Unmanned Ground Vehicle (UGV) Full Coverage Planning with Negative Obstacles

Abstract

We explored approaches that offer full coverage path planning while simultaneously avoiding negative obstacles. These approaches are specific to unmanned ground vehicles (UGVs), which need to constantly interact with a traversable ground surface. We tested multiple potential solutions in simulation, and the results are presented herein. Full coverage path planner (FCPP) approaches were evaluated based on their ability to discretize their paths, use waypoints effectively, and be easily integrated with our current robot platform. For negative obstacles, we explored approaches that will integrate with our current navigation stack. The preferred solution will allow for teleoperation, waypoint navigation, and full autonomy while avoiding positive and negative obstacles.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2023
Accession Number
AD1209288

Entities

People

  • Ahmet Soylemezoglu
  • Amir Naser
  • Garry Glaspell
  • Jin-kyu Lee
  • Osama Ennasr

Organizations

  • Engineer Research and Development Center

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Autonomous Navigation
  • Autonomous Systems
  • Autonomy
  • Change Detection
  • Control Systems
  • Department Of Defense
  • Detection
  • Detectors
  • Ecology
  • Elevation
  • Engineering
  • Engineers
  • Ground Vehicles
  • Military Engineering
  • Motion Planning
  • Navigation
  • Robotics
  • Robots
  • Simulations
  • Unmanned Ground Systems
  • Unmanned Ground Vehicles
  • Visualizations

Readers

  • Robotics and Automation.
  • Systems Analysis and Design
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy