Paper Info
Title
Design Of A Novel Gripper System With 3d-And Inkjet-Printed Multimodal Sensors For Automated Grasping Of A Forestry Robot
Abstract
Future industrial robotic systems increasingly rely on automation of dangerous and tedious tasks. The acquisition of diverse and partially redundant information using reliable and rugged multimodal sensors helps to improve the safety an dependability of such systems. In this paper we propose proximity sensors suitable for the integration into the gripper of a forestry robot. The suggested sensors are complementary to vision based data acquisition as it can in particular provide information on objects close to the gripper that could otherwise not be obtained due to occlusion and missing direct line of sight. We present the design, fabrication and evaluation of 3D- and inkjet-printed capacitive sensors for grasping applications in harsh industrial environment, especially forestry robotics. The sensor elements have been developed along with a complete gripper re-design. The suggested fabrication strategy allows retrofitting of various industry components and reduced maintenance and costs as well as application-specific design and optimization and are also suitable for wireless operation. The developed gripper allows the support of grasping tasks by providing proximity and contact information.
Year
DOI
Venue
2019
10.1109/IROS40897.2019.8968134
2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
Field
DocType
ISSN
Dependability,Proximity sensor,Wireless,Computer science,Data acquisition,Control engineering,Automation,Capacitive sensing,Forestry,Artificial intelligence,Robot,Robotics
Conference
2153-0858
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Lisa-Marie Faller1134.94
Christian Stetco211.02
Hubert Zangl35821.63