Toward an object-based semantic memory for long-term operation of mobile service robots

Dayoub, Feras and Duckett, Tom and Cielniak, Grzegorz (2010) Toward an object-based semantic memory for long-term operation of mobile service robots. In: Workshop on Semantic Mapping and Autonomous Knowledge Acquisition, 18 October 2010, Taipei, Taiwan.

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Toward an object-based semantic memory for long-term operation of mobile service robots
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Abstract

Throughout a lifetime of operation, a mobile service robot needs to acquire, store and update its knowledge of a working environment. This includes the ability to identify and track objects in different places, as well as using this information for interaction with humans. This paper introduces a long-term updating mechanism, inspired by the modal model of human memory, to enable a mobile robot to maintain its knowledge of a changing environment. The memory model is integrated with a hybrid map that represents the global topology and local geometry of the environment, as well as the respective 3D location of objects. We aim to enable the robot to use this knowledge to help humans by suggesting the most likely locations of specific objects in its map. An experiment using omni-directional vision demonstrates the ability to track the movements of several objects in a dynamic environment over an extended period of time.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Throughout a lifetime of operation, a mobile service robot needs to acquire, store and update its knowledge of a working environment. This includes the ability to identify and track objects in different places, as well as using this information for interaction with humans. This paper introduces a long-term updating mechanism, inspired by the modal model of human memory, to enable a mobile robot to maintain its knowledge of a changing environment. The memory model is integrated with a hybrid map that represents the global topology and local geometry of the environment, as well as the respective 3D location of objects. We aim to enable the robot to use this knowledge to help humans by suggesting the most likely locations of specific objects in its map. An experiment using omni-directional vision demonstrates the ability to track the movements of several objects in a dynamic environment over an extended period of time.
Keywords:semantic mapping, mobile robotics, computer vision
Subjects:G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Computer Science
ID Code:3866
Deposited By:INVALID USER
Deposited On:18 Jan 2011 21:00
Last Modified:13 Mar 2013 08:53

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