1. Nathan Wiebe. Developing Grounded Communication in Multi-Agent Systems. Master's thesis, Department of Computer Science, University of Manitoba, Winnipeg, MB, January 2006. Abstract:

   For a mobile robot to be able to communicate usefully with others, the symbols it uses to communicate must be associated with (grounded to) physical entities in the environment. While it is common practice to hand-construct such groundings, this does not scale to large problems. In particular, when communicating about useful locations in the environment, there are a large number of potential groundings, even for a relatively simple task such as navigation. The research goal of this thesis was to design, implement, and evaluate an approach that allows a group of robotic agents to develop consistent shared groundings for locations in an environment over time. The approach was implemented in a multi-agent robot simulator and experiments were run in domains of varying size and complexity, and with different robot populations. A number of parameters involved in developing shared groundings were also varied. The results of these experiments illustrate that not only can such shared groundings be developed over time, but that these groundings will improve the effectiveness of communication and ultimately the performance of tasks that require communication.

   
   

   @mastersthesis{nathanthesis,
   author = {Nathan Wiebe},
   title = {Developing Grounded Communication in Multi-Agent Systems},
   school = {Department of Computer Science, University of Manitoba},
   year = {2006},
   month = {January},
   address = {Winnipeg, MB},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/nathanwiebemsc.pdf},
   abstract = {For a mobile robot to be able to communicate usefully with others, the symbols it uses to communicate must be associated with (grounded to) physical entities in the environment. While it is common practice to hand-construct such groundings, this does not scale to large problems. In particular, when communicating about useful locations in the environment, there are a large number of potential groundings, even for a relatively simple task such as navigation. The research goal of this thesis was to design, implement, and evaluate an approach that allows a group of robotic agents to develop consistent shared groundings for locations in an environment over time. The approach was implemented in a multi-agent robot simulator and experiments were run in domains of varying size and complexity, and with different robot populations. A number of parameters involved in developing shared groundings were also varied. The results of these experiments illustrate that not only can such shared groundings be developed over time, but that these groundings will improve the effectiveness of communication and ultimately the performance of tasks that require communication.} 
   }
   

1. Alfred Wurr and John Anderson. Stigmergic Navigation for Multi-Agent Teams in Complex Environments. In Crina Grosan Ajith Abraham and Vitorino Ramos, editors, Stigmergic Optimization, chapter 4, pages 85-116. Springer-Verlag, Berlin, 2006. Abstract:

   Robotic agents in dynamic environments must sometimes navigate using only their local perceptions. In complex environments, features such as terrain undulation, geometrically complex barriers, and similar obstacles form local maxima and minima that can trap and hinder agents using reactive navigation. Moreover, agents navigating in a purely reactive fashion forget their past discoveries quickly. Preserving this knowledge usually requires that each agent construct a detailed world model as it explores or be forced to rediscover desired goals each time. Explicit communication can also be required to share discoveries and coordinate actions. The cost of explicit communication can be substantial, however, making it desirable to avoid its use in many domains. Accordingly, in this paper we present a method of cooperative trail making that allows a team of agents using reactive navigation to assist one another in their explorations through implicit (stigmergic) communication.

   
   

   @incollection{WurrAnderson06:StigChapter,
   author = {Alfred Wurr and John Anderson},
   title = {Stigmergic Navigation for Multi-Agent Teams in Complex Environments},
   booktitle = {Stigmergic Optimization},
   publisher = {Springer-Verlag},
   year = {2006},
   editor = {Ajith Abraham, Crina Grosan and Vitorino Ramos},
   chapter = {4},
   pages = {85--116},
   address = {Berlin},
   isbn = {3-54034-689-9},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/WurrAndersonStigmergyChapter.pdf},
   abstract = {Robotic agents in dynamic environments must sometimes navigate using only their local perceptions. In complex environments, features such as terrain undulation, geometrically complex barriers, and similar obstacles form local maxima and minima that can trap and hinder agents using reactive navigation. Moreover, agents navigating in a purely reactive fashion forget their past discoveries quickly. Preserving this knowledge usually requires that each agent construct a detailed world model as it explores or be forced to rediscover desired goals each time. Explicit communication can also be required to share discoveries and coordinate actions. The cost of explicit communication can be substantial, however, making it desirable to avoid its use in many domains. Accordingly, in this paper we present a method of cooperative trail making that allows a team of agents using reactive navigation to assist one another in their explorations through implicit (stigmergic) communication.} 
   }
   




2. John Anderson and Jacky Baltes. An Agent-Based Approach to Introductory Robotics Using Robotic Soccer. International Journal of Robotics and Automation, 21(2), February 2006.
   

