A Survey on Human-aware Robot Navigation

Intelligent systems are increasingly part of our everyday lives and have been integrated seamlessly to the point where it is difficult to imagine a world without them. Physical manifestations of those systems on the other hand, in the form of embodied agents or robots, have so far been used only for specific applications and are often limited to functional roles (e.g. in the industry, entertainment and military fields). Given the current growth and innovation in the research communities concerned with the topics of robot navigation, human-robot-interaction and human activity recognition, it seems like this might soon change. Robots are increasingly easy to obtain and use and the acceptance of them in general is growing. However, the design of a socially compliant robot that can function as a companion needs to take various areas of research into account. This paper is concerned with the navigation aspect of a socially-compliant robot and provides a survey of existing solutions for the relevant areas of research as well as an outlook on possible future directions.Comment: Robotics and Autonomous Systems, 202

Application of Fuzzy Techniques in Human-Robot Interaction - A Review

Targeting research challenges in Socially Assistive Robotics (SAR), this paper provides a review of previous work that describe robot or non-robot systems that use fuzzy logic to infer high-level human intention or activities. In comparison to statistical and probabilistic approaches which are very popular in SAR and Human-Robot Interaction (HRI), this review focuses on fuzzy logic-based systems. As fuzzy logic has already been widely used in almost all research areas in robotics, this review does not consider systems that uses fuzzy logic for sensing, modelling or planning tasks except for inferencing or reasoning tasks. From this review, it was found minimal research has been done in this special research niche and is deemed to gain more attention as the research communities shifts from sensing toward modelling and inferencing in the loop of Sense-Model-Plan-Act or Sense-Plan-Act