7 research outputs found

    Online Visual Robot Tracking and Identification using Deep LSTM Networks

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    Collaborative robots working on a common task are necessary for many applications. One of the challenges for achieving collaboration in a team of robots is mutual tracking and identification. We present a novel pipeline for online visionbased detection, tracking and identification of robots with a known and identical appearance. Our method runs in realtime on the limited hardware of the observer robot. Unlike previous works addressing robot tracking and identification, we use a data-driven approach based on recurrent neural networks to learn relations between sequential inputs and outputs. We formulate the data association problem as multiple classification problems. A deep LSTM network was trained on a simulated dataset and fine-tuned on small set of real data. Experiments on two challenging datasets, one synthetic and one real, which include long-term occlusions, show promising results.Comment: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, 2017. IROS RoboCup Best Paper Awar

    The Effects of Visual Affordances and Feedback on a Gesture-based Interaction with Novice Users

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    This dissertation studies the roles and effects of visual affordances and feedback in a general-purpose gesture interface for novice users. Gesture interfaces are popularly viewed as intuitive and user-friendly modes of interacting with computers and robots, but they in fact introduce many challenges for users not already familiar with the system. Affordances and feedback – two fundamental building blocks of interface design – are perfectly suited to address the most important challenges and questions for novices using a gesture interface: what can they do? how do they do it? are they being understood? has anything gone wrong? Yet gesture interfaces rarely incorporate these features in a deliberate manner, and there are presently no well-adopted guidelines for designing affordances and feedback for gesture interaction, nor any clear understanding of their effects on such an interaction. A general-purpose gesture interaction system was developed based on a virtual touchscreen paradigm, and guided by a novel gesture interaction framework. This framework clarifies the relationship between gesture interfaces and the application interfaces they support, and it provides guidance for selecting and designing appropriate affordances and feedback. Using this gesture system, a 40-person (all novices) user study was conducted to evaluate the effects on interaction performance and user satisfaction of four categories of affordances and feedback. The experimental results demonstrated that affordances indicating how to do something in a gesture interaction are more important to interaction performance than affordances indicating what can be done, and also that system status is more important than feedback acknowledging user actions. However, the experiments also showed unexpectedly high interaction performance when affordances and feedback were omitted. The explanation for this result remains an open question, though several potential causes are analyzed, and a tentative interpretation is provided. The main contributions of this dissertation to the HRI and HCI research communities are 1) the design of a virtual touchscreen-based interface for general-purpose gesture interaction, to serve as a case study for identifying and designing affordances and feedback for gesture interfaces; 2) the method and surprising results of an evaluation of distinct affordance and feedback categories, in particular their effects on a gesture interaction with novice users; and 3) a set of guidelines and insights about the relationship between a user, a gesture interface, and a generic application interface, centered on a novel interaction framework that may be used to design and study other gesture systems. In addition to the intellectual contributions, this work is useful to the general public because it may influence how future assistive robots are designed to interact with people in various settings including search and rescue, healthcare and elderly care

    The Effects of Visual Affordances and Feedback on a Gesture-based Interaction with Novice Users

    Get PDF
    This dissertation studies the roles and effects of visual affordances and feedback in a general-purpose gesture interface for novice users. Gesture interfaces are popularly viewed as intuitive and user-friendly modes of interacting with computers and robots, but they in fact introduce many challenges for users not already familiar with the system. Affordances and feedback – two fundamental building blocks of interface design – are perfectly suited to address the most important challenges and questions for novices using a gesture interface: what can they do? how do they do it? are they being understood? has anything gone wrong? Yet gesture interfaces rarely incorporate these features in a deliberate manner, and there are presently no well-adopted guidelines for designing affordances and feedback for gesture interaction, nor any clear understanding of their effects on such an interaction. A general-purpose gesture interaction system was developed based on a virtual touchscreen paradigm, and guided by a novel gesture interaction framework. This framework clarifies the relationship between gesture interfaces and the application interfaces they support, and it provides guidance for selecting and designing appropriate affordances and feedback. Using this gesture system, a 40-person (all novices) user study was conducted to evaluate the effects on interaction performance and user satisfaction of four categories of affordances and feedback. The experimental results demonstrated that affordances indicating how to do something in a gesture interaction are more important to interaction performance than affordances indicating what can be done, and also that system status is more important than feedback acknowledging user actions. However, the experiments also showed unexpectedly high interaction performance when affordances and feedback were omitted. The explanation for this result remains an open question, though several potential causes are analyzed, and a tentative interpretation is provided. The main contributions of this dissertation to the HRI and HCI research communities are 1) the design of a virtual touchscreen-based interface for general-purpose gesture interaction, to serve as a case study for identifying and designing affordances and feedback for gesture interfaces; 2) the method and surprising results of an evaluation of distinct affordance and feedback categories, in particular their effects on a gesture interaction with novice users; and 3) a set of guidelines and insights about the relationship between a user, a gesture interface, and a generic application interface, centered on a novel interaction framework that may be used to design and study other gesture systems. In addition to the intellectual contributions, this work is useful to the general public because it may influence how future assistive robots are designed to interact with people in various settings including search and rescue, healthcare and elderly care

    Using MapReduce Streaming for Distributed Life Simulation on the Cloud

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    Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

    A complex systems approach to education in Switzerland

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    The insights gained from the study of complex systems in biological, social, and engineered systems enables us not only to observe and understand, but also to actively design systems which will be capable of successfully coping with complex and dynamically changing situations. The methods and mindset required for this approach have been applied to educational systems with their diverse levels of scale and complexity. Based on the general case made by Yaneer Bar-Yam, this paper applies the complex systems approach to the educational system in Switzerland. It confirms that the complex systems approach is valid. Indeed, many recommendations made for the general case have already been implemented in the Swiss education system. To address existing problems and difficulties, further steps are recommended. This paper contributes to the further establishment complex systems approach by shedding light on an area which concerns us all, which is a frequent topic of discussion and dispute among politicians and the public, where billions of dollars have been spent without achieving the desired results, and where it is difficult to directly derive consequences from actions taken. The analysis of the education system's different levels, their complexity and scale will clarify how such a dynamic system should be approached, and how it can be guided towards the desired performance
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