   @article{socceredjournal,
   author = {John Anderson and Jacky Baltes},
   title = {An Agent-Based Approach to Introductory Robotics Using Robotic Soccer},
   journal = {International Journal of Robotics and Automation},
   year = {2006},
   volume = {21},
   number = {2},
   month = {February},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/andersonBaltesIJRA.pdf} 
   }
   




3. Kuo-Yang Tu and Jacky Baltes. Fuzzy potential energy for a map approach to robot navigation. Robotics and Autonomous Systems, 54(7):574-589, 2006. Abstract:

   A fully autonomous robot needs a flexible map to solve frequent change of robot situations and/or tasks. In this paper, based on the second type of fuzzy modeling, fuzzy potential energy (FPE) is proposed to build a map that facilitates planning robot tasks for real paths. Three rules for making use of FPEs are derived to ground the basic ideas of building a map for task navigation. How the FPE performs robot navigation is explained by its gradient directions and shown by its gradient trajectories. To code qualitative information into quantity, the proposed FPE provides a way to quickly find a path for conducting the designated task or solving a robot under an embarrassing situation. This paper pioneers novel design and application of fuzzy modeling for a special map that exploits innovation usage of task navigation for real paths. Actually, visibility graphs based on the knowledge of human experts are employed to build FPE maps for navigation. To emphasize the idea of the created FPE, seven remarks direct the roadmap towards being a utility tool for robot navigation. Three illustrative examples, containing three spatial patterns, doors, corridors and cul-de-sacs, are also included. This paper paves the way to create ideas of intelligent navigation for further developments.

   
   

   @article{FuzzyPotentialEnergy2006,
   author = {Kuo-Yang Tu and Jacky Baltes},
   title = {Fuzzy potential energy for a map approach to robot navigation},
   journal = {Robotics and Autonomous Systems},
   year = {2006},
   volume = {54},
   number = {7},
   pages = {574--589},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/FuzzyPotentialEnergy2006.pdf},
   abstract = {A fully autonomous robot needs a flexible map to solve frequent change of robot situations and/or tasks. In this paper, based on the second type of fuzzy modeling, fuzzy potential energy (FPE) is proposed to build a map that facilitates planning robot tasks for real paths. Three rules for making use of FPEs are derived to ground the basic ideas of building a map for task navigation. How the FPE performs robot navigation is explained by its gradient directions and shown by its gradient trajectories. To code qualitative information into quantity, the proposed FPE provides a way to quickly find a path for conducting the designated task or solving a robot under an embarrassing situation. This paper pioneers novel design and application of fuzzy modeling for a special map that exploits innovation usage of task navigation for real paths. Actually, visibility graphs based on the knowledge of human experts are employed to build FPE maps for navigation. To emphasize the idea of the created FPE, seven remarks direct the roadmap towards being a utility tool for robot navigation. Three illustrative examples, containing three spatial patterns, doors, corridors and cul-de-sacs, are also included. This paper paves the way to create ideas of intelligent navigation for further developments. } 
   }
   




4. Ryan Wegner and John Anderson. Agent-Based Support for Balancing Teleoperation and Autonomy in Urban Search and Rescue. International Journal of Robotics and Automation, 21(2), February 2006.
   

   @article{teleautomjournal,
   author = {Ryan Wegner and John Anderson},
   title = {Agent-Based Support for Balancing Teleoperation and Autonomy in Urban Search and Rescue},
   journal = {International Journal of Robotics and Automation},
   year = {2006},
   volume = {21},
   number = {2},
   month = {February},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/wegnerAndersonIJRA.pdf} 
   }
   

1. Jacky Baltes and John Anderson. Abarenbou and DaoDan: Affordable Research Platforms for Humanoid Robotics. In Proceedings of the Invited Workshop on Artificial Intelligence and Humanoid Robotics, 29th Annual German Conference on Artificial Intelligence, Bremen, Germany, June 2006.
   

   @inproceedings{BaltesAnderson06:AbarenbouDaodan,
   author = {Jacky Baltes and John Anderson},
   title = {Abarenbou and DaoDan: Affordable Research Platforms for Humanoid Robotics},
   booktitle = {Proceedings of the Invited Workshop on Artificial Intelligence and Humanoid Robotics, 29th Annual German Conference on Artificial Intelligence},
   year = {2006},
   address = {Bremen, Germany},
   month = {June} 
   }
   




2. Jacky Baltes and John Anderson. Affordable Platforms for HuroSot. In Proceedings of the 2006 FIRA Robot World Congress, Dortmund, Germany, June 2006.
   

