Intent Understanding Using an Activation Spreading Architecture

Loading...
Thumbnail Image

Authors

Saffar, Mohammad T.
Nicolescu, Mircea
Nicolescu, Monica N.
Rekabdar, Banafsheh

Issue Date

2015

Type

Article

Language

en_US

Keywords

intent recognition , activation spreading network , activity recognition , scene understanding

Research Projects

Organizational Units

Journal Issue

Alternative Title

Abstract

In this paper, we propose a new approach for recognizing intentions of humans by observing their activities with a color plus depth (RGB-D) camera. Activities and goals are modeled as a distributed network of inter-connected nodes in an Activation Spreading Network (ASN). Inspired by a formalism in hierarchical task networks, the structure of the network captures the hierarchical relationship between high-level goals and low-level activities that realize these goals. Our approach can detect intentions before they are realized and it can work in real-time. We also extend the formalism of ASNs to incorporate contextual information into intent recognition. We further augment the ASN formalism with special nodes and synaptic connections to model ordering constraints between actions, in order to represent and handle partial-order plans in our ASN. A fully functioning system is developed for experimental evaluation. We implemented a robotic system that uses our intent recognition to naturally interact with the user. Our ASN based intent recognizer is tested against three different scenarios involving everyday activities performed by a subject, and our results show that the proposed approach is able to detect low-level activities and recognize high-level intentions effectively in real-time. Further analysis shows that contextual and partial-order ASNs are able to discriminate between otherwise ambiguous goals.

Description

Citation

Saffar, M., Nicolescu, M., Nicolescu, M., & Rekabdar, B. (2015). Intent Understanding Using an ActivationSpreading Architecture. Robotics, 4(3), 284–315. doi:10.3390/robotics4030284

Publisher

Robotics

Journal

Volume

Issue

PubMed ID

ISSN

2218-6581

EISSN

Collections