16,059 research outputs found
Semantic Mapping and Reasoning
Rich, yet efficient knowledge processing is one of the key problems in modern autonomous robotics. The Robot Autonomy and Interactive Learning (RAIL) Lab at the Georgia Institute of Technology has developed a new knowledge processing framework named Robot Common Sense Embedding (RoboCSE), which leverages multi-relational embeddings to learn object affordances, locations, and materials. This project aims to test the capabilities of RoboCSE for household robots by building a perception pipeline, which outputs a semantic map (i.e. map with object labels). The perception pipeline consists of two main components: a Simultaneous Localization and Mapping (SLAM) algorithm to build an occupancy map and two object classifiers to label objects in the map. We hope to integrate the semantic map into RoboCSE to test RoboCSE’s ability to perform high-level task planning and knowledge sharing.Undergraduat
Designing constraints: composing and performing with digital musical systems
This paper investigates two central terms in Human Computer Interaction (HCI) – affordances and constraints – and studies their relevance to the design and understanding of digital musical systems. It argues that in the analysis of complex systems, such as new interfaces for musical expression (NIME), constraints are a more productive analytical tool than the common HCI usage of affordances. Constraints are seen as limitations enabling the musician to encapsulate a specific search space of both physical and compositional gestures, proscribing complexity in favor of a relatively simple set of rules that engender creativity. By exploring the design of three different digital musical systems, the paper defines constraints as a core attribute of mapping, whether in instruments or compositional systems. The paper describes the aspiration for designing constraints as twofold: to save time, as musical performance is typically a real-time process, and to minimize the performer’s cognitive load. Finally, it discusses skill and virtuosity in the realm of new musical interfaces for musical expression with regard to constraints
Rethinking affordance
n/a – Critical survey essay retheorising the concept of 'affordance' in digital media context. Lead article in a special issue on the topic, co-edited by the authors for the journal Media Theory
MetaSpace II: Object and full-body tracking for interaction and navigation in social VR
MetaSpace II (MS2) is a social Virtual Reality (VR) system where multiple
users can not only see and hear but also interact with each other, grasp and
manipulate objects, walk around in space, and get tactile feedback. MS2 allows
walking in physical space by tracking each user's skeleton in real-time and
allows users to feel by employing passive haptics i.e., when users touch or
manipulate an object in the virtual world, they simultaneously also touch or
manipulate a corresponding object in the physical world. To enable these
elements in VR, MS2 creates a correspondence in spatial layout and object
placement by building the virtual world on top of a 3D scan of the real world.
Through the association between the real and virtual world, users are able to
walk freely while wearing a head-mounted device, avoid obstacles like walls and
furniture, and interact with people and objects. Most current virtual reality
(VR) environments are designed for a single user experience where interactions
with virtual objects are mediated by hand-held input devices or hand gestures.
Additionally, users are only shown a representation of their hands in VR
floating in front of the camera as seen from a first person perspective. We
believe, representing each user as a full-body avatar that is controlled by
natural movements of the person in the real world (see Figure 1d), can greatly
enhance believability and a user's sense immersion in VR.Comment: 10 pages, 9 figures. Video:
http://living.media.mit.edu/projects/metaspace-ii
Deep Affordance-grounded Sensorimotor Object Recognition
It is well-established by cognitive neuroscience that human perception of
objects constitutes a complex process, where object appearance information is
combined with evidence about the so-called object "affordances", namely the
types of actions that humans typically perform when interacting with them. This
fact has recently motivated the "sensorimotor" approach to the challenging task
of automatic object recognition, where both information sources are fused to
improve robustness. In this work, the aforementioned paradigm is adopted,
surpassing current limitations of sensorimotor object recognition research.
Specifically, the deep learning paradigm is introduced to the problem for the
first time, developing a number of novel neuro-biologically and
neuro-physiologically inspired architectures that utilize state-of-the-art
neural networks for fusing the available information sources in multiple ways.
The proposed methods are evaluated using a large RGB-D corpus, which is
specifically collected for the task of sensorimotor object recognition and is
made publicly available. Experimental results demonstrate the utility of
affordance information to object recognition, achieving an up to 29% relative
error reduction by its inclusion.Comment: 9 pages, 7 figures, dataset link included, accepted to CVPR 201
“No powers, man!”: A student perspective on designing university smart building interactions
Smart buildings offer an opportunity for better performance and enhanced experience by contextualising services and interactions to the needs and practices of occupants. Yet, this vision is limited by established approaches to building management, delivered top-down through professional facilities management teams, opening up an interaction-gap between occupants and the spaces they inhabit. To address the challenge of how smart buildings might be more inclusively managed, we present the results of a qualitative study with student occupants of a smart building, with design workshops including building walks and speculative futuring. We develop new understandings of how student occupants conceptualise and evaluate spaces as they experience them, and of how building management practices might evolve with new sociotechnical systems that better leverage occupant agency. Our findings point to important directions for HCI research in this nascent area, including the need for HBI (Human-Building Interaction) design to challenge entrenched roles in building management
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