Information on the group as a whole is available in the Mobile Robotics Group home page.

• Interest Operators
  

  Sandra Polifroni , Frank Ferrie, Greg Dudek

  We are interested in the use of computation interest operators (attention operators) for image recognition and memorization tasks, both in the context of computer vision and human preattentive vision. This work uses both psychophysics and computer science to qualitatively evaluate the performance of interest operators in image recall.
  
  

  ---

  
  
  
• Optimal Spiral Search
  

  Scott Burlington , G. Dudek

  This project involves the application of spiral search techniques to mobile robot navigation, and multi-agent coordination. If you are stuck in a long dark hallway and need to find the light switch as quickly as you can you should probably choose your turning points according to f(i), where m=2 and i is the number of turns. This scales to planar surfaces and has many synchonization issues when applied to more than one searcher. Here is a brief summary of some of his early work as presented to the CS 765 class.
  
  

  ---

  
  
  
• PCA analysis invariant to backgrounds
  

  Deeptiman Jugessur, G. Dudek

  Appearance based recognition using Principal Components Analysis with the added ability to account for varying backgrounds. This is done using an attention operator to focus on the object to be recognised and performing PCA only on the sub-windows within the object.
  
  Representative publications:
  
  • D. Jugessur and G. Dudek "Local Appearance for Robust Object Recognition" IEEE Computer Vision and Pattern Recognition (CVPR) June 2000. [gzipped postscript or pdf]
  • G. Dudek and D. Jugessur "Robust Place Recognition using Local Appearance based Methods" IEEE International Conference on Robotics and Automation (ICRA) April 2000. [ps.gz or pdf]
  
  
  

  ---

  
  
  

• Richard Unger , G. Dudek

  This project involves the development of a gestural interface to the Sony robotic dog (referred to as AIBO). The emphasis of the project is on systems integration and the encoding of complex actions via a simple gestural interface.
  
  

  ---

  
  
  
• Real-time recognition and collision avoidance.
  

  Francois Belair, Eric Bourque, Robert Sim, Phil Ciaravola, Yiannis Rekleitis, Gregory Dudek.

  Several members of the mobile robotics group are assembling components of our software infrastructure into a real-time mobile robotics testbed. A version of this testbed was employed to win an event in the AAAI 97 mobile robotics competition. An abstract of some of the objectives are described in: Autonomous Exploration: An Integrated Systems Approach published in the AAAI-97 Proceedings, AAAI/MIT Press, pp.779-780.
  

  Postscript version here

  
  

  ---

  
  
• Distributed Robot Control Software Environment
  

  G. Dudek

  A Distributed, device independent mobile robot controller and simulator. It supports distributed computation and visualization and can control one or more real Nomad or RWI robots. Some additional details and a picture are available.




---



• Defining Islands of Reliability for Exploration and Hybrid Topological-Metric Map Construction
  

  S. Simhon, G. Dudek

  We are interested in the definition and detection of landmarks and local reference frames in a large-scale environment. We are examining automatic methods for generation coupled navigation and sensing algorithms that are generalize across specific sensing technologies such as vision and sonar.
  These landmarks and reference frames are used to construct a hybrid topological metric map. The representation consists of local metric maps connected together to form a graph. Each local map is considered a node in the graph and the edges of the graph qualitatively describe the hierarchy and relationship of neighbouring nodes. The work is inspired by biological environment perception. MORE




---

• Virtual Environment Construction
  

  Eric Bourque, Philippe Ciaravola , G. Dudek

  We are examining techniques for the creation and management of virtual reality analogues for the real world. This includes the automatic acquisition of image-based VR images, as well as the automated selection of viewpoints and scenes of interest. Further information on the image acquisition system is available here. A preliminary paper on the image selection process is available in html form as well a in postscript.
  
  

  ---

• Accurate Position Estimation from Visual Landmarks
  

  Robert Sim (simra@cim.mcgill.ca), Gregory Dudek (dudek@cim.mcgill.ca)

  Methods for learning, encoding, detecting, and using visual landmarks for mobile robot pose estimation. A recent paper is

     Position Estimation Using Principal Components of Range Data
     Robert Sim and Gregory Dudek,
     Proc. IEEE/RSJ Conf. on Intelligent Robots and Systems (IROS),
     Victoria, B.C., October 1998.
  

  and a postscript copy is available here.
  
  

  ---

• Environment Shape and Layout from Active Shadows
  

  M. Langer (NEC), M. Daum, G. Dudek, S. W. Zucker

  This project deals with the inference of environmental structure from shadow information. Click here for an abstract
  
  

  ---

• Multi-Robot Exploration and Rendezvous
  

  N. Roy (now at CMU), I. Rekleitis, G. Dudek.

  This project deals with the exploration of an unknown environment using two or more robots working together. Key aspects of the problems coordination, and particularly rendezvous, between the robots, and efficient decomposition of the exploration task.

