The Autonomous City Explorer (ACE) project combines research from autonomous outdoor navigation and human-robot interaction. The ACE robot is capable of navigating unknown urban environments without the use of GPS data or prior map knowledge. It finds its way by interacting with pedestrians in a natural and intuitive way and building a topological representation of its surroundings. In a recent experiment the robot managed to successfully travel a 1.5 km distance from the campus of the Technische Universität München to Marienplatz, the central square of Munich.This article describes the principles and system components for navigation in urban environments, information retrieval through natural human-robot interaction, the construction of a suitable semantic representation as well as results from the field experiment.
In this paper we describe the design and control algorithms of AMOUR, a low-cost autonomous underwater vehicle (AUV) capable of missions of marine survey and monitoring. AMOUR is a highly maneuverable robot capable of hovering and carrying dynamic payloads during a single mission. The robot can carry a variety of payloads. It uses internal buoyancy and balance control mechanisms to achieve power efficient motions regardless of the payload size. AMOUR is designed to operate in synergy with a wireless underwater sensor network (WUSN) of static nodes. The robot's payload was designed in order to deploy, relocate and recover the static sensor nodes. It communicates with the network acoustically for signaling and localization and optically for data muling. We present control algorithms, navigation algorithms, and experimental data from pool and ocean trials with AMOUR that demonstrate its basic navigation capabilities, power efficiency, and ability to carry dynamic payloads.
Abstract-This paper describes a new methodological approach and robot system to trigger more prosocial human reactions towards a robot by transferring social-psychological principles from human-human interaction to human-robot interaction (HRI). The main idea is to trigger increased helpfulness by proactively creating similarity through dynamic emotional adaption of the robot to the mood of the human. This is achieved in an explicit and implicit way: Explicitly, by a similarity-statement of the robot of being in the same mood as the user, and implicitly by controlling the affective parameters of facial and verbal expressions of a robot head in an interaction scenario such that the current values of the human mood in the dimensions of pleasure, arousal, and dominance (PAD) are matched. In a first step, this is accomplished by an initial self-assessment by the human participant to be extended by automatic emotion recognition modules in a later stage. The effectiveness of the approach is confirmed by significant experimental results.
In this paper, the impact of facial expressions on HRI is explored_ To determine their influence on empathy of a human towards a robot and perceived subjective performance, an experimental setup is created, in which participants engage in a dialog with the robot head EDDIE. The web-based gaming application "Akinator" serves as a backbone for the dialog structure. In this game, the robot tries to guess a thought of person chosen by the human by asking various questions about the person. In our experimental evaluation, the robot reacts in various ways to the human's facial expressions, either ignoring them, mirroring them, or displaying its own facial expression based on a psychological model for social awareness.In which way this robot behavior influences human perception of the interaction is investigated by a questionnaire. Our results support the hypothesis that the robot behavior during interaction heavily influences the extent of empathy by a human towards a robot and perceived subjective task-performance, with the adaptive modes clearly leading compared to the non adaptive mode.
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