1. Khairuddin Omar, Md Jan Nordin, Prahlad Vadakkepat, Anton Satria Prabowono, Siti Norul Hada Sheikh Abdullah, Jacky Baltes, Shamsudin Mohn Amin, Wan Zuha Wan Hassan, and Mohammad Faidzul Nasrudin, editors. Intelligent Robotics Systems: Inspiring the NEXT (FIRA RoboWorld Congress 2013), volume 376 of Communications in Computer and Information Science, 2013. Springer-Verlag. Abstract:

   The volume consists of selected quality papers from three international conferences. The volume is intended to provide readers with the recent technical progress in robotics, human-robot interactions, cooperative robotics, and related fields. The volume contains 38 papers from the 112 contributed papers at the 16th FIRA RoboWorld congress, in Shah Alam, Malaysia, August 26-27, 2013.

   
   

   @proceedings{InspiringTheNext13,
   editor = {Khairuddin Omar and Md Jan Nordin and Prahlad Vadakkepat and Anton Satria Prabowono and Siti Norul Hada Sheikh Abdullah and Jacky Baltes and Shamsudin Mohn Amin and Wan Zuha Wan Hassan and Mohammad Faidzul Nasrudin},
   booktitle = {Intelligent Robotics Systems: Inspiring the NEXT (FIRA RoboWorld Congress 2013)},
   publisher = {Springer-Verlag},
   location = {Heidelberg},
   year = {2013},
   series = {Communications in Computer and Information Science},
   volume = {376},
   pages = {466},
   isbn = {978-3-642-40408-5},
   abstract = {The volume consists of selected quality papers from three international conferences. The volume is intended to provide readers with the recent technical progress in robotics, human-robot interactions, cooperative robotics, and related fields. The volume contains 38 papers from the 112 contributed papers at the 16th FIRA RoboWorld congress, in Shah Alam, Malaysia, August 26-27, 2013.} 
   }
   

1. Chad Peters. Intrusion and Fraud Detection Using Multiple Machine Learning Algorithms. Master's thesis, Department of Computer Science, University of Manitoba, Winnipeg, Canada, August 2013. Abstract:

   New methods of attacking networks are being invented at an alarming rate, and pure signature detection cannot keep up. The ability of intrusion detection systems to generalize to new attacks based on behavior is of increasing value. Machine Learning algorithms have been successfully applied to intrusion and fraud detection; however the time and accuracy tradeoffs between algorithms are not always considered when faced with such a broad range of choices. This thesis explores the time and accuracy metrics of a wide variety of machine learning algorithms, using a purpose-built supervised learning dataset. Topics covered include dataset dimensionality reduction through pre-processing techniques, training and testing times, classication accuracy, and performance tradeoffs. Further, ensemble learning and meta-classication are used to explore combinations of the algorithms and derived data sets, to examine the effects of homogeneous and heterogeneous aggregations. The results of this research are presented with observations and guidelines for choosing learning schemes in this domain.

   
   

   @mastersthesis{petersThesis,
   author = {Chad Peters},
   title = {Intrusion and Fraud Detection Using Multiple Machine Learning Algorithms},
   school = {Department of Computer Science, University of Manitoba},
   year = {2013},
   address = {Winnipeg, Canada},
   month = {August},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/PetersFinalThesis.pdf},
   abstract = {New methods of attacking networks are being invented at an alarming rate, and pure signature detection cannot keep up. The ability of intrusion detection systems to generalize to new attacks based on behavior is of increasing value. Machine Learning algorithms have been successfully applied to intrusion and fraud detection; however the time and accuracy tradeoffs between algorithms are not always considered when faced with such a broad range of choices. This thesis explores the time and accuracy metrics of a wide variety of machine learning algorithms, using a purpose-built supervised learning dataset. Topics covered include dataset dimensionality reduction through pre-processing techniques, training and testing times, classication accuracy, and performance tradeoffs. Further, ensemble learning and meta-classication are used to explore combinations of the algorithms and derived data sets, to examine the effects of homogeneous and heterogeneous aggregations. The results of this research are presented with observations and guidelines for choosing learning schemes in this domain.} 
   }
   