  Click here more more information on the rendezvous work, specifically. One of the first papers on our rendezvous work was:

    Roy, Nicholas,  Dudek, Gregory,
    ``Learning to Rendezvous during Multi-agent Exploration'',
    Proc. of the Sixth European Workshop on Learning Robots (EWLR-6)},
    Aug. 1997, Brighton, UK. 
  

  A postscript of this paper is also available.
  Some of the exploration work assumes tight coupleing between robots and looks at issues of (geometric) complexity. You can download a compressed postscript copy of one of the publications on the multi-robot exploration work that appeared at IJCAI 1997:

      @InProceedings{Rekleitis:97b,
  	author = {Ioannis Rekleitis, and Gregory Dudek, and Evangelos Milios},
  	title = {Multi-Robot Exploration of an Unknown Environment, 
  		 Efficiently Reducing the Odometry Error},
  	booktitle = {International Joint Conference in Artificial Intelligence},
  	editor = {IJCAI},
  	volume = 2,
  	year = 1997,
  	publisher = {Morgan Kaufmann Publishers, Inc. },
  	address = {Nagoya, Japan},
  	month = {August},
  	pages = {1340-1345}
  	}
  

  
  

  ---

• Object description and recognition
  

  G. Dudek, Nigel Ayoung-Chee, Frank Ferrie

  This project involves shape modelling based on a combination of local curvature information at multiple scale, and global superquadric surface fitting. Click here for abstract
  
  

  ---

• Mobile Robot Exploration by using Fused Data from Two Sensors
  

  Yiannis Rekleitis, G. Dudek, P. Freedman

  This research investigates the combined use of a sonar range finder and a laser range finder (QUADRIS or BIRIS) for exploring a structured indoor environment. The methodology is called "just-in-time" sensing. A longer abstract is also available. as well as a paper in gzipped postscript form:

  @InProceedings{Dudek:96a,
         author = "Gregory Dudek, and Paul Freedman and Ioannis M. Rekleitis",
         title = "Just-in-time sensing: 
                  efficiently combining sonar and laser range data 
                  for exploring unknown worlds",
         volume = "1",
         pages = "667-671",
         booktitle = "International Conference in Robotics and Automation",
         year = 1996,
         organization = "IEEE",
         month = "April"
         } 
  

  
  

  ---

• Localizing a Robot with Minimum Travel
  

  Gregory Dudek (dudek@cim.mcgill.ca), Kathleen Romanik (romanik@dimacs.rutgers.edu), Sue Whitesides (sue@cs.mcgill.ca)

  Click here for abstract
  
  

  ---

• Multi-Robot Collaboration
  

  G. Dudek in collaboration with Professors E. Milios and M. Jenkin of York U. and D. Wilkes at Ontario Hydro

  We are interested in elaborating a taxonomy for systems of multiple mobile robots. The specific issues we are foc using on are the relationships between inter-robot communication, sensing, and coordination of behaviour in the context of position estimation and exploration. A short paper describing a trial experiment in this context is available in postscript form.
  
  

  ---

• Mapping using weak information
  

  G. Dudek in collaboration with Professors E. Milios and M. Jenkin of York U. and D. Wilkes at Ontario Hydro

  Autonomous navigation using sensory information often depends on a usable map of the environment. This work deals with the automatic creation of such a maps by an autonomous agent and the minimal requirements such a map must satisfy in order to be useful. One aspect of this work is the analysis of how uncertainty either in the map or in sensing devices relates to the reliability and cost of navigation and and path planning. Another aspect is the development of sensing strategies and behaviours that facilitate reliable self-location and map construction.
  
  

  ---

• Probabilistic sonar understanding
  

  Simon Lacroix, Grogory Dudek

• Pose Estimation From Image Data Without Explicit Object Models
  

  G. Dudek, Chi Zhang

  We consider the problem of locating a robot in an initially-unfamiliar environment from visual input. The robot is not given a map of the environment, but it does have access to a limited set of training examples each of which specifies the video image observed when the robot is at a particular location and orientation. Such data might be acquired using dead reckoning the first time the robot entered an unfamiliar region (using some simple mechanism such as sonar to avoid collisions). In this paper, we address a specific variant of this problem for experimental and expository purposes: how to estimate a robot's orientation(pan and tilt) from sensor data.

  Performing the requisite scene reconstruction needed to construct a metric map of the environment using only video images is difficult. We avoid this by using an approach in which the robot learns to convert a set of image measurements into a representation of its pose (position and orientation). This provides a {\em local} metric description of the robot's relationship to a portion of a larger environment. A large-scale map might then be constructed from a collection of such local maps. In the case of our experiment, these maps express the statistical relationship between the image measurements and camera pose. The conversion from visual data to camera pose is implemented using multi-layer neural network that is trained using backpropagation. For extended environments, a separate network can be trained for each local region. The experimental data reported in this paper for orientation information (pan and tilt) suggests the accuracy of the technique is good while the on-line computational cost is very low.

