Planning with Task-Oriented Knowledge Acquisition for a Service Robot
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 812-817.
Abstract
We propose a framework for a service robot to behave intelligently in domains that contain incomplete information, underspecified goals and dynamic change. Human robot interaction (HRI), sensing actions and physical actions are uniformly formalized in action language BC. An answer set solver is called to generate plans that guide the robot to acquire task-oriented knowledge and execute actions to achieve its goal, including interacting with human to gather information and sensing the environment to help motion planning. By continuously interpreting and grounding useful sensing information, robot is able to use contingent knowledge to adapt to unexpected changes and faults. We evaluate the approach on service robot KeJia that serves drink to guests, a testing benchmark for general-purpose service robot proposed by RoboCup@Home competition.
@inproceedings{ijcai2016p120,
title = {Planning with Task-Oriented Knowledge Acquisition for a Service Robot},
author = {Chen, Kai and Yang, Fangkai and Chen, Xiaoping},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {812--817},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/120},
}
TY - CPAPER TI - Planning with Task-Oriented Knowledge Acquisition for a Service Robot AU - Chen, Kai AU - Yang, Fangkai AU - Chen, Xiaoping T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 812 EP - 817 UR - https://ijcai.org/proceedings/2016/120 ER -Copied
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