2. Michael de Denus. Adaptive Formation Control for Heterogeneous Robots With Limited Information. Master's thesis, Department of Computer Science, University of Manitoba, Winnipeg, Canada, April 2013. Abstract:

   In many robotics tasks, it is advantageous for robots to assemble into formations. In many of these applications, it is useful for the robots to have differing capabilities (i.e., be heterogeneous). These differences are task specic, but the most obvious differences lie in sensing and locomotion capabilities. Groups of robots may also have only imperfect or partially-known information about one another as well. One key piece of information that robots often lack is how many other robots are in the environment. This thesis describes a method for formation control that allows heterogeneous robots with limited information to dynamically assemble into formations, merge smaller formations together, and correct errors that may arise in the formation. The approach is shown to be scalable and robust against robot failure, and is evaluated in multiple simulated environments.

   
   

   @mastersthesis{deDenusThesis,
   author = {Michael de Denus},
   title = {Adaptive Formation Control for Heterogeneous Robots With Limited Information},
   school = {Department of Computer Science, University of Manitoba},
   year = {2013},
   address = {Winnipeg, Canada},
   month = {April},
   abstract = {In many robotics tasks, it is advantageous for robots to assemble into formations. In many of these applications, it is useful for the robots to have differing capabilities (i.e., be heterogeneous). These differences are task specic, but the most obvious differences lie in sensing and locomotion capabilities. Groups of robots may also have only imperfect or partially-known information about one another as well. One key piece of information that robots often lack is how many other robots are in the environment. This thesis describes a method for formation control that allows heterogeneous robots with limited information to dynamically assemble into formations, merge smaller formations together, and correct errors that may arise in the formation. The approach is shown to be scalable and robust against robot failure, and is evaluated in multiple simulated environments.},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/deDenusMScThesis.pdf} 
   }
   

1. Jacky Baltes, Chris Iverach-Brereton, and John Anderson. Sensor Filtering for Balancing of Humanoid Robots in Highly Dynamic Environments. In Proceedings of the 2013 International Automatic Control Conference (CACS), Sun Moon Lake, Taiwan, pages 170-173, December 2013. Abstract:

   This paper is part of our ongoing research in balancing of humanoid robots in highly dynamic environments. We focus on balancing of a humanoid robot on a Bongo board. One of the problems with balancing in highly dynamic environments such as the Bongo board is the fact that any control algorithm needs to overcome the inherent latency and jitter in the sensors as well as in the actuators of the robot, since it has very little time to react to disturbances. The sensor filter method described in this paper allows the robot Jimmy (a DARwIn-OP robot) to balance for several seconds on a Bongo board. A video of the robot Jimmy balancing on the Bongo board can be found at http://www.youtube.com/watch?v=ia2ZYqqF-lw .

   
   

   @inproceedings{SensorFilteringDynamicBalance13,
   author = {Jacky Baltes and Chris Iverach-Brereton and John Anderson},
   title = {Sensor Filtering for Balancing of Humanoid Robots in Highly Dynamic Environments},
   booktitle = {Proceedings of the 2013 International Automatic Control Conference (CACS)},
   address = {Sun Moon Lake, Taiwan},
   month = {December},
   pages = {170--173},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/SensorFilteringDynamicBalance13.pdf},
   year = {2013},
   abstract = {This paper is part of our ongoing research in balancing of humanoid robots in highly dynamic environments. We focus on balancing of a humanoid robot on a Bongo board. One of the problems with balancing in highly dynamic environments such as the Bongo board is the fact that any control algorithm needs to overcome the inherent latency and jitter in the sensors as well as in the actuators of the robot, since it has very little time to react to disturbances. The sensor filter method described in this paper allows the robot Jimmy (a DARwIn-OP robot) to balance for several seconds on a Bongo board. A video of the robot Jimmy balancing on the Bongo board can be found at http://www.youtube.com/watch?v=ia2ZYqqF-lw .} 
   }
   




