TY - JOUR
T1 - Controlling object hand-over in human-robot collaboration via natural wearable sensing
AU - Wang, Weitian
AU - Li, Rui
AU - Diekel, Zachary Max
AU - Chen, Yi
AU - Zhang, Zhujun
AU - Jia, Yunyi
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2019/2
Y1 - 2019/2
N2 - With the deployment of collaborative robots in intelligent manufacturing, object hand-over between humans and robots plays a significant role in human-robot collaborations. In most collaboration studies, human hand-over intentions were usually assumed to be known by the robot, and the research mainly focused on robot motion planning and control during the hand-over process. Several approaches have been developed to control the human-robot hand-over, such as vision-based approach and physical contact-based approach, but their applications in manufacturing environments are limited due to various constraints, such as limited human working ranges and safety concerns. In this paper, we develop a practical approach using a wearable sensory system, which has a natural and simple configuration and can be easily utilized by humans. This approach could make a robot recognize a human's hand-over intentions and enable the human to effectively and naturally control the hand-over process. In addition, the approach could recognize the attribute classes of the objects in the human's hand using the wearable sensing and enable the robot to actively make decisions to ensure that graspable objects are handed over from the human to the robot. Results and evaluations illustrate the effectiveness and advantages of the proposed approach in human-robot hand-over control.
AB - With the deployment of collaborative robots in intelligent manufacturing, object hand-over between humans and robots plays a significant role in human-robot collaborations. In most collaboration studies, human hand-over intentions were usually assumed to be known by the robot, and the research mainly focused on robot motion planning and control during the hand-over process. Several approaches have been developed to control the human-robot hand-over, such as vision-based approach and physical contact-based approach, but their applications in manufacturing environments are limited due to various constraints, such as limited human working ranges and safety concerns. In this paper, we develop a practical approach using a wearable sensory system, which has a natural and simple configuration and can be easily utilized by humans. This approach could make a robot recognize a human's hand-over intentions and enable the human to effectively and naturally control the hand-over process. In addition, the approach could recognize the attribute classes of the objects in the human's hand using the wearable sensing and enable the robot to actively make decisions to ensure that graspable objects are handed over from the human to the robot. Results and evaluations illustrate the effectiveness and advantages of the proposed approach in human-robot hand-over control.
KW - Hand-over control
KW - human intention understanding
KW - human-robot collaboration
KW - object attribute recognition
UR - http://www.scopus.com/inward/record.url?scp=85058885871&partnerID=8YFLogxK
U2 - 10.1109/THMS.2018.2883176
DO - 10.1109/THMS.2018.2883176
M3 - Article
AN - SCOPUS:85058885871
SN - 2168-2291
VL - 49
SP - 59
EP - 71
JO - IEEE Transactions on Human-Machine Systems
JF - IEEE Transactions on Human-Machine Systems
IS - 1
M1 - 8579107
ER -