1. Ryan Wegner. Balancing Robotic Teleoperation and Autonomy in a Complex and Dynamic Environment. Master's thesis, Department of Computer Science, University of Manitoba, July 2003.
   

   @mastersthesis{ryanthesis,
   author = {Ryan Wegner},
   title = {Balancing Robotic Teleoperation and Autonomy in a Complex and Dynamic Environment},
   school = {Department of Computer Science, University of Manitoba},
   year = {2003},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/ryanthesis.pdf},
   month = {July} 
   }
   




2. Alfred Wurr. Robotic Team Navigation in Complex Environments Using Stigmergic Cues. Master's thesis, Department of Computer Science, University of Manitoba, Winnipeg, MB, July 2003.
   

   @mastersthesis{alfthesis,
   author = {Alfred Wurr},
   title = {Robotic Team Navigation in Complex Environments Using Stigmergic Cues},
   school = {Department of Computer Science, University of Manitoba},
   year = {2003},
   month = {July},
   address = {Winnipeg, MB},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/alfthesis.pdf} 
   }
   

1. Jacky Baltes. Camera Interface. In Thomas Bräunl, editor, Embedded Robotics: Mobile Robot Design and Applications with Embedded Systems, chapter 8.1. Springer-Verlag New York, Inc., Heidelberg, Germany, 2003.
   

   @incollection{braunl03:_embed_robot,
   author = {Jacky Baltes},
   title = {Camera Interface},
   editor = {Thomas Br\&\#228;unl},
   booktitle = {Embedded Robotics: Mobile Robot Design and Applications with Embedded Systems},
   chapter = {8.1},
   year = {2003},
   isbn = {3540343180},
   publisher = {Springer-Verlag New York, Inc.},
   address = {Heidelberg, Germany} 
   }
   

1. John Anderson, Jacky Baltes, Doug Cornelson, Terry Liu, Clint Stuart, and Adam Zilkie. The Little Black Devils. In Daniel Polani, Brett Browning, Andrea Bonarini, and Kazuo Yoshida, editors, The Seventh RoboCup Competitions and Conferences, Padova, Italy, July 2003.
   

   @inproceedings{anderson03:_littl_black_devil,
   author = {John Anderson and Jacky Baltes and Doug Cornelson and Terry Liu and Clint Stuart and Adam Zilkie},
   title = {The Little Black Devils},
   booktitle = {The Seventh RoboCup Competitions and Conferences},
   year = 2003,
   editor = {Daniel Polani and Brett Browning and Andrea Bonarini and Kazuo Yoshida},
   address = {Padova, Italy},
   month = {July} 
   }
   




2. John Anderson, Jacky Baltes, Doug Cornelson, Terry Liu, Clint Stuart, and Adam Zilkie. The University of Manitoba ULeague Team. In Daniel Polani, Brett Browning, Andrea Bonarini, and Kazuo Yoshida, editors, The Seventh RoboCup Competitions and Conferences, Padova, Italy, July 2003.
   

   @inproceedings{anderson03:_univer_manit_uleag_team,
   author = {John Anderson and Jacky Baltes and Doug Cornelson and Terry Liu and Clint Stuart and Adam Zilkie},
   title = {The University of Manitoba ULeague Team},
   booktitle = {The Seventh RoboCup Competitions and Conferences},
   year = 2003,
   editor = {Daniel Polani and Brett Browning and Andrea Bonarini and Kazuo Yoshida},
   address = {Padova, Italy},
   month = {July} 
   }
   




3. John Anderson, Jacky Baltes, and Jay Kraut. The Keystone Rescue Team. In Daniel Polani, Brett Browning, Andrea Bonarini, and Kazuo Yoshida, editors, The Seventh RoboCup Competitions and Conferences, Padova, Italy, July 2003.
   

   @inproceedings{anderson03:_keyst_rescue_team,
   author = {John Anderson and Jacky Baltes and Jay Kraut},
   title = {The Keystone Rescue Team},
   booktitle = {The Seventh RoboCup Competitions and Conferences},
   editor = {Daniel Polani and Brett Browning and Andrea Bonarini and Kazuo Yoshida},
   year = 2003,
   address = {Padova, Italy},
   month = {July} 
   }
   




4. John Anderson, Jacky Baltes, David Livingston, and Elizabeth Sklar. Toward an Undergraduate League for RoboCup. In Daniel Polani, Brett Browning, Andrea Bonarini, and Kazuo Yoshida, editors, The Seventh RoboCup Competitions and Conferences, Padova, Italy, 2003.
   

