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Heterogeneous 3D Exploration with UAVs
KTH, School of Electrical Engineering and Computer Science (EECS).
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Multi-robot exploration algorithms usually focus on exploration time minimization while ignoring map accuracy. In this thesis, it is presented a new heterogeneous multi-robot exploration strategy that finds a balance between time consumption and map accuracy. By ranking UAVs based on their sensor accuracy, it is possible to coordinate them and pick strategic points to explore rather than the most rewarding ones. In particular, with a function (in this case a Gaussian) that maps a voxel’s uncertainty to a score, it is possible to tailor a UAV’s preference (by tuning expected value and variance) towards certain features and not only unexplored space. This algorithm was compared with AEPlanner for several environments, achieving better accuracy towards complete map exploration.

Abstract [sv]

Multi-robot-utforskningsalgoritmer fokuserar vanligtvis på tidsminimeringen medan man ignorerar kartnoggrannheten. I detta examensarbete presenteras en ny heterogen multirobot-utforskningsstrategi som hittar en balans mellan tidsförbrukningen och kartnoggrannheten. Genom att rangordna UAVer baserat på sensorns noggrannhet är det möjligt att samordna dem och välja strategiska punkter för att utforska istället för de mest givande. I synnerhet med en funktion (i detta fall en gaussisk) som tilldelar en voxels osäkerhet en poäng, är det möjligt att skräddarsy en UAVs preferens (genom att ställa in förväntat värde och varians) till vissa funktioner och inte bara outforskat utrymme. Denna algoritm jämfördes med AEPlanner för flera miljöer, vilket uppnådde bättre noggrannhet mot fullständig kartutforskning.

Place, publisher, year, edition, pages
2019. , p. 51
Series
TRITA-EECS-EX ; 2019:804
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-271194OAI: oai:DiVA.org:kth-271194DiVA, id: diva2:1415975
Educational program
Master of Science - Systems, Control and Robotics
Examiners
Available from: 2020-03-20 Created: 2020-03-20 Last updated: 2020-03-20Bibliographically approved

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School of Electrical Engineering and Computer Science (EECS)
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4445464748495047 of 204
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