[robotics-worldwide] Call for participation ICRA10 Workshop on Robotics and Intelligent Transportation System

Philippe MARTINET Philippe.MARTINET at lasmea.univ-bpclermont.fr
Tue Mar 23 20:37:01 PDT 2010

ICRA10 Workshop on Robotics and Intelligent Transportation System

Full Day Workshop

May 7th 2010, Anchorage, Alaska

Contact : Professor Philippe Martinet

Research Director Christian Laugier, INRIA, Emotion project, INRIA  
Rhône-Alpes, 655 Avenue de l'Europe, 38334 Saint Ismier Cedex, France,  
Phone: +33 4 7661 5222, Fax : +33 4 7661 5477, Email:  
Christian.Laugier at inrialpes.fr,
Home page: http://emotion.inrialpes.fr/laugier  

Beverly W. Long Distinguished Professor Ming Lin, Department of  
Computer Science University of North Carolina, 254 Brooks Building,  
CB#3175 , Chapel Hill, NC 27599-3175, USA, Phone: +01 919 962-1974 ,  
Fax : +01 919 962-1799, Email: lin at cs.unc.edu,
Home page: http://www.cs.unc.edu/~lin/ <http://www.cs.unc.edu/%7Elin/>

Professor Philippe Martinet, LASMEA-CNRS Laboratory, Blaise Pascal  
University, Campus des Cezeaux, 63177 Aubiere, Cedex, France, Phone:  
+33 473 407 653, Sec : +33 473 407 261, Fax : +33 473 407 262, Email:  
martinet at lasmea.univ-bpclermont.fr,
Home page:  

Professor Urbano Nunes, Department of Electrical and Computer  
Engineering of the Faculty of Sciences and Technology of University of  
Coimbra, 3030-290 Coimbra, Portugal, GABINETE 3A.10, Phone: +351 239  
796 287, Fax: +351 239 406 672, Email: urbano at deec.uc.pt,
Home page: http://www.isr.uc.pt/~urbano <http://www.isr.uc.pt/%7Eurbano>

General Scope

Autonomous driving and navigation is a major research issue which  
would affect our lives in near future. The purpose of this workshop is  
to discuss topics related to the challenging problems of autonomous  
navigation and of driving assistance in open and dynamic environments.  
Technologies related to application fields such as unmanned outdoor  
vehicles or intelligent road vehicles will be considered from both the  
theoretical and technological point of views. Several research  
questions located on the cutting edge of the state of the art will be  
addressed. Among the many application areas that robotics is  
addressing, transportation of people and goods seem to be a domain  
that will dramatically benefit from intelligent automation. Fully  
automatic driving is emerging as the approach to dramatically improve  
efficiency while at the same time leading to the goal of zero  
fatalities. Theses new technologies can be applied efficiently for  
other application field like unmanned vehicles, w
  heelchair or assistance mobile robot. Technologies related to this  
area, such as autonomous outdoor vehicles, achievements, challenges  
and open questions would be presented, including the following topics:  
Object detection, tracking and classification, Collision prediction  
and avoidance, Environment perception, vehicle localization and  
autonomous navigation, Real-time perception and sensor fusion, SLAM in  
dynamic environments, Real-time motion planning in dynamic  
environments, 3D Modelling and reconstruction, Human-Robot  
Interaction, Behavior modeling and learning, Robust sensor-based 3D  
reconstruction, Modeling and Control of mobile robot, Cooperation and  
communications, Multi-agent based architectures, Cooperative unmanned  
vehicles. This edition will be done with 4 wellknown invited speakers  
(Alberto Broggi, Alexandre Bayen, Oussama Khatib, Rudiger Dillmann),  
with 6 selected papers for oral presentation, and with 7 papers  
presented during an interactive session.