   @inproceedings{anderson03:_towar_under_league_roboc,
   author = {John Anderson and Jacky Baltes and David Livingston and Elizabeth Sklar},
   title = {Toward an Undergraduate League for RoboCup},
   booktitle = {The Seventh RoboCup Competitions and Conferences},
   editor = {Daniel Polani and Brett Browning and Andrea Bonarini and Kazuo Yoshida},
   year = 2003,
   address = {Padova, Italy} 
   }
   




5. Jacky Baltes and John Anderson. Flexible Binary Space Partitioning for Robotic Rescue. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, pages 3144-3149, October 2003. [Slides] Abstract:

   In domains such as robotic rescue, robots must plan paths through environments that are complex and dynamic, and in which robots have only incomplete knowledge. This will normally require both diversions from planned paths as well as significant re-planning as events in the domain unfold and new information is acquired. In terms of a representation for path planning, these requirements place significant demands on efficiency and flexibility. This paper describes a method for flexible binary space partitioning designed to serve as a basis for path planning in uncertain dynamic domains such as robotic rescue. This approach is used in the 2003 version of the \kfb\, a robotic rescue team. We describe the algorithm used, make comparisons to related approaches to path planning, and provide an empirical evaluation of an implementation of this approach.

   
   

   @inproceedings{baltes03:_flexib_binar_space_partit_robot_rescue,
   author = {Jacky Baltes and John Anderson},
   title = {Flexible Binary Space Partitioning for Robotic Rescue},
   booktitle = {Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
   year = 2003,
   address = {Las Vegas},
   month = {October},
   pages = {3144-3149},
   abstract = {In domains such as robotic rescue, robots must plan paths through environments that are complex and dynamic, and in which robots have only incomplete knowledge. This will normally require both diversions from planned paths as well as significant re-planning as events in the domain unfold and new information is acquired. In terms of a representation for path planning, these requirements place significant demands on efficiency and flexibility. This paper describes a method for flexible binary space partitioning designed to serve as a basis for path planning in uncertain dynamic domains such as robotic rescue. This approach is used in the 2003 version of the \kfb\, a robotic rescue team. We describe the algorithm used, make comparisons to related approaches to path planning, and provide an empirical evaluation of an implementation of this approach.},
   pdf = {http://aalab.cs.umanitoba.ca/%7ejacky/Publications/pdf/baltes03:_flexib_binar_space_partit_robot_rescue.pdf},
   slides = {http://aalab.cs.umanitoba.ca/%7ejacky/Publications/pdf/baltes03:_flexib_binar_space_partit_robot_rescue_slides.pdf} 
   }
   




6. Jacky Baltes and John Anderson. Identifying Robots Through Behavioral Analysis. In Proceedings of the Second International Conference on Computational Intelligence, Robotics, and Autonomous Systems, Singapore, 2003. Annotation:

   Identifying the location and orientation of robots is a significant problem in vision for robotic soccer. Previous approaches use some type of identifying marker system (coloured spots, arrangements of bars) in order to facilitate fast visual identification of individual robots. However, these methods do not scale well to larger teams and require considerable calibration effort. This paper describes an approach that does not require such markers. Instead, the movement history as well and command history are used to identity the robot by employing Bayesian techniques to correlate the commands sent to the robot with the robot's actions in the environment. This approach is implemented in the latest version of our global video server, \Doraemon.

   
   

   @inproceedings{baltes03:_ident_robot_throug_behav_analy,
   author = {Jacky Baltes and John Anderson},
   title = {Identifying Robots Through Behavioral Analysis},
   booktitle = {Proceedings of the Second International Conference on Computational Intelligence, Robotics, and Autonomous Systems},
   year = 2003,
   address = {Singapore},
   annote = {Identifying the location and orientation of robots is a significant problem in vision for robotic soccer. Previous approaches use some type of identifying marker system (coloured spots, arrangements of bars) in order to facilitate fast visual identification of individual robots. However, these methods do not scale well to larger teams and require considerable calibration effort. This paper describes an approach that does not require such markers. Instead, the movement history as well and command history are used to identity the robot by employing Bayesian techniques to correlate the commands sent to the robot with the robot's actions in the environment. This approach is implemented in the latest version of our global video server, \Doraemon.} 
   }
   




