Low Size, Weight, Power, and Cost (SWaP-C) Payload for Autonomous Navigation and Mapping on an Unmanned Ground Vehicle

Abstract

Autonomous navigation and unknown environment exploration with an unmanned ground vehicle (UGV) is extremely challenging. This report investigates a mapping and exploration solution utilizing low size, weight, power, and cost payloads. The platform presented here leverages simultaneous localization and mapping to efficiently explore unknown areas by finding navigable routes. The solution utilizes a diverse sensor payload that includes wheel encoders, 3D lidar, and red-green-blue and depth cameras. The main goal of this effort is to leverage path planning and navigation for mapping and exploration with a UGV to produce an accurate 3D map. The solution provided also leverages the Robot Operating System.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2023
Accession Number
AD1213595

Entities

People

  • Brandon M. Dodd
  • Charles C. Ellison
  • Garry P. Glaspell
  • Michael A. Paquette
  • Osama Ennasr

Organizations

  • Engineer Research and Development Center

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Autonomous Navigation
  • Autonomous Systems
  • Collision Avoidance
  • Control Systems
  • Detection
  • Detectors
  • Engineers
  • Ground Vehicles
  • Laser Radar
  • Motion Planning
  • Navigation
  • Operating Systems
  • Particle Swarm Optimization
  • Robot Mapping
  • Robotics
  • Robots
  • Simultaneous Localization And Mapping
  • Unmanned Ground Vehicles

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Integrated Circuit Design and Technology.
  • Robotics and Automation.

Technology Areas

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