Main Topics
# Object detection, tracking and classification
# Collision prediction and avoidance
# Environment perception, vehicle localization and autonomous navigation
# Real-time perception and sensor fusion
# SLAM in dynamic environments
# Real-time motion planning in dynamic environments
# 3D Modelling and reconstruction
# Human-Robot Interaction
# Behavior modeling and learning
# Robust sensor-based 3D reconstruction
# Modeling and Control of mobile robot
# Cooperation and communications (among vehicles and infrastructure)
# Multi-agent based architectures
# Cooperative unmanned vehicles (not restricted to ground transportation)

International Program Committee
# Lounis Adouane (Blaise Pascal University, France)
# Alberto Broggi (VisLab, Parma University, Italy)
# Javier Ibanez-Guzman (Renault, France)
# Christian Laugier (Emotion, INRIA, France)
# Sukhan Lee (ISRC, Sungkyunkwan University, South Korea)
# Philippe Martinet (Blaise Pascal University, France)
# Ming Lin ((University of North Carolina, USA),
# Urbano Nunes (Coimbra University, Portugal),
# Cedric Pradalier, (ETH Zurich, Switzerland)
# Cyril Stachniss (AIS, University of Freiburg, Germany)
# Ljubo Vlacic (Griffith University, Australia)

Preliminary program

Introduction /8:30-8:35/
Chairman: /Min Lin & Philippe Martinet/

Session I: Perception & Localization /8:35-10:10/
Chairman: /Alberto Broggi/

     Title: The VIAC Challenge: Setup of an Autonomous Vehicle for a
      13,000 km Intercontinental Unmanned Drive /8:35-9:20/
      Keynote speaker: Alberto Broggi (Parma University, Italy) /40min
      + 5min questions/
      Co-Authors: Massimo Bertozzi, Luca Bombini, Alberto Broggi, and
      Paolo Grisleri

      /Abstract/: Autonomous vehicles have been demonstrated to be able
      to traverse the desert (the DARPA Grand Challenge, 2005), navigate
      downtown together with other traffic (the DARPA Urban Challenge,
      2007), someone is even trying to emulate experienced drivers in
      extreme races,... In all these situations, however, the unmanned
      vehicles move within a semi-controlled environment. VisLab is now
      trying to push the unmanned vehicles technology to the limit and
      test their systems (both hardware and software) for a long time
      and in an extreme environment: on July 10, 2010, two autonomous
      vehicles will leave Italy and will drive for 13,000 km in Europe
      towards Moscow, then Russia, then Siberia, Kazakstan, then China,
      Mongolia, finally reaching Shanghai on October 10, 2010, after 3
      months of autonomous driving. As a 'challenge into the challenge,
      VisLab selected electric vehicles, with the final aim of setting a
      new milestone in the history of robotics: goods will be
      transported from Italy to China on a ground trip with no driver,
      and without using a drop of conventional fuel. Not only these
      vehicles will be moving without any human intervention, but the
      driverless technology will be powered by solar energy thanks to a
      panel on the vehicle's roof. The talk will present the current
      state of the art and the major design challenges.

     Title: Learning a Real-Time 3D Point Cloud Obstacle Discriminator
      via Bootstrapping /9:20-9:45/
      Authors: Michael Samples and Michael R. James /20min + 5min

      /Abstract/: Many recent mobile robotics applications have
      incorporated the use of 3D LIDAR sensors as an important component
      in scene understanding due to frequent data measurements and
      direct observation of geometric relationships. However, the
      sparseness of point cloud information and the lack of unique cues
      at an individual point level presents challenges in algorithm
      design for obstacle detection, segmentation, and tracking. Since
      individual measurements yield less information about the presence
      of obstacles, many algorithmic approaches model the joint
      posterior of point-labels. Such approaches can produce robust
      point labelings at higher computation cost. In this paper, we
      apply joint posterior approaches with smooth terrain priors for
      point cloud obstacle discrimination. The resulting labels are used
      to bootstrap efficient discriminators which require no human
      labeled data, yet are comparable in discriminative ability to the
      joint posterior approaches.