7. Jacky Baltes and John Anderson. Learning Orientation Information for Robotic Soccer Using Neural Nets. In Proceedings of the FIRA World Congress, Vienna, Austria, October 2003. Annotation:

   Robotic soccer teams using both local and global vision traditionally rely on a set of pre-determined markers (e.g., a group of small colored circles mounted on the top surface of the robot) to provide easy targets for visual analysis in order to determine the team membership, identity, and orientation of robots in the visual field. This approach requires calibration before any competition, as well as agreement in advance on color codes different enough between teams to avoid recognition errors at run-time. Even after extensive calibration, small lighting variations can cause extensive misidentification. In this paper, we examine an alternative approach: training a neural network to recognize the orientation of the robots on a team so that visual tracking can occur in real time without special markers of any kind. This paper describes the design and implementation of such an approach, and shows the results of an empirical evaluation of this approach.

   
   

   @inproceedings{baltes03:_learn_orien_infor_robot_soccer,
   author = {Jacky Baltes and John Anderson},
   title = {Learning Orientation Information for Robotic Soccer Using Neural Nets},
   booktitle = {Proceedings of the FIRA World Congress},
   year = 2003,
   address = {Vienna, Austria},
   month = {October},
   annote = {Robotic soccer teams using both local and global vision traditionally rely on a set of pre-determined markers (e.g., a group of small colored circles mounted on the top surface of the robot) to provide easy targets for visual analysis in order to determine the team membership, identity, and orientation of robots in the visual field. This approach requires calibration before any competition, as well as agreement in advance on color codes different enough between teams to avoid recognition errors at run-time. Even after extensive calibration, small lighting variations can cause extensive misidentification. In this paper, we examine an alternative approach: training a neural network to recognize the orientation of the robots on a team so that visual tracking can occur in real time without special markers of any kind. This paper describes the design and implementation of such an approach, and shows the results of an empirical evaluation of this approach.} 
   }
   




8. Jacky Baltes and John Anderson. The Keystone Rescue Robotic Rescue Team. In Proceedings of the IJCAI Robotics Workshop, 2003.
   

   @inproceedings{baltes03:_keyst_rescue,
   author = {Jacky Baltes and John Anderson},
   title = {The Keystone Rescue Robotic Rescue Team},
   booktitle = {Proceedings of the IJCAI Robotics Workshop},
   year = 2003 
   }
   




9. Jacky Baltes and Patrick Lam. Walking Gaits for a Small Humanoid Robot. In Daniel Polani, Brett Browning, Andrea Bonarini, and Kazuo Yoshida, editors, The Seventh RoboCup Competitions and Conferences, Padova, Italy, 2003.
   

   @inproceedings{baltes03:_walkin_gaits_small_human_robot,
   author = {Jacky Baltes and Patrick Lam},
   title = {Walking Gaits for a Small Humanoid Robot},
   booktitle = {The Seventh RoboCup Competitions and Conferences},
   editor = {Daniel Polani and Brett Browning and Andrea Bonarini and Kazuo Yoshida},
   year = 2003,
   address = {Padova, Italy} 
   }
   




10. Jacky Baltes and Sara McGrath. Tao-Pie-Pie. In Daniel Polani, Brett Browning, Andrea Bonarini, and Kazuo Yoshida, editors, The Seventh RoboCup Competitions and Conferences, Padova, Italy, July 2003.
    

    @inproceedings{baltes03:_tao_pie_pie,
    author = {Jacky Baltes and Sara McGrath},
    title = {Tao-Pie-Pie},
    booktitle = {The Seventh RoboCup Competitions and Conferences},
    year = 2003,
    editor = {Daniel Polani and Brett Browning and Andrea Bonarini and Kazuo Yoshida},
    address = {Padova, Italy},
    month = {July} 
    }
    




11. Jacky Baltes, Sara McGrath, and John Anderson. Feedback Control of Walking for a Small Humanoid Robot. In Proceedings of the FIRA World Congress, Vienna, Austria, October 2003. Annotation:

    This paper describes methods used in stabilizing the walking gait of Tao-Pie-Pie, a small humanoid robot given rate feedback from two RC gyroscopes. Tao-Pie-Pie is a fully autonomous small humanoid robot (30cm tall). Although Tao-Pie-Pie uses a minimal set of actuators and sensors, it has proven itself in international competitions, winning honors at the RoboCup\ and HuroSot\ competitions in 2002 and 2003. The feedback control law is based solely on the rate information from two RC gyroscopes. This alleviates drift problems introduced by integrating the RC gyroscope feedback in the more common position control approaches.

