ToBI - Team of Bielefeld A Human-Robot Interaction System for RoboCup@Home 2017

Wachsmuth S, Lier F, Meyer zu Borgsen S, Kummert J, Lach L, Sixt D. ToBI - Team of Bielefeld A Human-Robot Interaction System for RoboCup@Home 2017. Presented at the RoboCup 2017, Nagoya.The Team of Bielefeld (ToBI) has been founded in 2009. The RoboCup teams’ activities are embedded in a long-term research agenda towards human-robot interaction with laypersons in regular and smart home environments. The RoboCup@Home competition is an im- portant benchmark and milestone for this goal in terms of robot capabilities as well as the system integration effort. In order to achieve a robust and stable system performance, we apply a systematic approach for reproducible robotic experimentation including automatic tests. For RoboCup 2017, we plan to enhance this approach by simulating complete RoboCup@Home tasks. We further extend it to the RoboCup@Home standard platform Pepper. Similar to the Nao platform, the Pepper comes with its own runtime and development eco-system. Thus, one of the chal- lenges will be the cross-platform transfer of capabilities between robots based on different eco-system, e.g. the utilized middleware and application layers. In this paper, we will present a generic approach to such issues: the Cognitive Interaction Toolkit. The overall framework inherently supports the idea of open research and offers direct access to reusable components and reproducible systems via a web-based catalog. A main focus of research at Bielefeld are robots as an ambient host in a smart home or for instance as a museum’s guide. Both scenarios are highly relevant for the RoboCup@Home standard platform competition. Skills developed in these domains will be transferred to the RoboCup@Home scenarios

ToBI - Team of Bielefeld A Human-Robot Interaction System for RoboCup@Home 2018

Wachsmuth S, Lier F, Meyer zu Borgsen S. ToBI - Team of Bielefeld A Human-Robot Interaction System for RoboCup@Home 2018. Presented at the RoboCup 2018, Montreal, Canada.The Team of Bielefeld (ToBI) was founded in 2009. The RoboCup team’s activities are embedded in a long-term research agenda towards human-robot interaction with laypersons in regular and smart home environments. The RoboCup@Home competition is an important benchmark and milestone for this goal in terms of robot capabilities as well as the system integration effort. In order to achieve a robust and stable system performance, we apply a systematic approach for reproducible robotic experimentation including automated tests. A second focus of research is the development of reusable robot behaviors and robot skills. By re-usability we mean both, the re-use in different robot tasks as well as the reuse across different platforms. For RoboCup 2018, we plan to enhance this approach for the standard platform Pepper which comes with certain requirements and limitations, like its own runtime and development ecosystem, limited computing resources onboard, or a limited range of sensor devices. We further introduce a simulation environment for the Pepper robot that is based on MORSE and allows to define additional artificial agents as human-like interaction partners. This is one of the key features for simulating complete RoboCup@Home tasks. In this paper, we will present a generic approach to these issues. System descriptions as well as build and deployment procedures are modeled in the Cognitive Interaction Toolkit. The overall framework inherently supports the idea of open research and offers direct access to reusable components and reproducible systems via a web-based catalo

Nonverbal Communication During Human-Robot Object Handover. Improving Predictability of Humanoid Robots by Gaze and Gestures in Close Interaction

Meyer zu Borgsen S. Nonverbal Communication During Human-Robot Object Handover. Improving Predictability of Humanoid Robots by Gaze and Gestures in Close Interaction. Bielefeld: Universität Bielefeld; 2020.This doctoral thesis investigates the influence of nonverbal communication on human-robot object handover. Handing objects to one another is an everyday activity where two individuals cooperatively interact. Such close interactions incorporate a lot of nonverbal communication in order to create alignment in space and time. Understanding and transferring communication cues to robots becomes more and more important as e.g. service robots are expected to closely interact with humans in the near future. Their tasks often include delivering and taking objects. Thus, handover scenarios play an important role in human-robot interaction. A lot of work in this field of research focuses on speed, accuracy, and predictability of the robot’s movement during object handover. Still, robots need to be enabled to closely interact with naive users and not only experts. In this work I present how nonverbal communication can be implemented in robots to facilitate smooth handovers. I conducted a study on people with different levels of experience exchanging objects with a humanoid robot. It became clear that especially users with only little experience in regard to interaction with robots rely heavily on the communication cues they are used to on the basis of former interactions with humans. I added different gestures with the second arm, not directly involved in the transfer, to analyze the influence on synchronization, predictability, and human acceptance. Handing an object has a special movement trajectory itself which has not only the purpose of bringing the object or hand to the position of exchange but also of socially signalizing the intention to exchange an object. Another common type of nonverbal communication is gaze. It allows guessing the focus of attention of an interaction partner and thus helps to predict the next action. In order to evaluate handover interaction performance between human and robot, I applied the developed concepts to the humanoid robot Meka M1. By adding the humanoid robot head named Floka Head to the system, I created the Floka humanoid, to implement gaze strategies that aim to increase predictability and user comfort. This thesis contributes to the field of human-robot object handover by presenting study outcomes and concepts along with an implementation of improved software modules resulting in a fully functional object handing humanoid robot from perception and prediction capabilities to behaviors enhanced and improved by features of nonverbal communication

ToBI - Team of Bielefeld Enhancing the Robot Capabilities of the Social Standard Platform Pepper

Lier F, Kummert J, Renner P, Wachsmuth S. ToBI - Team of Bielefeld Enhancing the Robot Capabilities of the Social Standard Platform Pepper. In: Holz D, Genter K, Saad M, von Stryk O, eds. RoboCup 2018: Robot World Cup XXII. Lecture Notes in Computer Science. Vol 11374. Cham: Springer; 2019: 524-535