   @inproceedings{BaltesAnderson06:AbarenbouDaodan,
   author = {Jacky Baltes and John Anderson},
   title = {Affordable Platforms for HuroSot},
   booktitle = {Proceedings of the 2006 FIRA Robot World Congress},
   year = {2006},
   address = {Dortmund, Germany},
   month = {June} 
   }
   




3. Jacky Baltes and John Anderson. DAODAN: An Affordable Research Platform for Humanoid Robotics. In Proceedings of the Fourth International Conference on Autonomous Robots and Agents (ICARA), Palmerston North, New Zealand, December 2006.
   

   @inproceedings{BaltesAnderson06:DaoDanIcara,
   author = {Jacky Baltes and John Anderson},
   title = {DAODAN: An Affordable Research Platform for Humanoid Robotics},
   booktitle = {Proceedings of the Fourth International Conference on Autonomous Robots and Agents (ICARA)},
   year = {2006},
   address = {Palmerston North, New Zealand},
   month = {December} 
   }
   




4. Jacky Baltes and John Anderson. DaiGuardRS - an affordable platform for research into humanoid robotic soccer. In 37th International Symposium on Robotics (ISR/Robotic-2006), Munich, Germany, May 2006.
   

   @inproceedings{BaltesAnderson06:AbarenbouDaodan,
   author = {Jacky Baltes and John Anderson},
   title = {DaiGuardRS - an affordable platform for research into humanoid robotic soccer},
   booktitle = {37th International Symposium on Robotics (ISR/Robotic-2006)},
   year = {2006},
   address = {Munich, Germany},
   month = {May} 
   }
   




5. Jacky Baltes and John Anderson. The Keystone Scavenger Team. In Yolanda Gill and Raymond Mooney, editors, Proceedings of AAAI-06 (Robot Exhibition Papers), Boston, July 2006. AAAI Press. Abstract:

   Stereo vision for small mobile robots is a challenging problem, particularly when employing embedded systems with limited processing power. However, it holds the promise of greatly increasing the localization, mapping, and navigation ability of mobile robots. To help in scene understanding, objects in the field of vision must be extracted and represented in a fashion useful to the system. At the same time, methods must be in place for dealing with the large volume of data that stereo vision produces, in order that a practical frame rate may be obtained. We have been working on stereo vision as the sole form of perception for Urban Search and Rescue (USAR) domains over the last three years. Recently, we have extended our work to include domains with more complex human robot interactions. Our entry in the 2006 AAAI Robotics competition embodies these ideas.

   
   

   @inproceedings{AndersonBaltes06:ScavengerAAAI,
   author = {Jacky Baltes and John Anderson},
   title = {The Keystone Scavenger Team},
   booktitle = {Proceedings of AAAI-06 (Robot Exhibition Papers)},
   year = {2006},
   editor = {Yolanda Gill and Raymond Mooney},
   address = {Boston},
   month = {July},
   publisher = {AAAI Press},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/ScavengerAAAI06.pdf},
   abstract = {Stereo vision for small mobile robots is a challenging problem, particularly when employing embedded systems with limited processing power. However, it holds the promise of greatly increasing the localization, mapping, and navigation ability of mobile robots. To help in scene understanding, objects in the field of vision must be extracted and represented in a fashion useful to the system. At the same time, methods must be in place for dealing with the large volume of data that stereo vision produces, in order that a practical frame rate may be obtained. We have been working on stereo vision as the sole form of perception for Urban Search and Rescue (USAR) domains over the last three years. Recently, we have extended our work to include domains with more complex human robot interactions. Our entry in the 2006 AAAI Robotics competition embodies these ideas.} 
   }
   




6. Mark Karpenko, John Anderson, and Nariman Sepehri. Coordination of Hydraulic Manipulators by Reinforcement Learning. In Proceedings of the American Control Conference, Minneapolis, MN, June 2006.
   

   @inproceedings{KarpenkoAndersonSepehri06:RL,
   author = {Mark Karpenko and John Anderson and Nariman Sepehri},
   title = {Coordination of Hydraulic Manipulators by Reinforcement Learning},
   booktitle = {Proceedings of the American Control Conference},
   year = {2006},
   address = {Minneapolis, MN},
   month = {June},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/KarpenkoAndersonSepehri_ACC06_0483.pdf} 
   }
   

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