Inferring user intent to interact with a public service robot using bimodal information analysis. (18th April 2019)

• Record Type: Journal Article
• Authors: Li, Kang; Sun, Shiying; Zhao, Xiaoguang; Wu, Jinting; Tan, Min
• Is Part Of: Advanced robotics. Volume 33:Number 7/8(2019)
• Page Start: 369
• Page End: 387
• Publication Date: 2019-04-18
• Subjects: Intent interactive inferring -- public service robot -- bimodal information analysis -- robot operating system (ROS); Robotics -- Periodicals; Robotics -- Japan -- Periodicals; Robotics; Japan; Periodicals; 629.89205
• DOI: 10.1080/01691864.2019.1599727
• Languages: English
• ISSNs: 0169-1864

Abstract

ABSTRACT: Achieving polite service with a public service robot requires it to proactively ascertain who will interact with it in human-populated environments. Enlightened by interactive inference of intentions among humans, we investigate a novel and practical interactive intention-predicting method for people using bimodal information analysis for a public service robot. Different from the traditional research, only the visual cues are used to analyze the user's attention, this method combines the RGB-D camera and laser information to perceive the user, which realizes the 360-degree range perception, and compensates for the lack of perspective using the RGB-D camera. In addition, seven kinds of interactive intent features were extracted, and a random forest regression model was trained to score the interaction intentions of the people in the field of view. Considering the inference order of two different sensors, a priority rule for intention inference is also designed. The algorithm is implemented into a robot operation system (ROS) and evaluated on our public service robot. Extensive experimental results illustrate that the proposed method enables public service robots to achieve a higher level of politeness than the traditional, passive interactivity approach in which robots wait for commands from users. GRAPHICAL ABSTRACT: