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Extending a UGV Teleoperation FLC Interface with Wireless Network Connectivity Information
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0002-6716-1111
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0001-5451-8209
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0002-0483-8391
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0002-7714-928X
2015 (English)In: 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), IEE , 2015, 4305-4312 p.Conference paper (Refereed)Text
Abstract [en]

Teleoperated Unmanned Ground Vehicles (UGVs) are expected to play an important role in future search and rescue operations. In such tasks, two factors are crucial for a successful mission completion: operator situational awareness and robust network connectivity between operator and UGV. In this paper, we address both these factors by extending a new Free Look Control (FLC) operator interface with a graphical representation of the Radio Signal Strength (RSS) gradient at the UGV location. We also provide a new way of estimating this gradient using multiple receivers with directional antennas. The proposed approach allows the operator to stay focused on the video stream providing the crucial situational awareness, while controlling the UGV to complete the mission without moving into areas with dangerously low wireless connectivity. The approach is implemented on a KUKA youBot using commercial-off-the-shelf components. We provide experimental results showing how the proposed RSS gradient estimation method performs better than a difference approximation using omnidirectional antennas and verify that it is indeed useful for predicting the RSS development along a UGV trajectory. We also evaluate the proposed combined approach in terms of accuracy, precision, sensitivity and specificity.

Place, publisher, year, edition, pages
IEE , 2015. 4305-4312 p.
Series
, IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:kth:diva-185108DOI: 10.1109/IROS.2015.7353987ISI: 000371885404073ScopusID: 2-s2.0-84958172076ISBN: 978-1-4799-9994-1OAI: oai:DiVA.org:kth-185108DiVA: diva2:919021
Conference
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), SEP 28-OCT 02, 2015, Hamburg, GERMANY
Note

QC 20160412

Available from: 2016-04-12 Created: 2016-04-11 Last updated: 2016-04-12Bibliographically approved

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Caccamo, SergioParasuraman, RamviyasBåberg, FredrikÖgren, Petter
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