Accession Number : ADA618913


Title :   Physics-Aware Informative Coverage Planning for Autonomous Vehicles


Descriptive Note : Conference paper


Corporate Author : NAVAL RESEARCH LAB WASHINGTON DC NAVY CENTER FOR APPLIED RESEARCH IN ARTIFICIAL INTELLIGENCE


Personal Author(s) : Kuhlman, Michael J ; Svec, Petr ; Kaipa, Krishnanand N ; Sofge, Donald ; Gupta, Satyandra K


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a618913.pdf


Report Date : Jun 2014


Pagination or Media Count : 7


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.


Descriptors :   *SELF OPERATION , *STOCHASTIC CONTROL , *UNMANNED , *VEHICLES , ALGORITHMS , ARTIFICIAL INTELLIGENCE , AUTOMATION , COLLISION AVOIDANCE , COMPUTERIZED SIMULATION , DIGITAL MAPS , GAUSSIAN NOISE , LINEARITY , MARKOV PROCESSES , MONITORING , MULTISENSORS , PATHS , PLANNING , POSITION(LOCATION) , PROBABILITY , ROBOTICS , SHIP MOTION , TARGET DETECTION , UNCERTAINTY


Subject Categories : Statistics and Probability
      Cybernetics
      Underwater and Marine Navigation and Guidance
      Human Factors Engineering & Man Machine System


Distribution Statement : APPROVED FOR PUBLIC RELEASE