2. Jacky Baltes, Chris Iverach-Brereton, Diana Carrier, and John Anderson. The Snobots: Jennifer, Jimmy, and Jeff. In Sven Behnke, Manuela Veloso, Arnoud Visser, and Rong Xiong, editors, RoboCup-2013 Proceedings (Team Description Papers), Eindhoven, Netherlands, July 2013. Abstract:

   This paper describes our latest humanoid robots: Jennifer, Jimmy, and Jeff. These robots are customised DARwIn-OP model robots; we have written our own image processing and localisation algorithms, and modied the robots' hardware through the addition of single-DOF grippers and FSR sensors mounted in the feet. We have used these robots successfully in several competitions over the last two years, including FIRA and IRC. This will be our first time using them at RoboCup.

   
   

   @inproceedings{RC2013HumanoidTeam,
   author = {Jacky Baltes and Chris Iverach-Brereton and Diana Carrier and John Anderson},
   title = {The Snobots: Jennifer, Jimmy, and Jeff},
   booktitle = {RoboCup-2013 Proceedings (Team Description Papers)},
   editor = {Sven Behnke and Manuela Veloso and Arnoud Visser and Rong Xiong},
   address = {Eindhoven, Netherlands},
   year = {2013},
   month = {July},
   abstract = {This paper describes our latest humanoid robots: Jennifer, Jimmy, and Jeff. These robots are customised DARwIn-OP model robots; we have written our own image processing and localisation algorithms, and modied the robots' hardware through the addition of single-DOF grippers and FSR sensors mounted in the feet. We have used these robots successfully in several competitions over the last two years, including FIRA and IRC. This will be our first time using them at RoboCup.},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/teamDescriptionRoboCup13.pdf} 
   }
   




3. Jacky Baltes, Kuo-Yang Tu, and John Anderson. Options and Pitfalls in Embedded Systems Development for Intelligent Humanoid Robots. In Proceedings of FIRA 2013, CCIS 376, Kuala Lumpur, Malaysia, pages 77-89, August 2013. Abstract:

   This paper describes the most popular options that are available developers of intelligent humanoid robots and their advantages and disadvantages. There has never been a wider range of affordable and practical solutions for the developers of intelligent humanoid robots. This paper lists the suitability of the most common options such as microcontrollers, ARM based embedded boards, and x86 based small PCs and how well the meet different design constraints. Using an example from low level vision processing, the paper highlights common pitfalls when including these more complex embedded systems in their robot.

   
   

   @inproceedings{EmbeddedHumanoid13,
   author = {Jacky Baltes and Kuo-Yang Tu and John Anderson},
   title = {Options and Pitfalls in Embedded Systems Development for Intelligent Humanoid Robots},
   booktitle = {Proceedings of FIRA 2013, CCIS 376},
   address = {Kuala Lumpur, Malaysia},
   year = {2013},
   month = {August},
   pages = {77--89},
   abstract = {This paper describes the most popular options that are available developers of intelligent humanoid robots and their advantages and disadvantages. There has never been a wider range of affordable and practical solutions for the developers of intelligent humanoid robots. This paper lists the suitability of the most common options such as microcontrollers, ARM based embedded boards, and x86 based small PCs and how well the meet different design constraints. Using an example from low level vision processing, the paper highlights common pitfalls when including these more complex embedded systems in their robot. },
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/EmbeddedHumanoid13.pdf} 
   }
   




4. Tyler Gunn and John Anderson. Dynamic Heterogeneous Team Formation for Robotic Urban Search and Rescue. In Proceedings of the Fourth International Conference on Ambient Systems, Networks and Technologies (ANT-2013), Halifax, Canada, June 2013. Note: Best Paper Award. Abstract:

   Though much work on coalition formation and maintenance exists from the standpoint of abstract agents, this has not yet translated well to the realm of physically grounded robots. Most multi-robot research has focused on pre-formed teams, with little attention to the formation and maintenance of the team itself. While this is plausible in forgiving domains, it fails rapidly in challenging environments where equipment is lost or broken easily, such as urban search and rescue. This paper describes the team management elements of a framework for coordinating a changing collection of heterogeneous robots operating in complex and dynamic environments such as disaster zones. Our framework helps a team to reshape itself to compensate for lost or failed robots, including adding newly-encountered robots or additions from other teams, and also allows new teams to be formed dynamically starting from an individual robot. We evaluate our framework through an example implementation where robots perform exploration in order to locate victims in a simulated disaster environment.

