Adaptive Sampling-based View Planning under Time Constraints

Lars Kunze, Mohan Sridharan, Christos Dimitrakakis, Jeremy Wyatt

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Planning for object search requires the generation and sequencing of views in a continuous space. These plans need to consider the effect of overlapping views and a limit imposed on the time taken to compute and execute the plans. We formulate the problem of view planning in the presence of overlapping views and time constraints as an Orienteering Problem with history-dependent rewards. We consider two variants of this problem—in variant (I) only the plan execution time is constrained, whereas in variant (II) both planning and execution time are constrained. We abstract away the unreliability of perception, and present a sampling-based view planner that simultaneously selects a set of views and a route through them, and incorporates a prior over object locations. We show that our approach outperforms the state of the art methods for the orienteering problem by evaluating all algorithms in four environments that vary in size and complexity.
Original languageEnglish
Title of host publicationProceedings of 2017 European Conference on Mobile Robotics (ECMR 2017)
PublisherIEEE Computer Society Press
ISBN (Electronic)9781538610961
ISBN (Print)9781538610978
Publication statusPublished - 9 Nov 2017
Event2017 European Conference on Mobile Robots (ECMR) - Paris , France
Duration: 6 Sept 20178 Sept 2017


Conference2017 European Conference on Mobile Robots (ECMR)
Abbreviated titleECMR 2017


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