Adaptive haptic shared control framework using markov decision processing

Amir H. Ghasemi, Hossein Rastgoftar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

Semi-autonomous steering promises to combine the best of human perception, planning, and manual control with the precision of automatic control. This paper presents an adaptive haptic shared control scheme using Markov Decision Process (MDP) to keep human drivers in the loop yet free attention and avoid automation pitfalls. Using MDP, algorithms are developed to support the negotiation of authority between the human driver and automation system.

Original languageEnglish (US)
Title of host publicationModeling and Validation; Multi-Agent and Networked Systems; Path Planning and Motion Control; Tracking Control Systems; Unmanned Aerial Vehicles (UAVs) and Application; Unmanned Ground and Aerial Vehicles; Vibration in Mechanical Systems; Vibrations and Control of Systems; Vibrations
Subtitle of host publicationModeling, Analysis, and Control
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791851913
DOIs
StatePublished - 2018
Externally publishedYes
EventASME 2018 Dynamic Systems and Control Conference, DSCC 2018 - Atlanta, United States
Duration: Sep 30 2018Oct 3 2018

Publication series

NameASME 2018 Dynamic Systems and Control Conference, DSCC 2018
Volume3

Conference

ConferenceASME 2018 Dynamic Systems and Control Conference, DSCC 2018
Country/TerritoryUnited States
CityAtlanta
Period9/30/1810/3/18

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

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