   
   

   @inproceedings{gunnANT2013,
   author = {Tyler Gunn and John Anderson},
   title = {Dynamic Heterogeneous Team Formation for Robotic Urban Search and Rescue},
   booktitle = {Proceedings of the Fourth International Conference on Ambient Systems, Networks and Technologies (ANT-2013)},
   address = {Halifax, Canada},
   year = {2013},
   month = {June},
   note = {Best Paper Award},
   abstract = {Though much work on coalition formation and maintenance exists from the standpoint of abstract agents, this has not yet translated well to the realm of physically grounded robots. Most multi-robot research has focused on pre-formed teams, with little attention to the formation and maintenance of the team itself. While this is plausible in forgiving domains, it fails rapidly in challenging environments where equipment is lost or broken easily, such as urban search and rescue. This paper describes the team management elements of a framework for coordinating a changing collection of heterogeneous robots operating in complex and dynamic environments such as disaster zones. Our framework helps a team to reshape itself to compensate for lost or failed robots, including adding newly-encountered robots or additions from other teams, and also allows new teams to be formed dynamically starting from an individual robot. We evaluate our framework through an example implementation where robots perform exploration in order to locate victims in a simulated disaster environment.},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/GunnANT2013.pdf} 
   }
   




5. Tyler Gunn and John Anderson. Effective Task Allocation for Evolving Multi-robot Teams in Dangerous Environments. In Proceedings of the 2013 IEEE/WIC/ACM International Conference on Intelligent Agent Technologies (IAT-2013), Atlanta, GA, pages 231-238, November 2013. Abstract:

   This paper describes the task management elements of a framework for coordinating a changing collection of heterogeneous robots operating in complex and dynamic environments such as disaster zones. Our framework allows a team to discover and distribute tasks among its members, in a distributed fashion, where the structure of the team is under regular change. Robots may become lost or fail at any time, and new equipment may arrive at any time. We evaluate our framework through an example implementation where robots perform exploration and search for victims in a simulated disaster environment.

   
   

   @inproceedings{gunnANT2013,
   author = {Tyler Gunn and John Anderson},
   title = {Effective Task Allocation for Evolving Multi-robot Teams in Dangerous Environments},
   booktitle = {Proceedings of the 2013 IEEE/WIC/ACM International Conference on Intelligent Agent Technologies (IAT-2013)},
   address = {Atlanta, GA},
   year = {2013},
   month = {November},
   pages = {231-238},
   abstract = {This paper describes the task management elements of a framework for coordinating a changing collection of heterogeneous robots operating in complex and dynamic environments such as disaster zones. Our framework allows a team to discover and distribute tasks among its members, in a distributed fashion, where the structure of the team is under regular change. Robots may become lost or fail at any time, and new equipment may arrive at any time. We evaluate our framework through an example implementation where robots perform exploration and search for victims in a simulated disaster environment.},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/GunnIAT13.pdf} 
   }
   




6. Kuo-Yang Tu, Chen-Yu Chiu, Shih-An Li, and Jacky Baltes. Design and Implementation of Stereo Vision Systems Based on FPGA for 3D Information. In Proceedings of FIRA 2013, CCIS 376, Kaohsiung, Taiwan, pages 309-318, August 2013. Abstract:

   The purpose of this paper is to utilize Field Programmable Gate Array (FPGA) to perform stereo vision distance detection. However, the stereo vision built by two cameras makes memory space lacking and image process slow under the constraints of FPGA application. In this paper, efficient memory space allocation and hardware calculation for stereo vision detection built in a System on a Programmable Chip (SOPC) based on FPGA are proposed. The hardware for stereo vision distance calculation includes the processing for the images of gray, binary, dilation, erosion, etc, and image geometry method for the vision distance through information of phase differences between two lenses. In addition, the simple hardware algorithm of background image subtraction to capture an object image from a series of image frames is also included. The totally hardware to perform stereo vision distance detection is difficult implementation, but firmware (some calculation in software) is flexible and quick to develop. Therefore, the performance of stereo vision distance detection according to hardware and firmware is compared. Finally, the distance calculation between objects and the lenses is demonstrated by practical experiments.

