Title :
Wearable Computing
Author :
Roggen, Daniel ; Magnenat, Stephane ; Waibel, Markus ; Troster, G.
Author_Institution :
Wearable Comput. Lab., Swiss Fed. Inst. of Technol., Zürich, Switzerland
fDate :
6/1/2011 12:00:00 AM
Abstract :
Driven by the rapid progress in mobile sensing and computing, wearable computing has developed powerful methods for the automatic recognition, categorization, and labeling of human actions and behaviors from sensor data. Because of the stringent requirements dictated by user acceptance, these methods are typically robust to human variability and hardware-dependent factors, including variability in sensor type and placement. This makes them a potentially useful tool for the automatic recognition and labeling of robot behaviors and may lead to new opportunities for research in robotics. We detail three domains in which the methods of activity recognition can play a role in robotics.
Keywords :
Internet; gesture recognition; human-robot interaction; mobile computing; unsupervised learning; wearable computers; World Wide Web; activity recognition; hardware-dependent factors; human action categorization; human action labeling; human action recognition; human behavior; human variability; human-robot interaction; large-scale activity data set annotation; mobile computing; mobile sensing; robot behaviors; robot self-learning; robotics; sensor data; user acceptance; wearable computing; Data systems; Human factors; Robot kinematics; Robot sensing systems; Sensor phenomena and characterization; Wearable computers;
Journal_Title :
Robotics & Automation Magazine, IEEE
DOI :
10.1109/MRA.2011.940992