Planning Beyond The Sensing Horizon Using a Learned Context

@article{Everett2019PlanningBT,
  title={Planning Beyond The Sensing Horizon Using a Learned Context},
  author={Michael Everett and J. Miller and J. How},
  journal={2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year={2019},
  pages={1064-1071}
}
  • Michael Everett, J. Miller, J. How
  • Published 2019
  • Computer Science
  • 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • Last-mile delivery systems commonly propose the use of autonomous robotic vehicles to increase scalability and efficiency. The economic inefficiency of collecting accurate prior maps for navigation motivates the use of planning algorithms that operate in unmapped environments. However, these algorithms typically waste time exploring regions that are unlikely to contain the delivery destination. Context is key information about structured environments that could guide exploration toward the… CONTINUE READING
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    References

    SHOWING 1-10 OF 40 REFERENCES
    Target-driven visual navigation in indoor scenes using deep reinforcement learning
    • 729
    • PDF
    Cognitive Mapping and Planning for Visual Navigation
    • 342
    High-speed autonomous navigation of unknown environments using learned probabilities of collision
    • 15
    • PDF
    Learning deep generative spatial models for mobile robots
    • Andrzej Pronobis, R. P. Rao
    • Computer Science, Engineering
    • 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
    • 2017
    • 26
    • PDF
    Learning search heuristics for finding objects in structured environments
    • 29
    • PDF
    Active Visual Object Search in Unknown Environments Using Uncertain Semantics
    • 79
    Learning to locate from demonstrated searches
    • 1
    • PDF
    Receding Horizon "Next-Best-View" Planner for 3D Exploration
    • 189
    • PDF