     Title: In Improved Flies Method for Stereo Vision: Application to
      Pedestrian Detection /9:45-10:10/
      Authors: Hao Lee, Gwenaelle Toulminet, Fawzi Nashashibi /20min +
      5min questions/

      /Abstract/: In the vast research field of intelligent
      transportation systems, the problem of detection (and recognition)
      of environment objects, for example pedestrians and vehicles, is
      indispensable but challenging. The research work presented in this
      paper is devoted to stereo-vision based method with pedestrian
      detection as its application (a sub-part of the French national
      project "LOVe": Logiciels d'Observation des  
Vulnerables). With a
      prospect of benefiting from an innovative method i.e. the genetic
      evolutionary "flies" method proposed by former researchers on
      continuous data updating and asynchronous data reading, we have
      carried on the "flies" method through the task of pedestrian
      detection affiliated with the "LOVe" project. Compared  
with former
      work of the "flies" method, two main contributions have been
      incorporated into the architecture of the "flies"  
method: first,
      an improved fitness function has been proposed instead of the
      original one; second, a technique coined  
"concentrating" has been
      integrated into the evolution procedure. The improved "flies"
      method is used to offer range information of possible objects in
      the detection field. The integrate scheme of pedestrian detection
      is presented as well. Some experimental results are given for
      validating the performance improvements brought by the improved
      "flies" method and for validating the pedestrian  
detection method
      based on the improved "flies" method.

Session II: Path Planning & Navigation systems /10:30-12:05/
Chairman: /Alexandre Bayen/

     Title: Mobile Millenium /10:30-11:15/
      Keynote speaker: Alexandre Bayen (Berkeley University, USA)
      /40min + 5min questions/

      /Abstract/: This talk describes how the mobile internet is
      changing the face of traffic monitoring at a rapid pace. In the
      last five years, cellular phone technology has bypassed several
      attempts to construct dedicated infrastructure systems to monitor
      traffic. Today, GPS equipped smartphones are progressively
      morphing into an ubiquitous traffic monitoring system, with the
      potential to provide information almost everywhere in the
      transportation network. Traffic information systems of this type
      are one of the first instantiations of participatory sensing for
      large scale cyberphysical infrastructure systems. However, while
      mobile device technology is very promising, fundamental challenges
      remain to be solved to use it to its full extent, in particular in
      the fields of modeling and data assimilation. The talk will
      present a new system, called Mobile Millennium, launched recently
      by UC Berkeley, Nokia and Navteq, in which the driving public in
      Northern California can freely download software into their GPS
      equiped smartphones, enabling them to view traffic in real time
      and become probe vehicles themselves. The smartphone data is
      collected in a privacy-by-design environment, using spatially
      aware sampling. Using data assimilation, the probe data is fused
      with existing sensor data, to provide real time estimates of
      traffic. Results from experimental deployments in California and
      New York will be presented, as well as preliminary results from a
      pilot field operational test in California, with already more than

     Title: Optimal Vehicle Routing and Scheduling with Precedence
      Constraints and Location Choice /11:15-11:40/
      Authors: G. Ayorkor Korsah, Anthony Stentz, and M. Bernardine
      Dias, and Imran Fanaswala /20min + 5min questions/

      /Abstract/: To realize the vision of intelligent transportation
      systems with fully automated vehicles, there is a need for
      highlevel planning for single vehicles as well as fleets of
      vehicles. This paper addresses the problem of optimally assigning
      and scheduling a set of spatially distributed tasks to a fleet of
      vehicles working together to achieve a high-level goal, in domains
      where tasks may be related by precedence or synchronization
      constraints and might have a choice of locations at which they can
      be performed. Such problems may arise, for example, in disaster
      preparedness planning, transportation of people, and delivery of
      supplies. We present a novel mathematical model of the problem and
      describe how it can be solved optimally in a branch-and-price

     Title: Multi-Agent Planning and Simulation for Intelligent
      Transportation System /11:40-12:05/
      Authors: Ming C. Lin, Jason Sewall, Jur Van den Berg, David
      Willkie, Dinesh Manocha /20min + 5min questions/