   
   

   @inproceedings{StereoVisionFPGA,
   author = {Kuo-Yang Tu and Chen-Yu Chiu and Shih-An Li and Jacky Baltes},
   title = {Design and Implementation of Stereo Vision Systems Based on FPGA for 3D Information},
   booktitle = {Proceedings of FIRA 2013, CCIS 376},
   address = {Kaohsiung, Taiwan},
   year = {2013},
   month = {August},
   pages = {309-318},
   abstract = {The purpose of this paper is to utilize Field Programmable Gate Array (FPGA) to perform stereo vision distance detection. However, the stereo vision built by two cameras makes memory space lacking and image process slow under the constraints of FPGA application. In this paper, efficient memory space allocation and hardware calculation for stereo vision detection built in a System on a Programmable Chip (SOPC) based on FPGA are proposed. The hardware for stereo vision distance calculation includes the processing for the images of gray, binary, dilation, erosion, etc, and image geometry method for the vision distance through information of phase differences between two lenses. In addition, the simple hardware algorithm of background image subtraction to capture an object image from a series of image frames is also included. The totally hardware to perform stereo vision distance detection is difficult implementation, but firmware (some calculation in software) is flexible and quick to develop. Therefore, the performance of stereo vision distance detection according to hardware and firmware is compared. Finally, the distance calculation between objects and the lenses is demonstrated by practical experiments.},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/StereoVisionFPGA.pdf} 
   }
   




7. Michael de Denus, John Anderson, and Jacky Baltes. Distributed Formation Control of Heterogeneous Robots with Limited Information. In Sven Behnke, Manuela Veloso, Arnoud Visser, and Rong Xiong, editors, Proceedings of RoboCup-2013: Robot Soccer World Cup XVII, Eindhoven, Netherlands, July 2013. [Poster] Abstract:

   In many multi-robot tasks, it is advantageous for robots to assemble into formations. In many of these applications, it is useful for ering capabilities (i.e., be heterogeneous) in terms of perception and locomotion abilities. In real world settings, groups of robots may also have only imperfect or partially-known information about one another as well. Together, heterogeneity and imperfect knowledge provide signicant challenges to creating and maintaining formations. This paper describes a method for formation control that allows heterogeneous robots with limited information (no known population size, shared coordinates, or predened relationships) to dynamically assemble into formation, merge smaller formations together, and correct errors that may arise in the formation. Using a simulation, we have shown our approach to be scalable and robust against robot failure.

   
   

   @inproceedings{RC13Formations,
   author = {Michael de Denus and John Anderson and Jacky Baltes},
   title = {Distributed Formation Control of Heterogeneous Robots with Limited Information},
   booktitle = {Proceedings of RoboCup-2013: Robot Soccer World Cup XVII},
   editor = {Sven Behnke and Manuela Veloso and Arnoud Visser and Rong Xiong},
   address = {Eindhoven, Netherlands},
   year = {2013},
   month = {July},
   abstract = {In many multi-robot tasks, it is advantageous for robots to assemble into formations. In many of these applications, it is useful for ering capabilities (i.e., be heterogeneous) in terms of perception and locomotion abilities. In real world settings, groups of robots may also have only imperfect or partially-known information about one another as well. Together, heterogeneity and imperfect knowledge provide signicant challenges to creating and maintaining formations. This paper describes a method for formation control that allows heterogeneous robots with limited information (no known population size, shared coordinates, or predened relationships) to dynamically assemble into formation, merge smaller formations together, and correct errors that may arise in the formation. Using a simulation, we have shown our approach to be scalable and robust against robot failure.},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/deDenusFormationsRoboCup13.pdf},
   poster = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/deDenusFormationsRoboCup13Poster.pdf} 
   }
   

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