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Formation Obstacle Avoidance using RRT and Constraint Based Programming
KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0002-0483-8391
KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
2017 (English)In: 2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR), IEEE conference proceedings, 2017, 8088131Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we propose a new way of doing formation obstacle avoidance using a combination of Constraint Based Programming (CBP) and Rapidly Exploring Random Trees (RRTs). RRT is used to select waypoint nodes, and CBP is used to move the formation between those nodes, reactively rotating and translating the formation to pass the obstacles on the way. Thus, the CBP includes constraints for both formation keeping and obstacle avoidance, while striving to move the formation towards the next waypoint. The proposed approach is compared to a pure RRT approach where the motion between the RRT waypoints is done following linear interpolation trajectories, which are less computationally expensive than the CBP ones. The results of a number of challenging simulations show that the proposed approach is more efficient for scenarios with high obstacle densities.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2017. 8088131
Keyword [en]
Constraint Based Programming, RRT, formation keeping, obstacle avoidance, path-planning
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-198606DOI: 10.1109/SSRR.2017.8088131Scopus ID: 2-s2.0-85040244103ISBN: 9781538639221 OAI: oai:DiVA.org:kth-198606DiVA: diva2:1171687
Conference
2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR), Shanghai, October 11-13, 2017
Projects
TRADR
Funder
EU, FP7, Seventh Framework Programme, FP7-ICT-609763
Note

QC 20180109

Available from: 2018-01-08 Created: 2018-01-08 Last updated: 2018-01-18Bibliographically approved

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Båberg, FredrikPetter, Ögren
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Output format
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