Angelika Peer

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Emotion recognition from EEG signals allows the direct assessment of the “inner” state of a user, which is considered an important factor in human-machine-interaction. Many methods for feature extraction have been studied and the selection of both appropriate features and electrode locations is usually based on neuro-scientific findings. Their(More)
Goal-directed movements are executed under the permanent supervision of the central nervous system, which continuously processes sensory afferents and triggers on-line corrections if movement accuracy seems to be compromised. For arm reaching movements, visual information about the hand plays an important role in this supervision, notably improving reaching(More)
This chapter introduces the main topics of a telerobotic system. It describes the architecture of such a system from a general point of view and emphasizes the interaction between a human operator and a robot that performs the task in the remote environment. Furthermore it focuses on multi-modal human system interfaces and explains the main features of(More)
In order to enable intuitive physical interaction with autonomous robots as well as in collaborative multi-user virtual reality and teleoperation systems a deep understanding of human-human haptic interaction is required. In this paper the effect of haptic interaction in single and dyadic conditions is investigated. Furthermore, an energy-based framework(More)
When robots leave industrial settings, they have to be designed allowing intuitive communication with the humans they interact with. The current paper focuses on collaboration in kinesthetic tasks. Herein, we investigate decision situations. This way, the need of communication between partners can be addressed. The current paper introduces for the first(More)
Recent developments strive for realizing robotic systems that not only interact, but closely collaborate with humans in performing everyday manipulation tasks. Successful collaboration requires the integration of the individual partner's intentions into a shared action plan, which may involve continuous negotiation of intentions. We focus on collaboration(More)
Imitation learning, also known as Programming by Demonstration, allows a non-expert user to teach complex skills to a robot. While so far researchers focused on abstracting kinematic relations, only little attention has been paid to force information. In this work we study imitation learning of human grasping skills from motion and force data. For this(More)
In a haptic shared control system, a virtual assistant and a human share the control over performed actions to facilitate execution of manipulation tasks. The assistance level determines the amount of support provided by the assistant. It should be adapted autonomously such that task performance and human effort are optimized. The effect of the assistance(More)
A haptic teleoperation system enables an operator to interact with a remote environment. How well the remote environment is presented to the operator is typically referred to as transparency. Common transparency measures for haptic teleoperation consider one or two fixed environments only, usually the extreme cases of freespace and stiff contact. Our(More)
Despite the great diversity of teleoperator designs and applications, their underlying control systems have many similarities. These similarities can be exploited to enable inter-operability between heterogeneous systems. We have developed a network data specification, the Interoperable Telerobotics Protocol, that can be used for Internet based control of a(More)