Modular Piezoresistive Smart Textile for State Estimation of Cloths

Smart textiles have found numerous applications ranging from health monitoring to smart homes. Their main allure is their flexibility, which allows for seamless integration of sensing in everyday objects like clothing. The application domain also includes robotics; smart textiles have been used to improve human-robot interaction, to solve the problem of state estimation of soft robots, and for state estimation to enable learning of robotic manipulation of textiles. The latter application provides an alternative to computationally expensive vision-based pipelines and we believe it is the key to accelerate robotic learning of textile manipulation. Current smart textiles, however, maintain wired connections to external units, which impedes robotic manipulation, and lack modularity to facilitate state estimation of large cloths. In this work, we propose an open-source, fully wireless, highly flexible, light, and modular version of a piezoresistive smart textile. Its output stability was experimentally quantified and determined to be sufficient for classification tasks. Its functionality as a state sensor for larger cloths was also verified in a classification task where two of the smart textiles were sewn onto a piece of clothing of which three states are defined. The modular smart textile system was able to recognize these states with average per-class F1-scores ranging from 85.7 to 94.6% with a basic linear classifier.

Download Full-text

Mindful tutors

Interaction Studies ◽

10.1075/is.12.1.06fis ◽

2011 ◽

Vol 12 (1) ◽

pp. 134-161 ◽

Cited By ~ 26

Author(s):

Kerstin Fischer ◽

Kilian Foth ◽

Katharina J. Rohlfing ◽

Britta Wrede

Keyword(s):

Social Communication ◽

Human Robot Interaction ◽

Robot Interaction ◽

Social Actors ◽

Everyday Objects ◽

Computers As Social Actors ◽

Keywords Child ◽

Linguistic Behaviour ◽

Almost All ◽

High Degree

It has been proposed that the design of robots might benefit from interactions that are similar to caregiver–child interactions, which is tailored to children’s respective capacities to a high degree. However, so far little is known about how people adapt their tutoring behaviour to robots and whether robots can evoke input that is similar to child-directed interaction. The paper presents detailed analyses of speakers’ linguistic behaviour and non-linguistic behaviour, such as action demonstration, in two comparable situations: In one experiment, parents described and explained to their nonverbal infants the use of certain everyday objects; in the other experiment, participants tutored a simulated robot on the same objects. The results, which show considerable differences between the two situations on almost all measures, are discussed in the light of the computer-as-social-actor paradigm and the register hypothesis. Keywords: child-directed speech (CDS); motherese; robotese; motionese; register theory; social communication; human–robot interaction (HRI); computers-as-social-actors; mindless transfer

Download Full-text

Investigating Implicit Cues for User State Estimation in Human-Robot Interaction Using Physiological Measurements

RO-MAN 2007 - The 16th IEEE International Symposium on Robot and Human Interactive Communication ◽

10.1109/roman.2007.4415249 ◽

2007 ◽

Cited By ~ 18

Author(s):

Emily Mower ◽

David J. Feil-Seifer ◽

Maja J. Mataric ◽

Shrikanth Narayanan

Keyword(s):

State Estimation ◽

Human Robot Interaction ◽

Robot Interaction

Download Full-text

Natural language instructions for human–robot collaborative manipulation

The International Journal of Robotics Research ◽

10.1177/0278364918760992 ◽

2018 ◽

Vol 37 (6) ◽

pp. 558-565 ◽

Cited By ~ 2

Author(s):

Rosario Scalise ◽

Shen Li ◽

Henny Admoni ◽

Stephanie Rosenthal ◽

Siddhartha S Srinivasa

Keyword(s):

Natural Language ◽

Language Processing ◽

Human Robot Interaction ◽

Robotic Manipulation ◽

Easy Access ◽

Domain Specific Language ◽

Robot Interaction ◽

Specific Language ◽

Domain Specific ◽

Object Reference

This paper presents a dataset of natural language instructions for object reference in manipulation scenarios. It comprises 1582 individual written instructions, which were collected via online crowdsourcing. This dataset is particularly useful for researchers who work in natural language processing, human–robot interaction, and robotic manipulation. In addition to serving as a rich corpus of domain-specific language, it provides a benchmark of image–instruction pairs to be used in system evaluations and uncovers inherent challenges in tabletop object specification. Example code is provided for easy access via Python.

