Publication:
Automatic Waypoint Generation to Improve Robot Navigation Through Narrow Spaces

dc.contributor.authorMoreno, Francisco-Angel
dc.contributor.authorMonroy, Javier
dc.contributor.authorRuiz-Sarmiento, Jose-Raul
dc.contributor.authorGalindo, Cipriano
dc.contributor.authorGonzalez-Jimenez, Javier
dc.contributor.authoraffiliation[Moreno,FA; Monroy,J; Ruiz-Sarmiento,JR; Galindo,C; Gonzalez-Jimenez,J] Machine Perception and Intelligent Robotics Group (MAPIR), Dept. of System Engineering and Automation Biomedical Research Institute of Malaga (IBIMA), University of Malaga, Málaga, Spain.
dc.date.accessioned2024-02-10T20:02:48Z
dc.date.available2024-02-10T20:02:48Z
dc.date.issued2019-12-31
dc.description.abstractIn domestic robotics, passing through narrow areas becomes critical for safe and effective robot navigation. Due to factors like sensor noise or miscalibration, even if the free space is sufficient for the robot to pass through, it may not see enough clearance to navigate, hence limiting its operational space. An approach to facing this is to insert waypoints strategically placed within the problematic areas in the map, which are considered by the robot planner when generating a trajectory and help to successfully traverse them. This is typically carried out by a human operator either by relying on their experience or by trial-and-error. In this paper, we present an automatic procedure to perform this task that: (i) detects problematic areas in the map and (ii) generates a set of auxiliary navigation waypoints from which more suitable trajectories can be generated by the robot planner. Our proposal, fully compatible with the robotic operating system (ROS), has been successfully applied to robots deployed in different houses within the H2020 MoveCare project. Moreover, we have performed extensive simulations with four state-of-the-art robots operating within real maps. The results reveal significant improvements in the number of successful navigations for the evaluated scenarios, demonstrating its efficacy in realistic situations.
dc.description.sponsorshipThis work has been supported by the research projects WISER (DPI2017-84827-R), funded by the Spanish Government and the European Regional Development’s Funds (FEDER), MoveCare (ICT-26-2016b-GA-732158), funded by the European H2020 program, and by a postdoc contract from the I-PPIT program of the University of Malaga. The publication of this paper has been funded by the University of Malaga.
dc.identifier.doi10.3390/s20010240
dc.identifier.e-issn1424-8220es_ES
dc.identifier.journalSensorses_ES
dc.identifier.otherhttp://hdl.handle.net/10668/4419
dc.identifier.pubmedID31906184es_ES
dc.identifier.urihttp://hdl.handle.net/20.500.12105/17950
dc.language.isoeng
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)
dc.relation.publisherversionhttps://www.mdpi.com/1424-8220/20/1/240/htmes
dc.rights.accessRightsopen accesses_ES
dc.rights.licenseAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectMobile robots
dc.subjectRobot navigation
dc.subjectRobot localization
dc.subjectRobot deployment
dc.subjectWaypoint generation
dc.subjectNavigation assistant
dc.subjectArtificial Intelligence
dc.subjectMap
dc.subjectInteligencia artificial
dc.subjectMapa
dc.subjectRobótica
dc.subject.meshHumans
dc.subject.meshRobotics
dc.subject.meshReactive Oxygen Species
dc.subject.meshArtificial Intelligence
dc.subject.meshAlgorithms
dc.titleAutomatic Waypoint Generation to Improve Robot Navigation Through Narrow Spaces
dc.typeresearch article
dc.type.hasVersionVoR
dspace.entity.typePublication
relation.isPublisherOfPublication30293a55-0e53-431f-ae8c-14ab01127be9
relation.isPublisherOfPublication.latestForDiscovery30293a55-0e53-431f-ae8c-14ab01127be9

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