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Free Look UGV Teleoperation Control Tested in Game Environment: Enhanced Performance and Reduced Workload
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0002-0483-8391
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
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2016 (English)In: International Symposium on Safety,Security and Rescue Robotics, 2016Conference paper (Refereed)
Abstract [en]

Concurrent telecontrol of the chassis and camera ofan Unmanned Ground Vehicle (UGV) is a demanding task forUrban Search and Rescue (USAR) teams. The standard way ofcontrolling UGVs is called Tank Control (TC), but there is reasonto believe that Free Look Control (FLC), a control mode used ingames, could reduce this load substantially by decoupling, andproviding separate controls for, camera translation and rotation.The general hypothesis is that FLC (1) reduces robot operators’workload and (2) enhances their performance for dynamic andtime-critical USAR scenarios. A game-based environment wasset-up to systematically compare FLC with TC in two typicalsearch and rescue tasks: navigation and exploration. The resultsshow that FLC improves mission performance in both exploration(search) and path following (navigation) scenarios. In the former,more objects were found, and in the latter shorter navigationtimes were achieved. FLC also caused lower workload and stresslevels in both scenarios, without inducing a significant differencein the number of collisions. Finally, FLC was preferred by 75% of the subjects for exploration, and 56% for path following.

Place, publisher, year, edition, pages
Keyword [en]
Teleoperation, UGV, Search and Rescue, First Response, Disaster Response, FPS, Computer Game
National Category
Research subject
Computer Science
URN: urn:nbn:se:kth:diva-192941OAI: diva2:974494
International Symposium on Safety, Security and Rescue Robotics, Lausanne, October 23-27th, 2016
EU, FP7, Seventh Framework Programme, FP7-ICT-609763
Available from: 2016-09-26 Created: 2016-09-23 Last updated: 2016-10-19

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Båberg, FredrikCaccamo, SergioÖgren, Petter
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Computer Vision and Active Perception, CVAP

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