Browsing University of Hertfordshire by Author "Scheunemann, Marcus M."

Now showing items 1-7 of 7

    • Autonomous and Intrinsically Motivated Robots for Sustained Human-Robot Interaction 

      Scheunemann, Marcus M. (2021-02-04)
      A challenge in using fully autonomous robots in human-robot interaction (HRI) is to design behavior that is engaging enough to encourage voluntary, long-term interaction, yet robust to the perturbations induced by human ...

    • Bluetooth low energy for autonomous human-robot interaction 

      Scheunemann, Marcus M.; Dautenhahn, Kerstin (IEEE Computer Society, 2017-03-06)
      This demonstration shows how inexpensive, off-the-shelf, and unobtrusive Bluetooth Low Energy (BLE) devices can be utilized for enabling robots to recognize touch gestures, to perceive proximity information, and to distinguish ...

    • Deep Learning for Semantic Segmentation on Minimal Hardware 

      Dijk, Sander G. van; Scheunemann, Marcus M. (Springer Nature, 2019-08-04)
      Deep learning has revolutionised many fields, but it is still challenging to transfer its success to small mobile robots with minimal hardware. Specifically, some work has been done to this effect in the RoboCup humanoid ...

    • Intrinsically Motivated Autonomy in Human-Robot Interaction: Human Perception of Predictive Information in Robots 

      Scheunemann, Marcus M.; Salge, Christoph; Dautenhahn, Kerstin (Springer Nature, 2019-06-28)
      In this paper we present a fully autonomous and intrinsically motivated robot usable for HRI experiments. We argue that an intrinsically motivated approach based on the Predictive Information formalism, like the one presented ...

    • ROS 2 for RoboCup 

      Scheunemann, Marcus M.; van Dijk, Sander G. (Springer Nature, 2019-12-01)
      There has always been much motivation for sharing code and solutions among teams in the RoboCup community. Yet the transfer of code between teams was usually complicated due to a huge variety of used frameworks and their ...

    • Utilizing Bluetooth Low Energy to recognize proximity, touch and humans 

      Scheunemann, Marcus M.; Dautenhahn, Kerstin; Salem, Maha; Robins, Ben (Institute of Electrical and Electronics Engineers (IEEE), 2016-11-17)
      Interacting with humans is one of the main challenges for mobile robots in a human inhabited environment. To enable adaptive behavior, a robot needs to recognize touch gestures and/or the proximity to interacting individuals. ...

    • Warmth and Competence to Predict Human Preference of Robot Behavior in Physical Human-Robot Interaction 

      Scheunemann, Marcus M.; Cuijpers, Raymond H.; Salge, Christoph (Institute of Electrical and Electronics Engineers (IEEE), 2020-10-14)
      A solid methodology to understand human perception and preferences in human-robot interaction (HRI) is crucial in designing real-world HRI. Social cognition posits that the dimensions Warmth and Competence are central and ...