A Human-Robot Interaction for a Mecanum Wheeled Mobile Robot with Real-Time 3D Two-Hand Gesture Recognition

被引：6

作者：

Luo, Xueling ^{[1
]}

Amighetti, Andrea ^{[1
,2
]}

Zhang, Dan ^{[1
]}

机构：

[1] York Univ, Dept Mech Engn, Toronto, ON, Canada

[2] Univ Brescia, Dept Ind Mech Engn, Brescia, Italy

来源：

2019 3RD INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, AUTOMATION AND CONTROL TECHNOLOGIES (AIACT 2019) | 2019年 / 1267卷

基金：

加拿大自然科学与工程研究理事会;

关键词：

D O I：

10.1088/1742-6596/1267/1/012056

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Human interaction with mobile robot becomes a popular research area and its applications are widely used in industrial, commercial and military fields. A two-hand gesture recognition method with depth camera is presented for real-time controlling the mecanum wheeled mobile robot. Seven different gestures could be recognized from one hand for mobile robot navigation and three gestures could be recognized from the other hand for controlling the gripper installed on the robot. Under the proposed control scheme, the mobile robot system can be navigated and can be operated at the same time for achieving missions by two different groups of hand gestures. The accuracy of the gesture recognition is about 94%. During mobile robot control experiment, the system works timely, accurately and stably for certain tasks such as directional movement, grasping and cleaning obstacles.

引用

页数：7

共 15 条

[1] Model-based 3D hand posture estimation from a single 2D image [J].