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    Physiological Data-Based Evaluation of a Social Robot Navigation System
    (Ieee, 2020) Kivrak, Hasan; Uluer, Pinar; Kose, Hatice; Gumuslu, Elif; Barkana, Duygun Erol; Cakmak, Furkan; Yavuz, Sirma
    The aim of this work is to create a social navigation system for an affective robot that acts as an assistant in the audiology department of hospitals for children with hearing impairments. Compared to traditional navigation systems, this system differentiates between objects and human beings and optimizes several parameters to keep at a social distance during motion when faced with humans not to interfere with their personal zones. For this purpose, social robot motion planning algorithms are employed to generate human-friendly paths that maintain humans' safety and comfort during the robot's navigation. This paper evaluates this system compared to traditional navigation, based on the surveys and physiological data of the adult participants in a preliminary study before using the system with children. Although the self-report questionnaires do not show any significant difference between navigation profiles of the robot, analysis of the physiological data may be interpreted that, the participants felt comfortable and less threatened in social navigation case.
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    Social navigation framework for assistive robots in human inhabited unknown environments
    (Elsevier - Division Reed Elsevier India Pvt Ltd, 2021) Kivrak, Hasan; Cakmak, Furkan; Kose, Hatice; Yavuz, Sirma
    In human-populated environments, robot navigation requires more than mere obstacle avoidance for safe and comfortable human-robot interaction. Socially aware navigation approaches become vital for deploy-ing mobile service robots in human interactive environments, where the robot operates in interaction with human implicitly or explicitly. These approaches aim to generate human-friendly paths in human-robot interactive environments considering social cues and human behaviour patterns. This paper proposes a social navigation framework for mobile service robots, maintaining humans' safety and comfort while navigating towards the goal location in human interactive environments. Our main contribution is that the presented social navigation framework is designed to be used in human interac-tive unknown environments. To achieve this goal, we use a variant of a pedestrian model called Collision Prediction based Social Force model (CP-SFM). This model is particularly developed for low or average density environments and takes the motion of the people tracked in the environment into account during the navigation. The model is employed as a local planner to generate human-friendly plausible routes for our service robot in corridor like indoor environment scenarios. A variety of different extensions and improvements of the conventional social force model are employed in the implementation stage. A novel improvement in producing multi-level mapping, identifying obstacle repulsion points and adopting CP-SFM for application in motion planning as local task solver is presented. The whole framework has been implemented as ROS nodes, and tested both in real world and simulation environments and successfully verified based on the obtained results. (C) 2020 Karabuk University. Publishing services by Elsevier B.V.
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    Waypoint based path planner for socially aware robot navigation
    (Springer, 2022) Kivrak, Hasan; Cakmak, Furkan; Kose, Hatice; Yavuz, Sirma
    Social navigation is beneficial for mobile robots in human inhabited areas. In this paper, we focus on smooth path tracking and handling disruptions during plan execution in social navigation. We extended the social force model (SFM)-based local planner to achieve smooth and effective social path following. The SFM-based local motion planner is used with the A* global planner, to avoid getting stuck in local minima, while incorporating social zones for human comfort. It is aimed at providing smooth path following and reducing the number of unnecessary re-plannings in evolving situations and a waypoint selection algorithm is proposed. The whole plan is not directly assigned to the robot since the global path has too many grid nodes and it is not possible to follow the path easily in such a dynamic and uncertain environment inhabitated by humans. Therefore, the extracted waypoints by the proposed waypoint selection algorithm are incrementally sent to the robot for smooth and legible robot navigation behavior. A corridor like scenario is tested in a simulated environment for the evaluation of the system and the results demonstrated that the proposed method can create paths that respect people's social space while also eliminating unnecessary replanning and providing that plans are carried out smoothly. The study presented an improvement in the number of replannings, path execution time, path length, and path smoothness of 90.4%, 53.7%, 8.3%, 55, 2%, respectively.