      /Abstract/: In this paper, we provide a brief survey of our recent
      work on multi-agent planning and simulation for intelligent
      transportation system. In particular, we first present a novel
      algorithm to reconstruct and visualize continuous traffic flows
      from discrete spatio-temporal data provided by traffic sensors.
      Given the positions of each car at two recorded locations on a
      highway and the corresponding time instances, our approach can
      reconstruct the traffic flows (i.e. the dynamic motions of
      multiple cars over time) in between the two locations along the
      highway using a priority-based multi-agent planning algorithm. Our
      algorithm is applicable to high-density traffic on highways with
      an arbitrary number of lanes and takes into account the geometric,
      kinematic, and dynamic constraints on the cars. In addition, we
      describe an efficient method for simulating realistic traffic
      flows on large-scale road networks. Our technique is based on a
      continuum PDE model of traffic flow that we extend to correctly
      handle lane changes and merges, as well as traffic behaviors due
      to changes in speed limit. We show that our method can simulate
      plausible traffic flows on publiclyavailable, real-world road data
      and demonstrate the scalability of this technique on many-core

Session III: Human Robot Interaction /13:30-14:15/

     Title: Robot for the Human /13:30-14:15/
      Keynote speaker: Oussama Khatib (Stanford University, USA)
      /40min + 5min questions/

      /Abstract/: Robotics is rapidly expanding into the human
      environment and vigorously engaged in its new emerging challenges.
      From a largely dominant industrial focus, robotics has undergone
      by the turn of the new millennium a major transformation in scope
      and dimensions. This expansion has been brought about by the
      maturity of the field and the advances in its related
      technologies. The new generation of robots is expected to safely
      and dependably co-habitat with humans in homes, workplaces, and
      communities, providing support in services, entertainment,
      education, health care, manufacturing, and assistance.
      Interacting, exploring, and working with humans, the new
      generation of robots will increasingly touch people and their
      lives. New design and fabrication concepts, novel sensing
      modalities, effective planning and control strategies, modeling
      and understanding of human motion and skills are among the key
      requirements discussed for the development of this new generation
      of human-friendly robots.

Session IV: Interactive session /14:15-15:45/
Chairman: /Ming Lin & Philippe Martinet/

     Title: Benchmark Tools for Evaluating AGVs at Industrial
      Authors: Hector Yuste, Leopoldo Armesto and Josep Tornero

      /Abstract/: The paper addresses the problem of evaluating AGVs
      with different degrees of autonomy by defining a methodology and
      benchmark tools to grade the performance of each solution. The
      proposed benchmark requires running different experiments, from
      manual driving to autonomous navigation, at different velocities
      and different scenarios. The goal is to evaluate the performance
      of AGVs, in terms of robustness to reach the goal, collisions
      reduction, traveling time, average speed, etc. The underlying
      objective is to evaluate the potential advantages of
      manual-assisted driving as well as autonomous navigation against
      standard manual driving. To obtain valid and significant results,
      180 experiments have been completed on each case with drivers of
      different ages, sex and skills.

     Title: Automatic Routing System for Intelligent Warehouses
      Authors: K. T. Vivaldini, J. P. M. Galdames, T. B. Pasqual, R. M.
      Sobral; R. C. Araújo, M. Becker, and G. A. P. Caurin

      /Abstract/: Automation of logistic processes is essential to
      improve productivity and reduce costs. In this context,
      intelligent warehouses are becoming a key to logistic systems
      thanks to their ability of optimizing transportation tasks and,
      consequently, reducing costs. This paper initially presents
      briefly routing systems applied on intelligent warehouses. Then,
      we present the approach used to develop our router system. This
      router system is able to solve traffic jams and collisions,
      generate conflict-free and optimized paths before sending the
      final paths to the robotic forklifts. It also verifies the
      progress of all tasks. When a problem occurs, the router system
      can change the tasks priorities, routes, etc. in order to avoid
      new conflicts. In the routing simulations each vehicle executes
      its tasks starting from a predefined initial pose, moving to the
      desired position. Our algorithm is based on Dijkstra's
      shortestpath and the time window approaches and it was implemented
      in C language. Computer simulation tests were used to validate the
      algorithm efficiency under different working conditions. Several
      simulations were carried out using the Player/Stage Simulator to
      test the algorithms. Thanks to the simulations, we could solve
      many faults and refine the algorithms before embedding them in
      real robots.

     Title: Coordinating the motion of multiple AGVs in automatic
      Authors: Roberto Olmi, Cristian Secchi and Cesare Fantuzzi

      /Abstract/: In this paper an algorithm for planning a coordinated
      motion of a fleet of Autonomous Guided Vehicles (AGVs) delivering
      goods in an automatic warehouse is proposed. The AGVs travel along
      a common segmented layout and a path is assigned to each robot by
      a mission planner. Coordination diagrams are used for representing
      possible collisions among the robots and a novel algorithm for
      efficiently determining a coordinated motion of the fleet is
      proposed. The coordination approach proposed in the paper is
      validated through experiments on real plants layouts. We present
      an example in which the coordinated motion of 10 vehicles is
      computed in only 12.4 sec. on a common PC.

     Title: ArosDyn: Robust Analysis of Dynamic Scenes by means of
      Bayesian Fusion of Sensor Data - Application to the Safety of Car
      Authors: Christian Laugier, Igor E. Paromtchik, Mathias Perrollaz,
      Mao Yong, Amaury Nègre, John-David Yoder, Christopher Tay

      /Abstract/: The ArosDyn project aims to develop an embedded
      software for robust analysis of dynamic scenes in urban
      environment during car driving. The software is based on Bayesian
      fusion of data from telemetric sensors (lidars) and visual sensors
      (stereo camera). The key objective is to process the dynamic
      scenes in real time to detect and track multiple moving objects,
      in order to estimate and predict risks of collision while driving.

     Title: Real-Time Detection of Moving Obstacles from Mobile
      Authors: Chunrong Yuan and Hanspeter A. Mallot

      /Abstract/: In this paper we present a vision-based algorithm for
      the detection of moving obstacles in complex and unknown
      environments. The goal is to find moving objects from images
      captured by a mobile camera navigating together with a moving
      platform. One specific feature of our approach is that it does not
      need any information of the camera and hence works without camera
      calibration. Another advantage lies in the fact that it integrates
      motion separation and outlier detection into one statistical
      framework. Based on sparse point correspondences extracted from
      consecutive frame pairs, scene points are clustered into different
      classes by statistical analysis and modeling of the probability
      distribution function of the underlying motion characteristics.
      Experimental results based on several real-world video streams
      demonstrate the efficiency of our algorithm.

     Title: Studying of WiFi range-only sensor and its application to
      localization and mapping systems
      Authors: F. Herranz, M. Ocaña, L. M. Bergasa, M. A. Sotelo, D. F.
      Llorca, N. Hernandez, A. Llamazares and C. Fernandez

      /Abstract/: The goal of this paper is to study a noisy WiFi
      range-only sensor and its application in the development of
      localization and mapping systems. Moreover, the paper shows
      several localization and mapping techniques to be compared. These
      techniques have been applied successfully with other technologies,
      like ultra-wide band (UWB), but we demonstrate that even using a
      much more noisier sensor these systems can be applied correctly.
      We use two trilateration techniques and a particle filter to
      develop the localization and mapping systems based on the
      range-only sensor. Some experimental results and conclusions are

     Title: Terrain Classification for Improving Traversability of
      Autonomous Vehicles
      Authors: Jayoung Kim, Jonghwa Lee, Jihong Lee

      /Abstract/: One of the requirements for autonomous vehicles on
      off-road is to move harmoniously in unstructured environments. It
      is an undeniable fact that such capacity of autonomous vehicles is
      the most important in an aspect considering mobility of the
      vehicle. So, many researchers use contact and/or non-contact
      methods to detect a terrain whether the vehicle can move on or
      not. In this paper we introduce an algorithm to classify terrains
      using visual information. As pre-processing, contrast enhancement
      technique is introduced to improve accurate rate of
      classification. Also, for conducting classification algorithm,
      training images are grouped as each material and Bayesian
      classification recognizes new images as each material using such
      material groups. Consequently, we can confirm the good performance
      of classification. Moreover, we can build Traversability map on
      which autonomous vehicles can predict whether to go or not to go
      through real friction coefficients which are measured by Load-Cell
      on surfaces of various terrains.

