

Format of the paper: Please follows the IROS08 rules given at http://iros2008.inria.fr/submission.php

Important dates


• Deadline for Paper submission: May 31th, 2008
• Acceptance with review comments: June 22th, 2008
• Deadline for final paper submission: July 7th, 2008

Workshop


• Room: Gallieni 5
• Starting hour: 2:00pm
• Ending hour: 6:30pm

Presentation of paper


• Paper presentation (presentation, question): 40min (30min, 10 min)

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@robot.jussieu.fr
Presentation Slides

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@astro.mech.tohoku.ac.jp
Presentation Slides

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@ntu.edu.sg
Presentation Slides

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@cemagref.fr
Presentation Slides

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@ethz.ch
Presentation Slides

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@lsis.org
Presentation Slides

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.