Distributed Watchpoints: Debugging Very Large Ensembles of Robots

@inproceedings{ashley-rollman-iclp09,
  author = {Ashley-Rollman, Michael P. and Lee, Peter and Goldstein,
     Seth Copen and Pillai, Padmanabhan and Campbell, Jason D.},
  title = {A Language for Large Ensembles of Independently Executing
     Nodes},
  year = {2009},
  month = {July},
  keywords = {Distributed Systems, Meld, Programming Languages},
  url = {http://www.cs.cmu.edu/~claytronics/papers/ashley-rollman-iclp09.pdf},
  abstract = {We address how to write programs for distributed
     computing systems in which the network topology can change
     dynamically. Examples of such systems, which we call {\em
     ensembles}, include programmable sensor networks (where the
     network topology can change due to failures in the nodes or
     links) and modular robotics systems (whose physical configuration
     can be rearranged under program control). We extend Meld, a logic
     programming language that allows an ensemble to be viewed as a
     single computing system. In addition to proving some key
     properties of the language, we have also implemented a complete
     compiler for Meld. It generates code for TinyOS and for a
     Claytronics simulator. We have successfully written correct,
     efficient, and complex programs for ensembles containing over one
     million nodes.},
  booktitle = {Proceedings of the International Conference on Logic
     Programming (ICLP '09)},
}

@inproceedings{funiak-rss08,
  author = {Funiak, Stanislav and Pillai, Padmanabhan and
     Ashley-Rollman, Michael P. and Campbell, Jason D. and Goldstein,
     Seth Copen},
  title = {Distributed Localization of Modular Robot Ensembles},
  booktitle = {Proceedings of Robotics: Science and Systems},
  year = {2008},
  month = {June},
  abstract = {Internal localization, the problem of estimating
     relative pose for each module (part) of a modular robot is a
     prerequisite for many shape control, locomotion, and actuation
     algorithms. In this paper, we propose a robust hierarchical
     approach that uses normalized cut to identify dense subregions
     with small mutual localization error, then progressively merges
     those subregions to localize the entire ensemble. Our method
     works well in both 2D and 3D, and requires neither exact
     measurements nor rigid inter-module connectors. Most of the
     computations in our method can be effectively distributed. The
     result is a robust algorithm that scales to large,
     non-homogeneous ensembles. We evaluate our algorithm in accurate
     2D and 3D simulations of scenarios with up to 10,000 modules.},
  keywords = {Distributed Systems, Localization, Meld},
  url = {http://www.cs.cmu.edu/~claytronics/papers/funiak-rss2008.pdf},
}

@article{mderosa-ijrr-2008,
  author = {De~Rosa, Michael and Goldstein, Seth Copen and Lee, Peter
     and Campbell, Jason D. and Pillai, Padmanabhan},
  journal = {International Journal of Robotics Research},
  keywords = {Debugging, Distributed Systems},
  month = {March},
  note = {Special Issue on Modular Robotics},
  url = {http://www.cs.cmu.edu/~claytronics/papers/mderosa-ijrr-2008.pdf},
  venue = {International Journal of Robotics Research},
  number = {3},
  title = {Distributed Watchpoints: Debugging Large Modular Robotic
     Systems},
  abstract = {Distributed systems frequently exhibit properties of
     interest which span multiple entities. These properties cannot
     easily be detected from any single entity, but can be readily be
     detected by combining the knowledge of multiple entities. Testing
     for distributed properties is especially important in debugging
     or verifying software for modular robots. We have developed a
     technique we call distributed watchpoint triggers which can
     efficiently recognize distributed conditions. Our watchpoint
     description language can handle a variety of temporal, spatial,
     and logical properties spanning multiple robots. This paper
     presents the specification language, describes the distributed
     online mechanism for detecting distributed conditions in a
     running system, and evaluates the performance of our
     implementation.},
  volume = {27},
  also = {Distributed Watchpoints: Debugging Large Multi-Robot
     Systems, (icra07)},
  year = {2008},
}

