A Comparison of Visualisation Methods for Disambiguating Verbal Requests in Human-Robot Interaction

Picking up objects requested by a human user is a common task in human-robot interaction. When multiple objects match the user's verbal description, the robot needs to clarify which object the user is referring to before executing the action. Previous research has focused on perceiving user's multimodal behaviour to complement verbal commands or minimising the number of follow up questions to reduce task time. In this paper, we propose a system for reference disambiguation based on visualisation and compare three methods to disambiguate natural language instructions. In a controlled experiment with a YuMi robot, we investigated real-time augmentations of the workspace in three conditions -- mixed reality, augmented reality, and a monitor as the baseline -- using objective measures such as time and accuracy, and subjective measures like engagement, immersion, and display interference. Significant differences were found in accuracy and engagement between the conditions, but no differences were found in task time. Despite the higher error rates in the mixed reality condition, participants found that modality more engaging than the other two, but overall showed preference for the augmented reality condition over the monitor and mixed reality conditions

The Ambient Horn: Designing a novel audio-based learning experience

The Ambient Horn is a novel handheld device designed to support children learning about habitat distributions and interdependencies in an outdoor woodland environment. The horn was designed to emit non-speech audio sounds representing ecological processes. Both symbolic and arbitrary mappings were used to represent the processes. The sounds are triggered in response to the children’s location in certain parts of the woodland. A main objective was to provoke children into interpreting and reflecting upon the significance of the sounds in the context in which they occur. Our study of the horn being used showed the sounds to be provocative, generating much discussion about what they signified in relation to what the children saw in the woodland. In addition, the children appropriated the horn in creative ways, trying to ‘scoop’ up new sounds as they walked in different parts of the woodland

Usability evaluation of a virtual museum interface

The Augmented Representation of Cultural Objects (ARCO) system provides software and interface tools to museum curators to develop virtual museum exhibitions, as well as a virtual environment for museum visitors over the World Wide Web or in informative kiosks. The main purpose of the system is to offer an enhanced educative and entertaining experience to virtual museum visitors. In order to assess the usability of the system, two approaches have been employed: a questionnaire based survey and a Cognitive Walkthrough session. Both approaches employed expert evaluators, such as domain experts and usability experts. The result of this study shows a fair performance of the followed approach, as regards the consumed time, financial and other resources, as a great deal of usability problems has been uncovered and many aspects of the system have been investigated. The knowledge gathered aims at creating a conceptual framework for diagnose usability problems in systems in the area of Virtual Cultural Heritage

Games and Brain-Computer Interfaces: The State of the Art

BCI gaming is a very young field; most games are proof-of-concepts. Work that compares BCIs in a game environments with traditional BCIs indicates no negative effects, or even a positive effect of the rich visual environments on the performance. The low transfer-rate of current games poses a problem for control of a game. This is often solved by changing the goal of the game. Multi-modal input with BCI forms an promising solution, as does assigning more meaningful functionality to BCI control

Exploration of Reaction Pathways and Chemical Transformation Networks

For the investigation of chemical reaction networks, the identification of all relevant intermediates and elementary reactions is mandatory. Many algorithmic approaches exist that perform explorations efficiently and automatedly. These approaches differ in their application range, the level of completeness of the exploration, as well as the amount of heuristics and human intervention required. Here, we describe and compare the different approaches based on these criteria. Future directions leveraging the strengths of chemical heuristics, human interaction, and physical rigor are discussed.Comment: 48 pages, 4 figure