Improving the understanding of navigational commands by adapting a robot’s directional perception based on the environment

Article type: Research Article

Authors: Muthugala, M.A. Viraj J.^{; *} | Jayasekara, A.G. Buddhika P.

Affiliations: Intelligent Service Robotics Group, Department of Electrical Engineering, University of Moratuwa, Sri Lanka. E-mails: muthugala@ieee.org, buddhikaj@uom.lk

Correspondence: [*] Corresponding author. E-mail: muthugala@ieee.org.

Abstract: Intelligent service robots are being developed for emerging areas of robotics applications. Human-friendly interactive features are preferred for these service robots since these robots are anticipated to be operated by non-experts. Humans prefer to use voice instructions for exchanging the ideas between peers. Such voice instructions often include distance and direction related language descriptors that are fuzzy in nature. Therefore, these service robots must be capable of interpreting the meaning of such fuzzy notions in language instructions in order to enhance the rapport between the robots and their users. This paper proposes a method to interpret the directional notions in motional and positional navigational commands by considering the fuzziness associated with linguistic notions. A fuzzy inference system has been developed in order to adapt a robot’s perception of fuzzy directional notions based on the environment. This adaptation is realized by weighting the output membership function with the distribution of free space around the robot or a reference object. Experiments have been conducted in an artificially created domestic environment with heterogeneous characteristics. According to the experimental results, the proposed system is capable of enhancing the understanding of navigational commands with fuzzy notions.

Keywords: Understanding of fuzzy language notions, human–robot interactions, human-friendly robotics, service robotics, social robotics

DOI: 10.3233/AIS-190517

Journal: Journal of Ambient Intelligence and Smart Environments, vol. 11, no. 2, pp. 135-148, 2019