@inproceedings{rister-icra07,
  author = {Rister, Benjamin D. and Campbell, Jason D. and Pillai,
     Padmanabhan and Mowry, Todd C.},
  title = {Integrated Debugging of Large Modular Robot Ensembles},
  booktitle = {Proceedings of the IEEE International Conference on
     Robotics and Automation {ICRA '07}},
  venue = {IEEE International Conference on Robotics and Automation
     (ICRA)},
  keywords = {Debugging, Distributed Systems},
  month = {April},
  abstract = {Creatively misquoting Thomas Hobbes, the process of
     software debugging is nasty, brutish, and all too long. This
     holds all the more true in robotics, which frequently involves
     concurrency, extensive nondeterminisism, event-driven components,
     complex state machines, and difficult platform limitations.
     Inspired by the challenges we have encountered while attempting
     to debug software on simulated ensembles of tens of thousands of
     modular robots, we have developed a new debugging tool
     particularly suited to the characteristics of highly parallel,
     event- and state-driven robotics software. Our state capture and
     introspection system also provides data that may be used in
     higher-level debugging tools as well. We report on the design of
     this promising debugging system, and on our experiences with it
     so far.},
  year = {2007},
  url = {http://www.cs.cmu.edu/~claytronics/papers/rister-icra07.pdf},
}

@inproceedings{derosa-rss06,
  author = {De~Rosa, Michael and Goldstein, Seth Copen and Lee, Peter
     and Campbell, Jason D. and Pillai, Padmanabhan},
  booktitle = {Robotics: Science and Systems Workshop on
     Self-Reconfigurable Modular Robots},
  venue = {Robotics: Science and Systems Workshop on
     Self-Reconfigurable Modular Robots},
  title = {Distributed Watchpoints: Debugging Very Large Ensembles of
     Robots},
  month = {August},
  year = {2006},
  keywords = {Debugging, Distributed Systems},
  address = {Philadelphia, PA},
  talk = {http://www.cs.cmu.edu/~seth/papers/derosa-talk-rss06.pdf},
  url = {http://www.cs.cmu.edu/~claytronics/papers/derosa-rss06.pdf},
  abstract = {We describe a debugging tool for modular robotics that
     introduces the concept of distributed watchpoint triggers. This
     technique can initiate debugging actions (system halt, global
     snapshot, logging, etc.) in an ensemble of robots based on
     temporal, physical, and logical conditions distributed over
     multiple robots. Our technique is specifically designed to be
     effective in debugging modular robotic ensembles, where many
     important types of failure conditions can be detected within
     small, physically connected subsets of the total ensemble.},
}

@article{mderosa-ijrr-2008,
  author = {De~Rosa, Michael and Goldstein, Seth Copen and Lee, Peter
     and Campbell, Jason D. and Pillai, Padmanabhan},
  journal = {International Journal of Robotics Research},
  keywords = {Debugging, Distributed Systems},
  month = {March},
  note = {Special Issue on Modular Robotics},
  url = {http://www.cs.cmu.edu/~claytronics/papers/mderosa-ijrr-2008.pdf},
  venue = {International Journal of Robotics Research},
  number = {3},
  title = {Distributed Watchpoints: Debugging Large Modular Robotic
     Systems},
  abstract = {Distributed systems frequently exhibit properties of
     interest which span multiple entities. These properties cannot
     easily be detected from any single entity, but can be readily be
     detected by combining the knowledge of multiple entities. Testing
     for distributed properties is especially important in debugging
     or verifying software for modular robots. We have developed a
     technique we call distributed watchpoint triggers which can
     efficiently recognize distributed conditions. Our watchpoint
     description language can handle a variety of temporal, spatial,
     and logical properties spanning multiple robots. This paper
     presents the specification language, describes the distributed
     online mechanism for detecting distributed conditions in a
     running system, and evaluates the performance of our
     implementation.},
  volume = {27},
  also = {Distributed Watchpoints: Debugging Large Multi-Robot
     Systems, (icra07)},
  year = {2008},
}

