1,145 research outputs found
Turing-Test Evaluation of a Mobile Haptic Virtual Reality Kissing Machine
Various communication systems have been developed to integrate the haptic channel in digital communication. Future directions of such haptic technologies are moving towards realistic virtual reality applications and human-robot social interaction. With the digitisation of touch, robots equipped with touch sensors and actuators can communicate with humans on a more emotional and intimate level, such as sharing a hug or kiss just like humans do. This paper presents the design guideline, implementation and evaluations of a novel haptic kissing machine for smart phones - the Kissenger machine. The key novelties and contributions of the paper are: (i) A novel haptic kissing device for mobile phones, which uses dynamic perpendicular force stimulation to transmit realistic sensations of kissing in order to enhance intimacy and emotional connection of digital communication; (ii) Extensive evaluations of the Kissenger machine, including a lab experiment that compares mediated kissing with Kissenger to real kissing, a unique haptic Turing test that involves the first academic study of humanmachine kiss, and a field study of the effects of Kissenger on long distance relationships
Fast Damage Recovery in Robotics with the T-Resilience Algorithm
Damage recovery is critical for autonomous robots that need to operate for a
long time without assistance. Most current methods are complex and costly
because they require anticipating each potential damage in order to have a
contingency plan ready. As an alternative, we introduce the T-resilience
algorithm, a new algorithm that allows robots to quickly and autonomously
discover compensatory behaviors in unanticipated situations. This algorithm
equips the robot with a self-model and discovers new behaviors by learning to
avoid those that perform differently in the self-model and in reality. Our
algorithm thus does not identify the damaged parts but it implicitly searches
for efficient behaviors that do not use them. We evaluate the T-Resilience
algorithm on a hexapod robot that needs to adapt to leg removal, broken legs
and motor failures; we compare it to stochastic local search, policy gradient
and the self-modeling algorithm proposed by Bongard et al. The behavior of the
robot is assessed on-board thanks to a RGB-D sensor and a SLAM algorithm. Using
only 25 tests on the robot and an overall running time of 20 minutes,
T-Resilience consistently leads to substantially better results than the other
approaches
Self Organized Multi Agent Swarms (SOMAS) for Network Security Control
Computer network security is a very serious concern in many commercial, industrial, and military environments. This paper proposes a new computer network security approach defined by self-organized agent swarms (SOMAS) which provides a novel computer network security management framework based upon desired overall system behaviors. The SOMAS structure evolves based upon the partially observable Markov decision process (POMDP) formal model and the more complex Interactive-POMDP and Decentralized-POMDP models, which are augmented with a new F(*-POMDP) model. Example swarm specific and network based behaviors are formalized and simulated. This paper illustrates through various statistical testing techniques, the significance of this proposed SOMAS architecture, and the effectiveness of self-organization and entangled hierarchies
Motion clouds: model-based stimulus synthesis of natural-like random textures for the study of motion perception
Choosing an appropriate set of stimuli is essential to characterize the
response of a sensory system to a particular functional dimension, such as the
eye movement following the motion of a visual scene. Here, we describe a
framework to generate random texture movies with controlled information
content, i.e., Motion Clouds. These stimuli are defined using a generative
model that is based on controlled experimental parametrization. We show that
Motion Clouds correspond to dense mixing of localized moving gratings with
random positions. Their global envelope is similar to natural-like stimulation
with an approximate full-field translation corresponding to a retinal slip. We
describe the construction of these stimuli mathematically and propose an
open-source Python-based implementation. Examples of the use of this framework
are shown. We also propose extensions to other modalities such as color vision,
touch, and audition
Connecting the Brain to Itself through an Emulation.
Pilot clinical trials of human patients implanted with devices that can chronically record and stimulate ensembles of hundreds to thousands of individual neurons offer the possibility of expanding the substrate of cognition. Parallel trains of firing rate activity can be delivered in real-time to an array of intermediate external modules that in turn can trigger parallel trains of stimulation back into the brain. These modules may be built in software, VLSI firmware, or biological tissue as in vitro culture preparations or in vivo ectopic construct organoids. Arrays of modules can be constructed as early stage whole brain emulators, following canonical intra- and inter-regional circuits. By using machine learning algorithms and classic tasks known to activate quasi-orthogonal functional connectivity patterns, bedside testing can rapidly identify ensemble tuning properties and in turn cycle through a sequence of external module architectures to explore which can causatively alter perception and behavior. Whole brain emulation both (1) serves to augment human neural function, compensating for disease and injury as an auxiliary parallel system, and (2) has its independent operation bootstrapped by a human-in-the-loop to identify optimal micro- and macro-architectures, update synaptic weights, and entrain behaviors. In this manner, closed-loop brain-computer interface pilot clinical trials can advance strong artificial intelligence development and forge new therapies to restore independence in children and adults with neurological conditions
An Emotion Theory Approach to Artificial Emotion Systems for Robots and Intelligent Systems: Survey and Classification
This is the published version.To assist in the evaluation process when determining architectures for new robots and intelligent
systems equipped with artificial emotions, it is beneficial to understand the systems that have been built previously.
Other surveys have classified these systems on the basis of their technological features. In this survey
paper, we present a classification system based on a model similar to that used in psychology and philosophy
for theories of emotion. This makes possible a connection to thousands of years of discourse on the topic
of emotion. Five theories of emotion are described based on an emotion theory model proposed by Power
and Dalgleish. The paper provides classifications using a model of 10 new questions, for 14 major research
projects that describe implementations or designs for systems that use artificial emotions for either robotics
or general artificial intelligenc
Integrating Functional Synthesis
Design couples synthesis and analysis in iterative cycles, alternatively generating solutions, and evaluating their validity. The accuracy and depth of evaluation has increased markedly because of the availability of powerful simulation tools and the development of domain-specific knowledge bases. Efforts to extend the state of the art in evaluation have unfortunately been carried out in stovepipe fashion, depending on domain-specific views both of function and of what constitutes “good” design. Although synthesis as practiced by humans is an intentional process that centers on the notion of function, computational synthesis often eschews such intention for sheer permutation. Rather than combining synthesis and analysis to form an integrated design environment, current methods focus on comprehensive search for solutions within highly circumscribed subdomains of design. This paper presents an overview of the progress made in representing design function across abstraction levels proven useful to human designers. Through an example application in the domain of mechatronics, these representations are integrated across domains and throughout the design process
In silico case studies of compliant robots: AMARSI deliverable 3.3
In the deliverable 3.2 we presented how the morphological computing ap-
proach can significantly facilitate the control strategy in several scenarios,
e.g. quadruped locomotion, bipedal locomotion and reaching. In particular,
the Kitty experimental platform is an example of the use of morphological
computation to allow quadruped locomotion. In this deliverable we continue
with the simulation studies on the application of the different morphological
computation strategies to control a robotic system
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