Home alone: autonomous extension and correction of spatial representations

In this paper we present an account of the problems faced by a mobile robot given an incomplete tour of an unknown environment, and introduce a collection of techniques which can generate successful behaviour even in the presence of such problems. Underlying our approach is the principle that an autonomous system must be motivated to act to gather new knowledge, and to validate and correct existing knowledge. This principle is embodied in Dora, a mobile robot which features the aforementioned techniques: shared representations, non-monotonic reasoning, and goal generation and management. To demonstrate how well this collection of techniques work in real-world situations we present a comprehensive analysis of the Dora system’s performance over multiple tours in an indoor environment. In this analysis Dora successfully completed 18 of 21 attempted runs, with all but 3 of these successes requiring one or more of the integrated techniques to recover from problems

ToBI-Team of Bielefeld The Human-Robot Interaction System for RoboCup@Home 2015

Meyer zu Borgsen S, Korthals T, Ziegler L, Wachsmuth S. ToBI-Team of Bielefeld The Human-Robot Interaction System for RoboCup@Home 2015. Presented at the RoboCup 2015, Hefei, China

ToBI - Team of Bielefeld: The Human-Robot Interaction System for RoboCup@Home 2014

Ziegler L, Wittrowski J, Meyer zu Borgsen S, Wachsmuth S. ToBI - Team of Bielefeld: The Human-Robot Interaction System for RoboCup@Home 2014. Presented at the RoboCup 2014, João Pessoa, Brasil

ToBI-Team of Bielefeld The Human-Robot Interaction System for RoboCup@Home 2015

Meyer zu Borgsen S, Korthals T, Ziegler L, Wachsmuth S. ToBI-Team of Bielefeld The Human-Robot Interaction System for RoboCup@Home 2015. Presented at the RoboCup 2015, Hefei, China

ToBI-Team of Bielefeld The Human-Robot Interaction System for RoboCup@Home 2016

Meyer zu Borgsen S, Korthals T, Wachsmuth S. ToBI-Team of Bielefeld The Human-Robot Interaction System for RoboCup@Home 2016. Presented at the RoboCup, Leipzig, Germany

Investigating the influence of situations and expectations on user behavior : empirical analyses in human-robot interaction

Lohse M. Investigating the influence of situations and expectations on user behavior : empirical analyses in human-robot interaction. Bielefeld (Germany): Bielefeld University; 2010.Social sciences are becoming increasingly important for robotics research as work goes on to enable service robots to interact with inexperienced users. This endeavor can only be successful if the robots learn to interpret the users' behavior reliably and, in turn, provide feedback for the users, which enables them to understand the robot. In order to achieve this goal, the thesis introduces an approach to describe the interaction situation as a dynamic construct with different levels of specificity. The situation concept is the starting point for a model which aims to explain the users' behavior. The second important component of the model is the expectations of the users with respect to the robot. Both the situation and the expectations are shown to be the main determinants of the users' behaviors. With this theoretical background in mind, the thesis examines interactions from a home tour scenario in which a human teaches a robot about rooms and objects within them. To analyze the human expectations and behaviors in this situation, two main novel methods have been developed. In particular, a quantitative method for the analysis of the users' behavior repertoires (speech, gesture, eye gaze, body orientation, etc.) is introduced. The approach focuses on the interaction level, which describes the interplay between the robot and the user. In the second novel method, also the system level is taken into account, which includes the robot components and their interplay. This method serves for a detailed task analysis and helps to identify problems that occur in the interaction. By applying these methods, the thesis contributes to the identification of underlying expectations that allow future behavior of the users to be predicted in particular situations. Knowledge about the users' behavior repertoires serves as a cue for the robot about the state of the interaction and the task the users aim to accomplish. Therefore, it enables robot developers to adapt the interaction models of the components to the situation, actual user expectations, and behaviors. The work provides a deeper understanding of the role of expectations in human-robot interaction and contributes to the interaction and system design of interactive robots

Systemic interaction analysis (SInA) in HRI

Recent developments in robotics enable advanced human-robot interaction. Especially interactions of novice users with robots are often unpredictable and, therefore, demand for novel methods for the analysis of the interaction in systemic ways. We propose Systemic Interaction Analysis (SInA) as a method to jointly analyze system level and interaction level in an integrated manner using one tool. The approach allows us to trace back patterns that deviate from prototypical interaction sequences to the distinct system components of our autonomous robot. In this paper, we exemplarily apply the method to the analysis of the follow behavior of our domestic robot BIRON. The analysis is the basis to achieve our goal of improving human-robot interaction iteratively