Exploring AI-Enhanced Shared Control for an Assistive Robotic Arm

被引:0
作者
Pascher, Max [1 ,2 ]
Kronhardt, Kirill [1 ]
Freienstein, Jan [3 ]
Gerken, Jens [1 ]
机构
[1] TU Dortmund Univ, Dortmund, NW, Germany
[2] Univ Duisburg Essen, Essen, NW, Germany
[3] Westphalian Univ Appl Sci, Gelsenkirchen, NW, Germany
来源
ENGINEERING INTERACTIVE COMPUTER SYSTEMS, EICS 2023 INTERNATIONAL WORKSHOPS AND DOCTORAL CONSORTIUM | 2024年 / 14517卷
关键词
Assistive Technologies; Human-Robot-Interaction Mixed Reality; Shared Control; Visual Cues; MANIPULATION;
D O I
10.1007/978-3-031-59235-5_10
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Assistive technologies and in particular assistive robotic arms have the potential to enable people with motor impairments to live a self-determined life. More and more of these systems have become available for end users in recent years, such as the Kinova Jaco robotic arm. However, they mostly require complex manual control, which can overwhelm users. As a result, researchers have explored ways to let such robots act autonomously. However, at least for this specific group of users, such an approach has shown to be futile. Here, users want to stay in control to achieve a higher level of personal autonomy, to which an autonomous robot runs counter. In our research, we explore how Artificial Intelligence (AI) can be integrated into a shared control paradigm. In particular, we focus on the consequential requirements for the interface between human and robot and how we can keep humans in the loop while still significantly reducing the mental load and required motor skills.
引用
收藏
页码:102 / 115
页数:14
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