A Case Study on the Tower of Hanoi Challenge: Representation, Reasoning and Execution. Havir, G., Haspalamutgil, K., Palaz, C., Erdem, E., & Patoglu, V. In IEEE International Conference on Robotics and Automation (ICRA 2013), 2013. abstract bibtex The Tower of Hanoi puzzle, has recently been established as a robotics challenge as a part of EU Robotics coordination action in 2011 and IEEE IROS Conference in 2012. It provides a good standardized test bed to evaluate integration of high-level reasoning capabilities of robots together with their manipulation and perception aspects.We address this challenge within a general planning and monitoring framework: we represent the puzzle in a logic-based formalism, integrate task planning and motion planning, solve this hybrid planning problem with a state-of-the-art automated reasoner (e.g., a SAT solver), execute the computed plans under feedback control while also monitoring for failures, and recover from failures as required. We show the applicability of this framework by implementing it using two robotic manipulators on a physical experimental setup.
@InProceedings{Havur2013a,
booktitle = {IEEE International Conference on Robotics and Automation (ICRA 2013)},
author = {Giray Havir and Kadir Haspalamutgil and Can Palaz and Esra Erdem and Volkan Patoglu},
title = {A Case Study on the Tower of Hanoi Challenge{: R}epresentation, Reasoning and Execution},
year = {2013},
abstract = {The Tower of Hanoi puzzle, has recently been established as a robotics challenge as a part of EU Robotics coordination action in 2011 and IEEE IROS Conference in 2012. It provides a good standardized test bed to evaluate integration of high-level reasoning capabilities of robots together with their manipulation and perception aspects.We address this challenge within a general planning and monitoring framework: we represent the puzzle in a logic-based formalism, integrate task planning and motion planning, solve this hybrid planning problem with a state-of-the-art automated reasoner (e.g., a SAT solver), execute the computed plans under feedback control while also monitoring for failures, and recover from failures as required. We show the applicability of this framework by implementing it using two robotic manipulators on a physical experimental setup.}
}
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