Open Access
Volume 40, Number 3, June 2022
Page(s) 708 - 716
Published online 19 September 2022
  1. YAMAUCHI B. A frontier-based approach for autonomous exploration[C]//IEEE International Symposium on Computational Intelligence in Robotics and Automation, 1997: 146–151 [Google Scholar]
  2. ZHOU B, ZHANG Y, CHEN X, et al. FUEL: fast UAV exploration using incremental frontier structure and hierarchical planning[J]. IEEE Robotics and Automation Letters, 2021, 6(2): 779–786. [Article] [CrossRef] [Google Scholar]
  3. GOMEZ C, HERNANDEZ A C, BARBER R. Topological frontier-based exploration and map-building using semantic informa-tion[J]. Sensors, 2019, 19(20): 4595. [Article] [CrossRef] [Google Scholar]
  4. FARIA M, MAZA I, VIGURIA A. Applying frontier cells based exploration and lazy theta* path planning over single grid-based world representation for autonomous inspection of large 3D structures with an UAS[J]. Journal of Intelligent & Robotic Systems, 2019, 93(1/2): 113–133 [CrossRef] [Google Scholar]
  5. UMARI H, MUKHOPADHYAY S. Autonomous robotic exploration based on multiple rapidly-exploring randomized trees[C]//2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017: 1396–1402 [Google Scholar]
  6. QIAO W, FANG Z, SI B. A sampling-based multi-tree fusion algorithm for frontier detection[J]. International Journal of Advanced Robotic Systems, 2019, 16(4): 1–14 [NASA ADS] [Google Scholar]
  7. BIRCHER A, KAMEL M, ALEXIS K, et al. Receding horizon "next-best-view" planner for 3D exploration[C]//2016 IEEE International Conference on Robotics and Automation, 2016: 1462–1468 [CrossRef] [Google Scholar]
  8. DORNHEGE C, KLEINER A. A frontier-void-based approach for autonomous exploration in 3d[J]. Advanced Robotics, 2013, 27(6): 459–468. [Article] [CrossRef] [Google Scholar]
  9. IBRAHIM M F, HUDDIN A B, ZAMAN M H M, et al. An enhanced frontier strategy with global search target-assignment approach for autonomous robotic area exploration[J]. International Journal of Advanced Technology and Engineering Exploration, 2021, 8(75): 283–291. [Article] [CrossRef] [Google Scholar]
  10. LIANG L, REDONDO C, CAMPOY P. Optimal frontier-based autonomous exploration in unconstructed environment using RGB-D sensor[J]. Sensors, 2020, 20(22): 6507. [Article] [NASA ADS] [CrossRef] [Google Scholar]
  11. BATINOVIC A, PETROVIC T, IVANOVIC A, et al. A multi-resolution frontier-based planner for autonomous 3D exploration[J]. IEEE Robotics and Automation Letters, 2021, 6(3): 4528–4535. [Article] [CrossRef] [Google Scholar]
  12. FANG B, DING J, WANG Z. Autonomous robotic exploration based on frontier point optimization and multistep path planning[J]. IEEE Access, 2019, 7: 46104–46113. [Article] [CrossRef] [Google Scholar]
  13. CIESLEWSKI T, KAUFMANN E, SCARAMUZZA D. Rapid exploration with multi-rotors: a frontier selection method for high speed flight[C]//2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017: 2135–2142 [Google Scholar]
  14. HORNUNG A, WURM K M, BENNEWITZ M, et al. OctoMap: an efficient probabilistic 3D mapping framework based on octrees[J]. Autonomous Robots, 2013, 34(3): 189–206 [CrossRef] [Google Scholar]
  15. FURRER F, BURRI M, ACHTELIK M, et al. Robot Operating System(ROS)[M]. Cham, Springer, 2016: 595–625 [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.