Human-Automation Interaction for Assisting Novices to Emulate Experts by Inferring Task Objective Functions

被引：4
作者：
Byeon, Sooyung [1 ]
Jin, Wanxin [1 ]
Sun, Dawei [1 ]
Hwang, Inseok [1 ]
机构：
[1] Purdue Univ, Sch Aeronaut & Astronaut, W Lafayette, IN 47907 USA
来源：
2021 IEEE/AIAA 40TH DIGITAL AVIONICS SYSTEMS CONFERENCE (DASC) | 2021年
关键词：
Human-automation interaction; Skill transfer; Remotely piloted quadrotor; Inferring task objective function; Inverse optimal control; INVERSE OPTIMAL-CONTROL; SHARED CONTROL;
D O I：
10.1109/DASC52595.2021.9594324
中图分类号：
V [航空、航天];
学科分类号：
08 ; 0825 ;
摘要：
In this paper, we propose a human-automation interaction scheme to improve the task performance of novice human users with different skill levels. The proposed scheme includes two interaction modes: learn from experts mode and assist novices mode. In the learn from experts mode, the automation learns from a human expert user such that the awareness of task objective is obtained. Based on the learned task objective, in the assist novices mode, the automation customizes its control parameter to assist a novice human user towards emulating the performance of the expert human user. We experimentally test the proposed human-automation scheme in a designed quadrotor simulation environment, and the results show that the proposed approach is capable of adapting to and assisting the novice human user to achieve the performance that emulates the expert human user.
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页数：6
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