Session V: Multi-Robot Control & ITS /15:45-17:20/
Chairman: /Rüdiger Dillman /

     Title: Situation Assessment and Behaviour Decision Making of
      Cognitive Vehicles /15:45-16:30/
      Keynotes speaker: Rüdiger Dillman (Karlsruhe University,
      Germany) /40min + 5min questions/

      /Abstract/: Driving an autonomous vehicle on urban and rural
      environment requires knowledge about the situation on the road.
      Knowledge about the intension of other vehicles and inividuals on
      the road is required in order to classify the situation and to
      decide how to behave and to react. This paper addresses the
      problem of extracting information about the situative traffic
      environment of a vehicle from ist sensorial observations, its
      interpretation referencing situative knowledge and an estimation
      of it?s further behaviour. This estimation requires understanding
      the intension of the other vehicles or agents and a predictive
      view of further traffic state evolvement. Because of uncomplete
      observation and uncertainties the estimation and sensor fusion
      process has an important role. With the help of learning methods
      in terms of learning from example the vehicle will be able to
      learn from ist observations which allows the estimation of
      dangerous situations and a predictive view of its environment
      which allows the continuation of driving. Furthermore it is
      necessary to make according the actual situation and drive
      intension behavioural decisions considering it?s effects and
      results. Also here uncertainty has to be considered to enable
      predictive driving. A predictive behavioural decision process in
      combination with a learning process will be presented which allows
      to enhance the decision performance. A dynamic risk map is used to
      support algorithms for motion planning of the vehicle. Finally the
      vehicle should be able to execute maneuvers such as passing a
      crossing, lane changing, collision avoidance, overtaking and
      turning off, processing information about the actual situation and
      a prediction how it may evolve. The work to be reported is part of
      the collaborative research center SFB/TR 28 Cognitive Automobile
      which is sponsored by the German Research Agency DFG.

     Title: A global decentralized control strategy for urban vehicle
      platooning relying solely on monocular vision /16:30-16:55/
      Authors: Pierre Avanzini, Benoit Thuilot, Eric Royer, Philippe
      Martinet /20min + 5min questions/

      /Abstract/: Automated electric vehicles available in free access
      constitute a promising very efficient and environment-friendly
      "urban transportation system". An additional functionality that
      could enhance this transportation service is vehicle platooning.
      In order to avoid oscillations within the platoon when completing
      this task, a global control strategy, supported by inter-vehicle
      communications, is investigated. Vehicle absolute localization is
      then needed and is here derived from monocular vision. These data
      are however expressed in a virtual vision world, slightly
      distorted with respect to the actual metric one. It is shown that
      such a distortion can accurately be corrected by designing a
      nonlinear observer relying on odometric data. A global
      decentralized control strategy, relying on exact linearization
      techniques, can then be designed to achieve accurate vehicle
      platooning. Simulations and full-scale experiments demonstrate the
      performance of the proposed approach.

     Title: Lyapunov Global Stability for a Reactive Mobile Robot
      Navigation in Presence of Obstacles /16:55-17:20/
      Authors: Ahmed Benzerrouk, Lounis Adouane, Philippe Martinet/
      20min + 5min questions/

      /Abstract/: This paper deals with the navigation of a mobile robot
      in unknown environment. The robot has to reach a final target
      while avoiding obstacles. It is proposed to break the task
      complexity by dividing it into a set of basic tasks: Attraction to
      a target and obstacle avoidance. Each basic task is accomplished
      through the corresponding elementary controller. The activation of
      one controller for another is done according to the priority task.
      To ensure the overall stability of the control system, especially
      at the switch moments, properties of hybrid systems are used.
      Hybrid systems allow switching between continuous states in
      presence of discrete events. In this paper, it is proposed to act
      on the gain of the proposed control law. The aim is to ensure the
      convergence of a common Lyapunov function to all the controllers.
      This ensures the stability of the overall control. Simulation
      results confirm the theoretical study.

Closing /17:20-17:30/
Chairman: /Min Lin & Philippe Martinet/

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