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Artificial Intelligence for Long-Term Robot Autonomy: A Survey (1807.05196v1)

Published 13 Jul 2018 in cs.RO and cs.AI

Abstract: Autonomous systems will play an essential role in many applications across diverse domains including space, marine, air, field, road, and service robotics. They will assist us in our daily routines and perform dangerous, dirty and dull tasks. However, enabling robotic systems to perform autonomously in complex, real-world scenarios over extended time periods (i.e. weeks, months, or years) poses many challenges. Some of these have been investigated by sub-disciplines of AI including navigation & mapping, perception, knowledge representation & reasoning, planning, interaction, and learning. The different sub-disciplines have developed techniques that, when re-integrated within an autonomous system, can enable robots to operate effectively in complex, long-term scenarios. In this paper, we survey and discuss AI techniques as 'enablers' for long-term robot autonomy, current progress in integrating these techniques within long-running robotic systems, and the future challenges and opportunities for AI in long-term autonomy.

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Authors (5)
  1. Lars Kunze (40 papers)
  2. Nick Hawes (38 papers)
  3. Tom Duckett (14 papers)
  4. Marc Hanheide (27 papers)
  5. Tomáš Krajník (4 papers)
Citations (152)

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