Publication
User interactions and negative examples to improve the learning of semantic rules in a cognitive exercise scenario
Conference Article
Conference
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Edition
2023
Pages
7953-7960
Doc link
http://dx.doi.org/10.1109/IROS55552.2023.10341942
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Authors
Projects associated
Abstract
Enabling a robot to perform new tasks is a complex endeavor, usually beyond the reach of non-technical users. For this reason, research efforts that aim at empowering end-users to teach robots new abilities using intuitive modes of interaction are valuable. In this article, we present INtuitive PROgramming 2 (INPRO2), a learning framework that allows inferring planning actions from demonstrations given by a human teacher. INPRO2 operates in an assistive scenario, in which the robot may learn from a healthcare professional (a therapist or caregiver) new cognitive exercises that can be later administered to patients with cognitive impairment. INPRO2 features significant improvements over previous work, namely: (1) exploitation of negative examples; (2) proactive interaction with the teacher to ask questions about the legality of certain movements; and (3) learning goals in addition to legal actions. Through simulations, we show the performance of different proactive strategies for gathering negative examples. Real-world experiments with human teachers and a TIAGo robot are also presented to qualitatively illustrate INPRO2.
Categories
artificial intelligence, learning (artificial intelligence), planning (artificial intelligence), uncertainty handling.
Scientific reference
A. Suárez, A. Andriella, C. Torras and G. Alenyà. User interactions and negative examples to improve the learning of semantic rules in a cognitive exercise scenario, 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2023, Detroit, MI, USA, pp. 7953-7960.
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