Toward Mobile Robots Reasoning Like Humans

Authors

  • Jean Oh Carnegie Mellon University
  • Arne Suppé Carnegie Mellon University
  • Felix Duvallet Carnegie Mellon University
  • Abdeslam Boularias Carnegie Mellon University
  • Luis Navarro-Serment Carnegie Mellon University
  • Martial Hebert Carnegie Mellon University
  • Anthony Stentz Carnegie Mellon University
  • Jerry Vinokurov Carnegie Mellon University
  • Oscar Romero Carnegie Mellon University
  • Christian Lebiere Carnegie Mellon University
  • Robert Dean General Dynamics Robotic Systems

DOI:

https://doi.org/10.1609/aaai.v29i1.9383

Keywords:

semantic perception, symbolic navigation, prediction

Abstract

Robots are increasingly becoming key players in human-robot teams. To become effective teammates, robots must possess profound understanding of an environment, be able to reason about the desired commands and goals within a specific context, and be able to communicate with human teammates in a clear and natural way. To address these challenges, we have developed an intelligence architecture that combines cognitive components to carry out high-level cognitive tasks, semantic perception to label regions in the world, and a natural language component to reason about the command and its relationship to the objects in the world. This paper describes recent developments using this architecture on a fielded mobile robot platform operating in unknown urban environments. We report a summary of extensive outdoor experiments; the results suggest that a multidisciplinary approach to robotics has the potential to create competent human-robot teams.

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Published

2015-02-16

How to Cite

Oh, J., Suppé, A., Duvallet, F., Boularias, A., Navarro-Serment, L., Hebert, M., Stentz, A., Vinokurov, J., Romero, O., Lebiere, C., & Dean, R. (2015). Toward Mobile Robots Reasoning Like Humans. Proceedings of the AAAI Conference on Artificial Intelligence, 29(1). https://doi.org/10.1609/aaai.v29i1.9383