@inproceedings{derosa-icra07,
  abstract = {Tightly-coupled multi-agent systems such as modular
     robots frequently exhibit properties of interest that span
     multiple modules. These properties cannot easily be detected from
     any single module, though they might readily be detected by
     combining the knowledge of multiple modules. Testing for
     distributed conditions is especially important in debugging or
     verifying the correctness of software for modular robots. We have
     developed a technique we call distributed watchpoint triggers
     which can efficiently recognize such distributed conditions. Our
     watchpoint description language can handle a variety of temporal,
     spatial, and logical properties spanning multiple robots. This
     paper presents that language, describes our fully-distributed,
     online mechanism for detecting distributed conditions in a
     running system, and evaluates the performance of our
     implementation. We found that the performance of the system is
     highly dependent on the program being debugged, scales linearly
     with ensemble size, and is small enough to make the system
     practical in all but the worst case scenarios.},
  author = {De~Rosa, Michael and Goldstein, Seth Copen and Lee, Peter
     and Campbell, Jason D. and Pillai, Padmanabhan and Mowry, Todd
     C.},
  booktitle = {Proceedings of the IEEE International Conference on
     Robotics and Automation {ICRA '07}},
  venue = {IEEE International Conference on Robotics and Automation
     (ICRA)},
  title = {Distributed Watchpoints: Debugging Large Multi-Robot
     Systems},
  year = {2007},
  month = {April},
  keywords = {Debugging, Distributed Algorithms},
  url = {http://www.cs.cmu.edu/~claytronics/papers/derosa-icra07.pdf},
}

@inproceedings{rister-icra07,
  author = {Rister, Benjamin D. and Campbell, Jason D. and Pillai,
     Padmanabhan and Mowry, Todd C.},
  title = {Integrated Debugging of Large Modular Robot Ensembles},
  booktitle = {Proceedings of the IEEE International Conference on
     Robotics and Automation {ICRA '07}},
  venue = {IEEE International Conference on Robotics and Automation
     (ICRA)},
  keywords = {Debugging, Distributed Systems},
  month = {April},
  abstract = {Creatively misquoting Thomas Hobbes, the process of
     software debugging is nasty, brutish, and all too long. This
     holds all the more true in robotics, which frequently involves
     concurrency, extensive nondeterminisism, event-driven components,
     complex state machines, and difficult platform limitations.
     Inspired by the challenges we have encountered while attempting
     to debug software on simulated ensembles of tens of thousands of
     modular robots, we have developed a new debugging tool
     particularly suited to the characteristics of highly parallel,
     event- and state-driven robotics software. Our state capture and
     introspection system also provides data that may be used in
     higher-level debugging tools as well. We report on the design of
     this promising debugging system, and on our experiences with it
     so far.},
  year = {2007},
  url = {http://www.cs.cmu.edu/~claytronics/papers/rister-icra07.pdf},
}

@inproceedings{derosa-rss06,
  author = {De~Rosa, Michael and Goldstein, Seth Copen and Lee, Peter
     and Campbell, Jason D. and Pillai, Padmanabhan},
  booktitle = {Robotics: Science and Systems Workshop on
     Self-Reconfigurable Modular Robots},
  venue = {Robotics: Science and Systems Workshop on
     Self-Reconfigurable Modular Robots},
  title = {Distributed Watchpoints: Debugging Very Large Ensembles of
     Robots},
  month = {August},
  year = {2006},
  keywords = {Debugging, Distributed Systems},
  address = {Philadelphia, PA},
  talk = {http://www.cs.cmu.edu/~seth/papers/derosa-talk-rss06.pdf},
  url = {http://www.cs.cmu.edu/~claytronics/papers/derosa-rss06.pdf},
  abstract = {We describe a debugging tool for modular robotics that
     introduces the concept of distributed watchpoint triggers. This
     technique can initiate debugging actions (system halt, global
     snapshot, logging, etc.) in an ensemble of robots based on
     temporal, physical, and logical conditions distributed over
     multiple robots. Our technique is specifically designed to be
     effective in debugging modular robotic ensembles, where many
     important types of failure conditions can be detected within
     small, physically connected subsets of the total ensemble.},
}