Perception and mapping for unmanned ground vehicles in unstructured environments
Cheng, Weihao
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Permalink
https://hdl.handle.net/2142/127459
Description
Title
Perception and mapping for unmanned ground vehicles in unstructured environments
Author(s)
Cheng, Weihao
Issue Date
2024-11-20
Director of Research (if dissertation) or Advisor (if thesis)
Norris, William R
Committee Member(s)
Hovakimyan , Naira
Department of Study
Mechanical Sci & Engineering
Discipline
Mechanical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Autonomous Vehicles
Perception
Negative Obstacle Detection
Sensor Fusion
LiDAR
Abstract
This research work presents a comprehensive study on enhancing the perception and mapping capabilities of Unmanned Ground Vehicles (UGVs) operating in unstructured environments. The key perception challenges addressed include effective ground segmentation, negative obstacle detection, and terrain traversability mapping, all crucial for enabling safe UGV navigation in complex terrains. First, this research work explores and implements state-of-the-art ground segmentation methods. Then, this work conducts theoretical analyses on LiDAR-based negative obstacle detection and proposes a novel detection and mapping method. Additionally, a multi-modal terrain traversability mapping method is explored and implemented in this work. This multi-modal method integrates elevation data and visual information for more accurate terrain traversability mapping. The proposed techniques are tested on several autonomous platforms, demonstrating potential improvements in perception and mapping. Overall, the preliminary results are promising and provide great insights into future research to enhance UGV’s perception capabilities in hazardous environments.
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