6,489 research outputs found
Early Turn-taking Prediction with Spiking Neural Networks for Human Robot Collaboration
Turn-taking is essential to the structure of human teamwork. Humans are
typically aware of team members' intention to keep or relinquish their turn
before a turn switch, where the responsibility of working on a shared task is
shifted. Future co-robots are also expected to provide such competence. To that
end, this paper proposes the Cognitive Turn-taking Model (CTTM), which
leverages cognitive models (i.e., Spiking Neural Network) to achieve early
turn-taking prediction. The CTTM framework can process multimodal human
communication cues (both implicit and explicit) and predict human turn-taking
intentions in an early stage. The proposed framework is tested on a simulated
surgical procedure, where a robotic scrub nurse predicts the surgeon's
turn-taking intention. It was found that the proposed CTTM framework
outperforms the state-of-the-art turn-taking prediction algorithms by a large
margin. It also outperforms humans when presented with partial observations of
communication cues (i.e., less than 40% of full actions). This early prediction
capability enables robots to initiate turn-taking actions at an early stage,
which facilitates collaboration and increases overall efficiency.Comment: Submitted to IEEE International Conference on Robotics and Automation
(ICRA) 201
A Review of Verbal and Non-Verbal Human-Robot Interactive Communication
In this paper, an overview of human-robot interactive communication is
presented, covering verbal as well as non-verbal aspects of human-robot
interaction. Following a historical introduction, and motivation towards fluid
human-robot communication, ten desiderata are proposed, which provide an
organizational axis both of recent as well as of future research on human-robot
communication. Then, the ten desiderata are examined in detail, culminating to
a unifying discussion, and a forward-looking conclusion
An Intervening Ethical Governor for a Robot Mediator in Patient-Caregiver Relationships
© Springer International Publishing AG 2015DOI: 10.1007/978-3-319-46667-5_6Patients with Parkinson’s disease (PD) experience challenges when interacting with
caregivers due to their declining control over their musculature. To remedy those challenges, a
robot mediator can be used to assist in the relationship between PD patients and their caregivers.
In this context, a variety of ethical issues can arise. To overcome one issue in particular,
providing therapeutic robots with a robot architecture that can ensure patients’ and caregivers’
dignity is of potential value. In this paper, we describe an intervening ethical governor for a
robot that enables it to ethically intervene, both to maintain effective patient–caregiver
relationships and prevent the loss of dignity
- …