Skip to Main content Skip to Navigation
Conference papers

A framework for robot learning during child-robot interaction with human engagement as reward signal

Abstract : Using robots as therapeutic or educational tools for children with autism requires robots to be able to adapt their behavior specifically for each child with whom they interact. In particular, some children may like to be looked into the eyes by the robot while some may not. Some may like a robot with an extroverted behavior while others may prefer a more introverted behavior. Here we present an algorithm to adapt the robot's expressivity parameters of action (mutual gaze duration, hand movement expressivity) in an online manner during the interaction. The reward signal used for learning is based on an estimation of the child's mutual engagement with the robot, measured through non-verbal cues such as the child's gaze and distance from the robot. We first present a pilot joint attention task where children with autism interact with a robot whose level of expressivity is predetermined to progressively increase, and show results suggesting the need for online adaptation of expressivity. We then present the proposed learning algorithm and some promising simulations in the same task. Altogether, these results suggest a way to enable robot learning based on non-verbal cues and to cope with the high degree of non-stationarities that can occur during interaction with children.
Document type :
Conference papers
Complete list of metadata

Cited literature [10 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-02324150
Contributor : Mehdi Khamassi <>
Submitted on : Monday, October 21, 2019 - 7:25:53 PM
Last modification on : Wednesday, May 19, 2021 - 11:58:13 AM
Long-term archiving on: : Wednesday, January 22, 2020 - 8:01:19 PM

File

Khamassi2018ro-man_08525598.pd...
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02324150, version 1

Citation

Mehdi Khamassi, G Chalvatzaki, T Tsitsimis, G Velentzas, C Tzafestas. A framework for robot learning during child-robot interaction with human engagement as reward signal. 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN 2018), Aug 2018, Nanjing, China. ⟨hal-02324150⟩

Share

Metrics

Record views

35

Files downloads

109