Human--robot interaction (HRI) is studied in two important research areas, intention estimation and intention reshaping. Although there are many studies in the literature that define human intention, new research examines the reshaping of human intentions by using robots in HRI. In this paper, 2 different robot movements are tested in a real environment in order to reshape current human intention. The hidden Markov model (HMM) is used to estimate human intention in our intelligent robotic system. The algorithmic design of the system comprises 2 parts: the first part tracks the moving objects in the environment, and the second part estimates human intention and reshapes the estimated current human intention by using intelligent robots. In the first part, a feature vector consisting of the headings of the human posture and the locations of the humans and robots is created by using video processing techniques. The second part is related to estimating the current intention of a human participant via HMM models and to reshaping the current intention into another intention. The system is tested in a real experimental environment including humans and robots, and the results in the recorded videos are given at the end of the paper.
Human--robot interaction, intention estimation, intention reshaping, hidden Markov models
DURDU, AKİF; ERKMEN, İSMET; and ERKMEN, AYDAN MÜŞERREF
"Estimating and reshaping human intention via human--robot interaction,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 24:
1, Article 8.
Available at: https://journals.tubitak.gov.tr/elektrik/vol24/iss1/8