Download Full-text

An Approach to Telerobotic Manipulations

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.2801275 ◽

1997 ◽

Vol 119 (3) ◽

pp. 431-438 ◽

Cited By ~ 13

Author(s):

H. Kazerooni ◽

C. L. Moore

Keyword(s):

Closed Loop ◽

Control Method ◽

Sufficient Conditions ◽

Human Robot Interaction ◽

Loop System ◽

Robotic Manipulation ◽

Closed Loop System ◽

Robot Interaction ◽

Minimum Number ◽

The Stability

This article introduces three areas of study: 1 telefunctioning; 2 a control method for producing telefunctioning; and 3 an analysis of human-robot interaction when telefunctioning governs the system behavior. Telefunctioning facilitates the maneuvering of loads by creating a perpetual sense of the load dynamics for the operator. Telefunctioning is defined as a robotic manipulation method in which the dynamic behaviors of the slave robot and the master robot are functions of each other; these functions are the designer’s choice and depend on the application. (In a subclass of telefunctioning currently referred to as telepresence, these functions are specified as “unity” so that the master and slave variables (e.g., position, velocity) are dynamically equal.) To produce telefunctioning, this work determines a minimum number of functions relating the robots’ variables, and then develops a control architecture which guarantees that the defined functions govern the dynamic behavior of the closed-loop system. The stability of the closed-loop system (i.e., master robot, slave robot, human, and the load being manipulated) is analyzed and sufficient conditions for stability are derived.

Download Full-text

Utilizing Smart Textiles-Enabled Sensorized Toy and Playful Interactions for Assessment of Psychomotor Development on Children

Journal of Sensors ◽

10.1155/2015/898047 ◽

2015 ◽

Vol 2015 ◽

pp. 1-9 ◽

Cited By ~ 10

Author(s):

Mario Vega-Barbas ◽

Iván Pau ◽

Javier Ferreira ◽

Evelyn Lebis ◽

Fernando Seoane

Keyword(s):

Healthcare Services ◽

User Acceptance ◽

Psychomotor Development ◽

Sensor Technology ◽

User Engagement ◽

Smart Textiles ◽

Everyday Objects ◽

Multimodal Sensing ◽

Smart Textile ◽

Interesting Approach

Emerging pervasive technologies like smart textiles make it possible to develop new and more accessible healthcare services for patients independently of their location or time. However, none of these new e-health solutions guarantee a complete user acceptance, especially in cases requiring extensive interaction between the user and the solution. So far, researchers have focused their efforts on new interactions techniques to improve the perception of privacy and confidence of the people using e-health services. In this way, the use of smart everyday objects arises as an interesting approach to facilitate the required interaction and increase user acceptance. Such Smart Daily Objects together with smart textiles provide researchers with a novel way to introduce sophisticated sensor technology in the daily life of people. This work presents a sensorized smart toy for assessment of psychomotor development in early childhood. The aim of this work is to design, develop, and evaluate the usability and playfulness of a smart textile-enabled sensorized toy that facilitates the user engagement in a personalized monitoring healthcare activity. To achieve this objective the monitoring is based on a smart textile sensorized toy as catalyzer of acceptance and multimodal sensing sources to monitor psychomotor development activities during playtime.

Download Full-text

Affective State Estimation for Human–Robot Interaction

IEEE Transactions on Robotics ◽

10.1109/tro.2007.904899 ◽

2007 ◽

Vol 23 (5) ◽

pp. 991-1000 ◽

Cited By ~ 119

Author(s):

Dana Kulic ◽

Elizabeth A. Croft

Keyword(s):

State Estimation ◽

Affective State ◽

Human Robot Interaction ◽

Robot Interaction

Download Full-text

MemoRob: Studying Robots Distractor Effects

Modelling Measurement and Control C ◽

10.18280/mmc_c.811-410 ◽

2020 ◽

Vol 81 (1-4) ◽

pp. 55-61

Author(s):

Céline Jost ◽

Brigitte Le Pévédic ◽

Marine Grandgeorge ◽

Marie Le Menn ◽

Farah Arab ◽

...

Keyword(s):

Human Robot Interaction ◽

Robot Interaction ◽

Learning Modes ◽

Robotic Learning

MemoRob is a model about how to optimize the use of robots for learning. It is based on a list of each possible robotic source of distraction associated with its relevant effects according to its nature and to the target learning mode. While collecting the sources of distraction that the robotics literature provides, the instantiation method of pairing each source and each learning mode with the nature of the distraction as well as its distracting effects allows to consider how to remedy these effects of robotic distraction effects although still having the robotic input as a learning medium. In this article, we provide the motivations that led to the need for the MemoRob model, the list of sources and effects generated by the Human-Robot interaction that may interfere with learning situations, the learning modes described according to their processes and mechanisms and, finally, a set of predictions on whether a given robotic learning situations might promote attention or distraction.

Download Full-text