Unstructured with a Point: Validation and Robustness Evaluation of Point-Cloud Based Path Planning
Document Type
Technical Report
Publication Date
4-6-2021
Department
Department of Electrical and Computer Engineering
Abstract
Robust autonomous navigation in unstructured environments is an unsolved problem and critical to the operation of autonomous military and rescue ground vehicles. Two-dimensional path planners operating on occupancy grids or costs maps can produce infeasible paths when the operational area includes complex terrain. Recently, sample-based path planners that plan on LiDAR-acquired point-cloud maps have been proposed. These approaches require no discretization of the operational area and provide direct pose estimation by modeling vehicle and terrain interaction. In this paper, we show that direct sample-based path planning on point clouds is effective and robust in unstructured environments. Robustness is demonstrated by completing a system parameter sensitivity analysis of the system in an Unreal simulation environment and partnered with field validation.
Publication Title
SAE Technical Papers
Recommended Citation
Kysar, S.,
Bos, J.,
Kurup, A.,
Jeffries, Z.,
Carter, J.,
Majhor, C.,
Jayakumar, P.,
&
Smith, W.
(2021).
Unstructured with a Point: Validation and Robustness Evaluation of Point-Cloud Based Path Planning.
SAE Technical Papers.
http://doi.org/10.4271/2021-01-0251
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/14790