Ladar-Based Vehicle Detection and Tracking in Cluttered Environments

Abstract

Detecting and tracking vehicles is crucial for safe operation of Unmanned Ground Vehicles (UGVs), but is challenging in cluttered, real-world environments. Here we present a method for discriminating vehicles from clutter found in natural terrain such as foliage, steep slopes, rock-outcrops, etc. Our method relies on a scanning LADAR and combines an obstacle detector and tracker, a vehicle modeling scheme, and a Support Vector-based discriminator. The output of our real-time system is a list of labeled obstacles and vehicles along with their positions, sizes and velocity estimates. This is used by a planner to enable autonomous navigation in the presence of other vehicles and significant clutter. We provide a quantitative analysis of the performance of our algorithm.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2008
Accession Number
ADA504090

Entities

People

  • Daniel Morris
  • Regis Hoffman
  • Steve Mclean

Organizations

  • General Dynamics

Tags

Communities of Interest

  • Autonomy
  • Sensors

DTIC Thesaurus Topics

  • Autonomous Navigation
  • Autonomous Vehicles
  • Coordinate Systems
  • Detection
  • Detectors
  • Environment
  • Ground Vehicles
  • Navigation
  • Orientation (Direction)
  • Pattern Recognition
  • Supervised Machine Learning
  • Three Dimensional
  • Unmanned Ground Vehicles
  • Unmanned Vehicles
  • Urban Areas
  • Vehicles

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Robotics and Automation.

Technology Areas

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