Physics-Aware Informative Coverage Planning for Autonomous Vehicles

Abstract

Unmanned vehicles are emerging as an attractive tool for persistent monitoring tasks of a given area, but need automated planning capabilities for effective unattended deployment. Such an automated planner needs to generate collision-free coverage paths by steering waypoints to locations that both minimize the path length and maximize the amount of information gathered along the path. The approach presented in this paper significantly extends prior work and handles motion uncertainty of an unmanned vehicle and the presence of obstacles by using a Markov Decision Process based approach to generate collision-free paths. Simulation results show that the proposed approach is robust to significant motion uncertainties and reduces the probability of collision with obstacles in the environment.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2014
Accession Number
ADA618913

Entities

People

  • Donald Sofge
  • Krishnanand N. Kaipa
  • Michael J. Kuhlman
  • Petr Švec
  • Satyandra K. Gupta

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Autonomous Systems
  • Autonomous Vehicles
  • Collisions
  • Engineering
  • Environment
  • Mechanical Engineering
  • Monitoring
  • Motion Planning
  • Probability
  • Simulations
  • Uncertainty
  • Unmanned
  • Unmanned Surface Vehicles
  • Unmanned Vehicles
  • Vehicles

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Vision.
  • Operations Research

Technology Areas

  • Autonomy