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Driving on Point Clouds: Motion Planning, Trajectory Optimization, and Terrain Assessment in Generic Nonplanar Environments

Authors:

Philipp Krüsi,

Roland SiegwartAuthors Info & Claims

Journal of Field Robotics, Volume 34, Issue 5

Pages 940 - 984

https://doi.org/10.1002/rob.21700

Published: 01 August 2017 Publication History

Abstract

We present a practical approach to global motion planning and terrain assessment for ground robots in generic three-dimensional 3D environments, including rough outdoor terrain, multilevel facilities, and more complex geometries. Our method computes optimized six-dimensional trajectories compliant with curvature and continuity constraints directly on unordered point cloud maps, omitting any kind of explicit surface reconstruction, discretization, or topology extraction. We assess terrain geometry and traversability on demand during motion planning, by fitting robot-sized planar patches to the map and analyzing the local distribution of map points. Our motion planning approach consists of sampling-based initial trajectory generation, followed by precise local optimization according to a custom cost measure, using a novel, constraint-aware trajectory optimization paradigm. We embed these methods in a complete autonomous navigation system based on localization and mapping by means of a 3D laser scanner and iterative closest point matching, suitable for both static and dynamic environments. The performance of the planning and terrain assessment algorithms is evaluated in offline experiments using recorded and simulated sensor data. Finally, we present the results of navigation experiments in three different environments-rough outdoor terrain, a two-level parking garage, and a dynamic environment, demonstrating how the proposed methods enable autonomous navigation in complex 3D terrain.

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cover image Journal of Field Robotics

Journal of Field Robotics Volume 34, Issue 5

August 2017

203 pages

ISSN:1556-4959

EISSN:1556-4967

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John Wiley and Sons Ltd.

United Kingdom

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Published: 01 August 2017

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https://dl.acm.org/doi/10.1109/TRO.2023.3344030
E. Carvalho AFerreira JPortugal D(2024)3D traversability analysis and path planning based on mechanical effort for UGVs in forest environmentsRobotics and Autonomous Systems10.1016/j.robot.2023.104560171:COnline publication date: 1-Jan-2024
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Chang ZZhou BZheng NFang FQian K(2023)Subpaving-Map: Fast Terrain Mapping for Outdoor Scenes based on Set-membership TheoryProceedings of the 2023 3rd International Conference on Robotics and Control Engineering10.1145/3598151.3598436(227-231)Online publication date: 12-May-2023
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Waibel GLöw TNass MHoward DBandyopadhyay TBorges P(2022)How Rough Is the Path? Terrain Traversability Estimation for Local and Global Path PlanningIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2022.315032823:9(16462-16473)Online publication date: 1-Sep-2022
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Chen JYu LWang W(2022)Hilbert Space Filling Curve Based Scan-Order for Point Cloud Attribute CompressionIEEE Transactions on Image Processing10.1109/TIP.2022.318653231(4609-4621)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1109/TIP.2022.3186532
Overbye TSaripalli S(2022)G-VOM: A GPU Accelerated Voxel Off-Road Mapping System2022 IEEE Intelligent Vehicles Symposium (IV)10.1109/IV51971.2022.9827107(1480-1486)Online publication date: 4-Jun-2022
https://dl.acm.org/doi/10.1109/IV51971.2022.9827107
Engelsons DTiger MHeintz F(2022)Coverage Path Planning in Large-scale Multi-floor Urban Environments with Applications to Autonomous Road Sweeping2022 International Conference on Robotics and Automation (ICRA)10.1109/ICRA46639.2022.9811941(3328-3334)Online publication date: 23-May-2022
https://dl.acm.org/doi/10.1109/ICRA46639.2022.9811941
Sánchez-Ibáñez JPérez-Del-Pulgar CSerón JGarcía-Cerezo A(2022)Optimal path planning using a continuous anisotropic model for navigation on irregular terrainsIntelligent Service Robotics10.1007/s11370-022-00450-616:1(19-32)Online publication date: 5-Dec-2022
https://dl.acm.org/doi/10.1007/s11370-022-00450-6
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