12,315 research outputs found
THINK Robots
Retailers rely on Kiva Systems’ warehouse robots to deliver order-fulfillment services, but current systems are frequently interrupted and require physical barriers to ensure compliance with safety regulations since Kiva does not currently rely on the obstacle detection system to contribute to the functional safety of its overall system. After evaluating operating scenarios and detection technologies, a solution comprised of a stereo vision system to detect static objects and a radio ranging system to identify humans in the vicinity was designed, built, and verified, with the aim of reducing undue downtime and allowing humans and robots to safely interact without physical restrictions
Generating Engagement Behaviors in Human-Robot Interaction
Based on a study of the engagement process between humans, I have developed models for four types of connection events involving gesture and speech: directed gaze, mutual facial gaze, adjacency pairs and backchannels. I have developed and validated a reusable Robot Operating System (ROS) module that supports engagement between a human and a humanoid robot by generating appropriate connection events. The module implements policies for adding gaze and pointing gestures to referring phrases (including deictic and anaphoric references), performing end-of-turn gazes, responding to human-initiated connection events and maintaining engagement. The module also provides an abstract interface for receiving information from a collaboration manager using the Behavior Markup Language (BML) and exchanges information with a previously developed engagement recognition module. This thesis also describes a Behavior Markup Language (BML) realizer that has been developed for use in robotic applications. Instead of the existing fixed-timing algorithms used with virtual agents, this realizer uses an event-driven architecture, based on Petri nets, to ensure each behavior is synchronized in the presence of unpredictable variability in robot motor systems. The implementation is robot independent, open-source and uses the Robot Operating System (ROS)
Naturalism and Moral Expertise in the Zhuangzi
This essay will examine scholarly attempts at distilling a proto-ethical philosophy from the Daoist classic known as the Zhuangzi. In opposition to interpretations of the text which characterize it as amoralistic, I will identify elements of a natural normativity in the Zhuangzi. My examination features passages from the Zhuangzi – commonly known as the “knack” passages – which are often interpreted through some sort of linguistic, skeptical, or relativistic lens. Contra such readings, I believe the Zhuangzi prescribes an art of living – or shù [術] – which incorporates a few motifs familiar to certain threads of philosophical naturalism. Building on existing scholarship which treats of the praxeology of the text, I argue that the naturalist themes present in the Zhuangzi support an unusual, but robust, view of moral expertise
Design of a Multi-biometric Platform, based on physical traits and physiological measures: Face, Iris, Ear, ECG and EEG
Security and safety is one the main concerns both for governments and for private
companies in the last years so raising growing interests and investments in
the area of biometric recognition and video surveillance, especially after the sad
happenings of September 2001. Outlays assessments of the U.S. government for
the years 2001-2005 estimate that the homeland security spending climbed from
100 billion of 2005. In this lapse of
time, new pattern recognition techniques have been developed and, even more
important, new biometric traits have been investigated and refined; besides
the well-known physical and behavioral characteristics, also physiological measures
have been studied, so providing more features to enhance discrimination
capabilities of individuals. This dissertation proposes the design of a multimodal
biometric platform, FAIRY, based on the following biometric traits: ear,
face, iris EEG and ECG signals. In the thesis the modular architecture of the
platform has been presented, together with the results obtained for the solution
to the recognition problems related to the different biometrics and their possible
fusion. Finally, an analysis of the pattern recognition issues concerning the
area of videosurveillance has been discussed
Socionomic modelling in wireless sensor networks
The performance and efficiency of a Wireless Sensor Network (WSN) is typically subject to techniques used in data routing, clustering, and localization. Being primarily driven by resource constraints, a Socionomic model has been formulated to optimize resource usage and boost collaboration among sensor nodes. In this paper, we present several experimental results to ascertain the underlying philosophy of the Socionomic model for improving network lifetime of resource constrained devices - such as, sensor nodes
Design of a Multi-biometric Platform, based on physical traits and physiological measures: Face, Iris, Ear, ECG and EEG
Security and safety is one the main concerns both for governments and for private
companies in the last years so raising growing interests and investments in
the area of biometric recognition and video surveillance, especially after the sad
happenings of September 2001. Outlays assessments of the U.S. government for
the years 2001-2005 estimate that the homeland security spending climbed from
100 billion of 2005. In this lapse of
time, new pattern recognition techniques have been developed and, even more
important, new biometric traits have been investigated and refined; besides
the well-known physical and behavioral characteristics, also physiological measures
have been studied, so providing more features to enhance discrimination
capabilities of individuals. This dissertation proposes the design of a multimodal
biometric platform, FAIRY, based on the following biometric traits: ear,
face, iris EEG and ECG signals. In the thesis the modular architecture of the
platform has been presented, together with the results obtained for the solution
to the recognition problems related to the different biometrics and their possible
fusion. Finally, an analysis of the pattern recognition issues concerning the
area of videosurveillance has been discussed
Recommended from our members
Proxemics of screen mediation: engagement with reading on screen manifests as diminished variation due to self-control, rather than diminished mean distance from screen
Objective: Burgoon's theory of conversational involvement suggest that when people engage with a person, they will move slightly closer to them, often subtly and subconsciously. However, some studies have failed to extend this to human-computer interaction. Our hypothesis is that during online reading, engagement is associated with an expenditure of effort to hold the head upright, still and centrally.
Method: We presented to 27 participants (ages 21.00 ± 2.89, 15 female) seated in front of 47.5x27 cm monitor two reading stimuli in a counterbalanced order, one (interesting) based on a best selling novel and the other (boring) based on European Union banking regulations. The participants were video-recorded during their reading while they wore reflective motion tracking markers. The markers were video-tracked off-line using Kinovea 0.8.
Results: Subjective VAS ratings showed that the stimuli elicited the bored and interested states as expected. Video tracking showed that the boring stimulus (compared to the interesting reading) elicited a greater head-to-screen velocity, a greater head-to-screen distance range, a greater head-to-screen distance standard deviation, but not a further away head-to-screen mean distance.
Conclusions: The more interesting reading led to efforts to control the head to a more central viewing position while suppressing head fidgeting
Action Recognition in Videos: from Motion Capture Labs to the Web
This paper presents a survey of human action recognition approaches based on
visual data recorded from a single video camera. We propose an organizing
framework which puts in evidence the evolution of the area, with techniques
moving from heavily constrained motion capture scenarios towards more
challenging, realistic, "in the wild" videos. The proposed organization is
based on the representation used as input for the recognition task, emphasizing
the hypothesis assumed and thus, the constraints imposed on the type of video
that each technique is able to address. Expliciting the hypothesis and
constraints makes the framework particularly useful to select a method, given
an application. Another advantage of the proposed organization is that it
allows categorizing newest approaches seamlessly with traditional ones, while
providing an insightful perspective of the evolution of the action recognition
task up to now. That perspective is the basis for the discussion in the end of
the paper, where we also present the main open issues in the area.Comment: Preprint submitted to CVIU, survey paper, 46 pages, 2 figures, 4
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