Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 888804

Gesture Recognition System for Real-time Mobile Robot Control Based on Inertial Sensors and Motion Strings


Stančić, Ivo; Musić, Josip; Grujić, Tamara
Gesture Recognition System for Real-time Mobile Robot Control Based on Inertial Sensors and Motion Strings // Engineering applications of artificial intelligence, 66 (2017), 33-48 doi:10.1016/j.engappai.2017.08.013 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 888804 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Gesture Recognition System for Real-time Mobile Robot Control Based on Inertial Sensors and Motion Strings

Autori
Stančić, Ivo ; Musić, Josip ; Grujić, Tamara

Izvornik
Engineering applications of artificial intelligence (0952-1976) 66 (2017); 33-48

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
human-robot interaction ; mobile robot control ; inertial sensors ; machine learning ; real-time classification ; hand gestures

Sažetak
Navigating and controlling a mobile robot in an indoor or outdoor environment by using a range of body-worn sensors is becoming an increasingly interesting research area in the robotics community. In such scenarios, hand gestures offer some unique capabilities for human-robot interaction inherent to nonverbal communication with features and application scenarios not possible with the currently predominant vision based systems. Therefore, in this paper, we propose and develop an effective inertial- sensor-based system, worn by the user, along with a microprocessor and wireless module for communication with the robot at distances of up to 250 m. Possible features describing hand- gesture dynamics are introduced and their feasibility is demonstrated in an offline scenario by using several classification methods (e.g., random forests and artificial neural networks). Refined motion features are then used in K- means unsupervised clustering for motion primitive extraction, which forms the motion strings used for real-time classification. The system demonstrated an F1 score of 90.05% with the possibility of gesture spotting and null class classification (e.g., undefined gestures were discarded from the analysis). Finally, to demonstrate the feasibility of the proposed algorithm, it was implemented in an Arduino- based 8-bit ATmega2560 microcontroller for control of a mobile, tracked robot platform.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Temeljne tehničke znanosti



POVEZANOST RADA


Ustanove:
Fakultet elektrotehnike, strojarstva i brodogradnje, Split

Profili:

Avatar Url Tamara Grujić (autor)

Avatar Url Josip Musić (autor)

Avatar Url Ivo Stančić (autor)

Poveznice na cjeloviti tekst rada:

doi doi.org www.sciencedirect.com

Citiraj ovu publikaciju:

Stančić, Ivo; Musić, Josip; Grujić, Tamara
Gesture Recognition System for Real-time Mobile Robot Control Based on Inertial Sensors and Motion Strings // Engineering applications of artificial intelligence, 66 (2017), 33-48 doi:10.1016/j.engappai.2017.08.013 (međunarodna recenzija, članak, znanstveni)
Stančić, I., Musić, J. & Grujić, T. (2017) Gesture Recognition System for Real-time Mobile Robot Control Based on Inertial Sensors and Motion Strings. Engineering applications of artificial intelligence, 66, 33-48 doi:10.1016/j.engappai.2017.08.013.
@article{article, author = {Stan\v{c}i\'{c}, Ivo and Musi\'{c}, Josip and Gruji\'{c}, Tamara}, year = {2017}, pages = {33-48}, DOI = {10.1016/j.engappai.2017.08.013}, keywords = {human-robot interaction, mobile robot control, inertial sensors, machine learning, real-time classification, hand gestures}, journal = {Engineering applications of artificial intelligence}, doi = {10.1016/j.engappai.2017.08.013}, volume = {66}, issn = {0952-1976}, title = {Gesture Recognition System for Real-time Mobile Robot Control Based on Inertial Sensors and Motion Strings}, keyword = {human-robot interaction, mobile robot control, inertial sensors, machine learning, real-time classification, hand gestures} }
@article{article, author = {Stan\v{c}i\'{c}, Ivo and Musi\'{c}, Josip and Gruji\'{c}, Tamara}, year = {2017}, pages = {33-48}, DOI = {10.1016/j.engappai.2017.08.013}, keywords = {human-robot interaction, mobile robot control, inertial sensors, machine learning, real-time classification, hand gestures}, journal = {Engineering applications of artificial intelligence}, doi = {10.1016/j.engappai.2017.08.013}, volume = {66}, issn = {0952-1976}, title = {Gesture Recognition System for Real-time Mobile Robot Control Based on Inertial Sensors and Motion Strings}, keyword = {human-robot interaction, mobile robot control, inertial sensors, machine learning, real-time classification, hand gestures} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Citati:





    Contrast
    Increase Font
    Decrease Font
    Dyslexic Font