Acting and Planning with Hierarchical Operational Models on a Mobile Robot: A Study with RAE+UPOM

Oscar Lima, Marc Vinci, Sunandita Patra, Sebastian Stock, Joachim Hertzberg +4 more
7/15/2025
cs.ROcs.AI

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Abstract

Robotic task execution faces challenges due to the inconsistency between symbolic planner models and the rich control structures actually running on the robot. In this paper, we present the first physical deployment of an integrated actor-planner system that shares hierarchical operational models for both acting and planning, interleaving the Reactive Acting Engine (RAE) with an anytime UCT-like Monte Carlo planner (UPOM). We implement RAE+UPOM on a mobile manipulator in a real-world deployment for an object collection task. Our experiments demonstrate robust task execution under action failures and sensor noise, and provide empirical insights into the interleaved acting-and-planning decision making process.

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Cite this paper

@article{lima2025acting,
  title  = {Acting and Planning with Hierarchical Operational Models on a Mobile Robot: A Study with RAE+UPOM},
  author = {Oscar Lima and Marc Vinci and Sunandita Patra and Sebastian Stock and Joachim Hertzberg and Martin Atzmueller and Malik Ghallab and Dana Nau and Paolo Traverso},
  year   = {2025},
  eprint = {2507.11345},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2507.11345v1}
}

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