  Related work is taking place in the context of the IRIS project (below). A recent article appears in Neural COmputation and the abstract is available here.

• Spatial abstraction and mapping
  

  P. Mackenzie, G. Dudek

  This project involves the development of a formalism and methodology for making the transition from raw noisy sensor data collected by a roving robot to a map composed of object models and finally to a simple abstract map described in terms of discrete places of interest. An important early stage of such processing is the ability to select, represent and find a discrete set of places of interest or landmarks that will make up a map. Associated problems are those of using a map to accurately localize a mobile robot and generating intelligent exploration plans to verify and elaborate the map. Click here for a compressed postscript copy of a paper on this work.

• Spatial Mapping with Uncertain Data
  

  G. Dudek

  As a sensor-based mobile robot explores an unknown environment it collects percepts about the world it is in. These percepts may be ambiguous individually but as a collection they provide strong constraints on the topology of the environment. Appropriate exploration strategies and representations allow a limited set of possible world models to be considered as maps of the environment. The structure of the real world and the exploration method used specify the reliability of the final map and the computational and perceptual complexity of constructing it. Computational tools we are using range from graph-theoretic to connectionist.

• Human object recognition and shape integration
  

  Gregory Dudek, Daniel Bub: Neurolinguistics, Montreal Neurological Inst., Martin Arguin: Phychology Dept., University of Montreal

  Computational vision is defined, to a large extent, with reference to the visual abilities of humans. In this project we are examining the relationship between the characteristics of object shape and the abilities of humans to recognize these shapes. This includes the modelling of subjects with object recognition deficits due to brain damage as well as normal subjects. Click here for a compressed postscript copy of a recent paper on this work.

• Dynamic reasoning, navigation and sensing for mobile robots
  IRIS Project IS-5
  

  Martin D. Levine, Peter Caines, Renato DeMori, Gregory Dudek, Paul Freedman (CRIM), Geoffrey Hinton (University of Toronto)

  The goal of this project is to develop both the theoretical basis and practical instantiation of a mobile robotic system will be able to reason about tasks, recognize objects in its environment, map its environment, understand voice commands, and navigate through the environment and perform the specified search tasks. This will be achieved in a dynamic environment, in that knowledge of a (possibly changing) world may be updated, and the tasks themselves may be radically altered during the system's operation. Core research areas involved include perceptual modelling, control theory, neural networks, graph theory, attentive control of processing and speech understanding. Among the key capabilities indended as outcomes of this project are:
  • Integrated low (eg, points and lines) and high level (eg. places and rooms) descriptions of the environment.
  • Ability to deal with a changing environment.
  • Ability to reason about multiple tasks and the changing environment.
  • Ability to learn about the environment and the sensor characteristics.
  • Ability to accept high level verbal commands (with a limited lexicon and
  syntax) similar to those employed by humans (based on psychological data) and translate them into control actions for the robot and sensors.

• Natural language referring expressions in a person/machine dialogue.
  

  G. Dudek, R. DeMori, C. Pateras

  Click here for abstract

• Reliable Vehicle Trajectory Planning
  

  G. Dudek, Chi Zhang

  We are using a hybrid method for vehicle path planning that guarantees globally acceptable solutions yet has limit time and space complexity. This depends on a combination of variational methods with other approaches.

• Enhanced reality for mobile robotics
  

  Kadima Lonji, G. Dudek

  This project involves the use of a synthetic scene model for teleoperation or pose estimation. Live video and synthetic model information is fused to produce a composite image.

• Multi-sensor fusion for mobile robotics
  

  MRL group members

  Click here for abstract (with picture)

• A FLEXIBLE BEHAVIORAL ARCHITECTURE FOR MOBILE ROBOT NAVIGATION
  

  J. Zelek, M. D. Levine

  The intention of this study is to design an architecture that allows the behavioral control strategy that is flexible, generalizable, and extendable. The component dedicated to behavioral activities should be able to attempt tasks with or without a reasoning module. We are investigating 2D navigational tasks for a mobile robot possessing sonar sensors and a controllable TV camera mounted on a pan-tilt head. The major aspects of our proposed behavioral architecture are as follows: - A natural language lexicon is used to represent spatial information and for defining task commands. The lexicon is used as a language for internal communications and user-specified commands. The task is to go to a location in space, either known or determined by locating a specific object. - An extension of a formalism, referred to as teleo-reactive (T-R) programs (Nilsson:94), is used for specifying behavioral control. The extensions of this approach involve dealing with real-time resource limitations and constraints.