    
    

    @inproceedings{baltes03:_feedb_contr_walkin_small_human_robot,
    author = {Jacky Baltes and Sara McGrath and John Anderson},
    title = {Feedback Control of Walking for a Small Humanoid Robot},
    booktitle = {Proceedings of the FIRA World Congress},
    year = 2003,
    address = {Vienna, Austria},
    month = {October},
    annote = {This paper describes methods used in stabilizing the walking gait of Tao-Pie-Pie, a small humanoid robot given rate feedback from two RC gyroscopes. Tao-Pie-Pie is a fully autonomous small humanoid robot (30cm tall). Although Tao-Pie-Pie uses a minimal set of actuators and sensors, it has proven itself in international competitions, winning honors at the RoboCup\ and HuroSot\ competitions in 2002 and 2003. The feedback control law is based solely on the rate information from two RC gyroscopes. This alleviates drift problems introduced by integrating the RC gyroscope feedback in the more common position control approaches.} 
    }
    




12. Jacky Baltes, Sara McGrath, and John Anderson. Stabilizing Walking Gaits Using Feedback From Gyroscopes. In Proceedings of the Second International Conference on Computational Intelligence, Robotics, and Autonomous Systems, 2003. Annotation:

    This paper describes methods used in stabilizing the walking gait of Tao-Pie-Pie, a small humanoid robot given rate feedback from two RC gyroscopes. Tao-Pie-Pie is a fully autonomous small humanoid robot (30cm tall). Although Tao-Pie-Pie uses a minimal set of actuators and sensors, it has proven itself in international competitions, winning honors at the RoboCup and HuroSot competitions in 2002 and 2003. The feedback control law is based solely on the rate information from two RC gyroscopes. This alleviates drift problems introduced by integrating the RC gyroscope feedback in the more common position control approaches.

    
    

    @inproceedings{baltes03:_stabil_walkin_gaits_using_feedb_from_gyros,
    author = {Jacky Baltes and Sara McGrath and John Anderson},
    title = {Stabilizing Walking Gaits Using Feedback From Gyroscopes},
    booktitle = {Proceedings of the Second International Conference on Computational Intelligence, Robotics, and Autonomous Systems},
    year = 2003,
    annote = {This paper describes methods used in stabilizing the walking gait of Tao-Pie-Pie, a small humanoid robot given rate feedback from two RC gyroscopes. Tao-Pie-Pie is a fully autonomous small humanoid robot (30cm tall). Although Tao-Pie-Pie uses a minimal set of actuators and sensors, it has proven itself in international competitions, winning honors at the RoboCup and HuroSot competitions in 2002 and 2003. The feedback control law is based solely on the rate information from two RC gyroscopes. This alleviates drift problems introduced by integrating the RC gyroscope feedback in the more common position control approaches.} 
    }
    




13. Byung-Doo Lee, Hans Werner Guesgen, and Jacky Baltes. The Application of TD(l) Learning to the Opening Games of Go. In Proceedings of the Fifth International Conference on Advances in Pattern Recognition, Calcutta, India, 2003.
    

    @inproceedings{lee03:_applic_td_learn_openin_games_go,
    author = {Byung-Doo Lee and Hans Werner Guesgen and Jacky Baltes},
    title = {The Application of TD(l) Learning to the Opening Games of Go},
    booktitle = {Proceedings of the Fifth International Conference on Advances in Pattern Recognition},
    year = 2003,
    address = {Calcutta, India} 
    }
    




14. Ryan Wegner, John Anderson, and Jacky Baltes. Blending Autonomy and Teleoperation for Intelligent Control of Multiple Mobile Robots in Urban Search and Rescue Environments. In Proceedings of the FIRA World Congress, Vienna, Austria, October 2003.
    

    @inproceedings{wegner03:_blend_auton_teleop_intel_contr,
    author = {Ryan Wegner and John Anderson and Jacky Baltes},
    title = {Blending Autonomy and Teleoperation for Intelligent Control of Multiple Mobile Robots in Urban Search and Rescue Environments},
    booktitle = {Proceedings of the FIRA World Congress},
    year = 2003,
    address = {Vienna, Austria},
    month = {October} 
    }
    

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