@inproceedings{TAMBlta18,
    author = {Antony Thomas and Sunny Amatya and Fulvio Mastrogiovanni and Marco Baglietto},
    title = {Towards Perception Aware Task-Motion Planning},
    booktitle = {Proceedings of the AAAI Fall Symposium on Reasoning and Learning in Real-World Systems for Long-Term Autonomy},
    pages = {88--95},
    year = {2018},
    abstract = {We present an integrated Task-Motion Planning (TMP) framework in belief space. Autonomous robots operating in real world complex scenarios require planning in the discrete (task) space and the continuous (motion) space. We develop a framework for integrating belief space reasoning within a hybrid task planner. The expressive power of PDDL+ combined with heuristic driven semantic attachments performs the propagated and posterior belief estimates while planning. The underlying methodology for the development of the hybrid planner is discussed, providing suggestions for further improvements and future work. Furthermore, our approach is unified with ROSPlan and we validate key aspects of our approach using a realistic synthetic simulation.}
}