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경유지의 가시성을 고려한 2차원 라이다 센서 기반의 실용적인 경로 계획 프레임워크

Practical Path-planning Framework Considering Waypoint Visibility for Indoor Autonomous Navigation using Two-dimensional LiDAR Sensors

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주제분류공학일반

초록

Path-planning, a critical component of mobile robot navigation, comprises both local and global planning. Previous studies primarilyfocused on enhancing the individual performance of these planners, avoiding obstacles, and computing an optimal global path from astarting position to a target position. In this study, we introduce a practical path-planning framework that employs a target planner tobridge the local and global planners; this enables mobile robots to navigate seamlessly and efficiently toward a global target position. The proposed target planner assesses the visibility of waypoints along the global path, and it selects a reachable navigation target, whichcan then be used to generate efficient control commands for the local planners. A visibility-based target planner can handle situations,wherein the current, target waypoint is occupied by unknown obstacles. Real-world experiments demonstrated that the proposed pathplanning framework with the visibility-based target planner allowed the robot to navigate to the final target position along a more efficient path than the framework without a target planner.

Abstract

Path-planning, a critical component of mobile robot navigation, comprises both local and global planning. Previous studies primarilyfocused on enhancing the individual performance of these planners, avoiding obstacles, and computing an optimal global path from astarting position to a target position. In this study, we introduce a practical path-planning framework that employs a target planner tobridge the local and global planners; this enables mobile robots to navigate seamlessly and efficiently toward a global target position. The proposed target planner assesses the visibility of waypoints along the global path, and it selects a reachable navigation target, whichcan then be used to generate efficient control commands for the local planners. A visibility-based target planner can handle situations,wherein the current, target waypoint is occupied by unknown obstacles. Real-world experiments demonstrated that the proposed pathplanning framework with the visibility-based target planner allowed the robot to navigate to the final target position along a more efficient path than the framework without a target planner.

참고문헌 (16)

  1. R. Siegwart, "Introduction to Autonomous Mobile Robots", pp.369~422 (2011), The MIT Press
  2. K. Fransen, "Efficient path planning for automated guided vehicles using A* (Astar) algorithm incorporating turning costs in search heuristic", Int. J. Prod. Res., 61(3), pp.707~725 (2021)
  3. S. Karaman, "Sampling-based algorithms for optimal motion planning", Int. J. Rob. Res., 30(7), pp.846~894 (2011)
  4. S. Li, "A sampling and learning frame-work to prove motion planning infeasibility", Int. J. Rob. Res., 42(10), pp.938~956 (2023)
  5. S. M. LaValle, "Randomized kinodynamic planning", Int. J. Rob. Res., 20(5), pp.378~400 (2001)
  6. J. D. Gammell, "Informed RRT* : Optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic", Proc. of 2014 IEEE, 2014, 2997~3004
  7. D. Fox, "The dynamic window approach to collision avoidance", IEEE Robot. Autom. Mag., 4(1), pp.23~33 (1997)
  8. L. Chang, "Reinforcement based mobile robot path planning with improved dynamic window approach in unknown environment", Auton. Robots, 45(1), pp.51~76 (2021)
  9. J. Minguez, "Nearness diagram (ND) navigation: Collision avoidance in troublesome scenarios", IEEE Trans. Rob. Autom., 20(1), pp.45~59 (2004)
  10. J. W. Durham, "Smooth Nearness-Diagram Navigation", Proc. of IEEE, 2008, 690~695
  11. Y. Li, "A mobile robot path planning algorithm based on improved A* algorithm and dynamic window approach", IEEE Access, 10, pp.57736~57747 (2022)
  12. H. Ryu, "Improved informed RRT* using grid-map skeletonization for mobile robot path planning", Int. J. Precision Eng. Manuf., 20(11), pp.2033~2039 (2019)
  13. H. Ryu, "Hierarchical path-planning for mobile robots using a skeletonization-informed rapidly exploring random tree", Appl. Sci., 10(21), pp.7846(1)~7846(18) (2020)
  14. J. -L. Blanco, "Optimal filtering for non-parametric observation models : Applications to localization and SLAM", Int. J. Rob. Res., 29(14), pp.1726~1742 (2010)
  15. W. Hess, "Real-time loop closure in 2d lidar slam", Proc. of 2016 IEEE Int. Conf. Robot. Autom. (ICRA), pp.1271~1278 (2016)

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