Abstract:
Semi-autonomous control schemes can address the limitations of both teleoperation and fully autonomous robotic control of rescue robots in disaster environments by allowi...Show MoreMetadata
Abstract:
Semi-autonomous control schemes can address the limitations of both teleoperation and fully autonomous robotic control of rescue robots in disaster environments by allowing a human operator to cooperate and share such tasks with a rescue robot as navigation, exploration, and victim identification. In this paper, we present a unique hierarchical reinforcement learning-based semi-autonomous control architecture for rescue robots operating in cluttered and unknown urban search and rescue (USAR) environments. The aim of the controller is to enable a rescue robot to continuously learn from its own experiences in an environment in order to improve its overall performance in exploration of unknown disaster scenes. A direction-based exploration technique is integrated in the controller to expand the search area of the robot via the classification of regions and the rubble piles within these regions. Both simulations and physical experiments in USAR-like environments verify the robustness of the proposed HRL-based semi-autonomous controller to unknown cluttered scenes with different sizes and varying types of configurations.
Published in: IEEE Transactions on Cybernetics ( Volume: 44, Issue: 12, December 2014)
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- IEEE Keywords
- Index Terms
- Space Robot ,
- Disaster Scene ,
- Navigation ,
- Autonomic System ,
- Robot Control ,
- Environment In Order ,
- Region Classification ,
- Human Operator ,
- Autonomic Control ,
- Environmental Disasters ,
- Exploratory Technique ,
- Victim Identification ,
- Robots In Environments ,
- Natural Environment ,
- Value Function ,
- Number Of Steps ,
- Current Position ,
- Sensory Information ,
- Adjacent Cells ,
- Level Of Autonomy ,
- Unknown Environment ,
- Simultaneous Localization And Mapping ,
- Positive Reward ,
- Obstacle Avoidance ,
- Grid Map ,
- Potential Victims ,
- Scene Regions ,
- Mobile Robot ,
- Robot Navigation
- Author Keywords
- MeSH Terms
- Author Free Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Space Robot ,
- Disaster Scene ,
- Navigation ,
- Autonomic System ,
- Robot Control ,
- Environment In Order ,
- Region Classification ,
- Human Operator ,
- Autonomic Control ,
- Environmental Disasters ,
- Exploratory Technique ,
- Victim Identification ,
- Robots In Environments ,
- Natural Environment ,
- Value Function ,
- Number Of Steps ,
- Current Position ,
- Sensory Information ,
- Adjacent Cells ,
- Level Of Autonomy ,
- Unknown Environment ,
- Simultaneous Localization And Mapping ,
- Positive Reward ,
- Obstacle Avoidance ,
- Grid Map ,
- Potential Victims ,
- Scene Regions ,
- Mobile Robot ,
- Robot Navigation
- Author Keywords
- MeSH Terms
- Author Free Keywords