Tactile sensing with gesture-controlled collaborative robot
Само за регистроване кориснике
2020
Аутори
Sorgini, FrancescaFarulla, Giuseppe Airo
Lukić, Nikola
Danilov, Ivan
Roveda, Loris
Milivojević, Miloš
Pulikottil, Terrin Babu
Carrozza, Maria Chiara
Prinetto, Paolo
Tolio, Tullio
Oddo, Calogero Maria
Petrović, Petar
Bojović, Božica
Конференцијски прилог (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
Sensors and human machine interfaces for collaborative robotics will allow smooth interaction in contexts ranging from industry to tele-medicine and rescue. This paper introduces a bidirectional communication system to achieve multisensory telepresence during the gestural control of an industrial robotic arm. Force and motion from the robot are converted in neuromorphic haptic stimuli delivered on the user's hand through a vibro-tactile glove. Untrained personnel participated in an experimental task benchmarking a pick-and-place operation. The robot end-effector was used to sequentially press six buttons, illuminated according to a random sequence, and comparing the tasks executed without and with tactile feedback. The results demonstrated the reliability of the hand tracking strategy developed for controlling the robotic arm, and the effectiveness of a neuronal spiking model for encoding hand displacement and exerted forces in order to promote a fluid embodiment of the haptic interfac...e and control strategy. The main contribution of this paper is in presenting a robotic arm under gesture-based remote control with multisensory telepresence, demonstrating for the first time that a spiking haptic interface can be used to effectively deliver on the skin surface a sequence of stimuli emulating the neural code of the mechanoreceptors beneath.
Кључне речи:
telepresence / neuromorphic vibrotactile feedback / human-robot interaction / hand tracking / gesture-based teleoperation / collaborative roboticsИзвор:
2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2020 -, 2020, 364-368Издавач:
- Institute of Electrical and Electronics Engineers Inc.
Финансирање / пројекти:
- Italian Ministry of Foreign Affairs and International Cooperation via the Italy-Serbia bilateral project Human-Robot Co-Working as a Key Enabling Technology for the Factories of Future [PGR00758/2017]
- Italian Ministry of Education, Universities and Research within the "Smart Cities and Social Innovation Under 30" program through the PARLOMA Project [SIN_00132]
- EC within the Erasmus+ program [2018/KA107 47798-MOB00004]
- Dubai Future Foundation through Guaana.com open research platform
Колекције
Институција/група
Mašinski fakultetTY - CONF AU - Sorgini, Francesca AU - Farulla, Giuseppe Airo AU - Lukić, Nikola AU - Danilov, Ivan AU - Roveda, Loris AU - Milivojević, Miloš AU - Pulikottil, Terrin Babu AU - Carrozza, Maria Chiara AU - Prinetto, Paolo AU - Tolio, Tullio AU - Oddo, Calogero Maria AU - Petrović, Petar AU - Bojović, Božica PY - 2020 UR - https://machinery.mas.bg.ac.rs/handle/123456789/3445 AB - Sensors and human machine interfaces for collaborative robotics will allow smooth interaction in contexts ranging from industry to tele-medicine and rescue. This paper introduces a bidirectional communication system to achieve multisensory telepresence during the gestural control of an industrial robotic arm. Force and motion from the robot are converted in neuromorphic haptic stimuli delivered on the user's hand through a vibro-tactile glove. Untrained personnel participated in an experimental task benchmarking a pick-and-place operation. The robot end-effector was used to sequentially press six buttons, illuminated according to a random sequence, and comparing the tasks executed without and with tactile feedback. The results demonstrated the reliability of the hand tracking strategy developed for controlling the robotic arm, and the effectiveness of a neuronal spiking model for encoding hand displacement and exerted forces in order to promote a fluid embodiment of the haptic interface and control strategy. The main contribution of this paper is in presenting a robotic arm under gesture-based remote control with multisensory telepresence, demonstrating for the first time that a spiking haptic interface can be used to effectively deliver on the skin surface a sequence of stimuli emulating the neural code of the mechanoreceptors beneath. PB - Institute of Electrical and Electronics Engineers Inc. C3 - 2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2020 - T1 - Tactile sensing with gesture-controlled collaborative robot EP - 368 SP - 364 DO - 10.1109/MetroInd4.0IoT48571.2020.9138183 ER -
@conference{ author = "Sorgini, Francesca and Farulla, Giuseppe Airo and Lukić, Nikola and Danilov, Ivan and Roveda, Loris and Milivojević, Miloš and Pulikottil, Terrin Babu and Carrozza, Maria Chiara and Prinetto, Paolo and Tolio, Tullio and Oddo, Calogero Maria and Petrović, Petar and Bojović, Božica", year = "2020", abstract = "Sensors and human machine interfaces for collaborative robotics will allow smooth interaction in contexts ranging from industry to tele-medicine and rescue. This paper introduces a bidirectional communication system to achieve multisensory telepresence during the gestural control of an industrial robotic arm. Force and motion from the robot are converted in neuromorphic haptic stimuli delivered on the user's hand through a vibro-tactile glove. Untrained personnel participated in an experimental task benchmarking a pick-and-place operation. The robot end-effector was used to sequentially press six buttons, illuminated according to a random sequence, and comparing the tasks executed without and with tactile feedback. The results demonstrated the reliability of the hand tracking strategy developed for controlling the robotic arm, and the effectiveness of a neuronal spiking model for encoding hand displacement and exerted forces in order to promote a fluid embodiment of the haptic interface and control strategy. The main contribution of this paper is in presenting a robotic arm under gesture-based remote control with multisensory telepresence, demonstrating for the first time that a spiking haptic interface can be used to effectively deliver on the skin surface a sequence of stimuli emulating the neural code of the mechanoreceptors beneath.", publisher = "Institute of Electrical and Electronics Engineers Inc.", journal = "2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2020 -", title = "Tactile sensing with gesture-controlled collaborative robot", pages = "368-364", doi = "10.1109/MetroInd4.0IoT48571.2020.9138183" }
Sorgini, F., Farulla, G. A., Lukić, N., Danilov, I., Roveda, L., Milivojević, M., Pulikottil, T. B., Carrozza, M. C., Prinetto, P., Tolio, T., Oddo, C. M., Petrović, P.,& Bojović, B.. (2020). Tactile sensing with gesture-controlled collaborative robot. in 2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2020 - Institute of Electrical and Electronics Engineers Inc.., 364-368. https://doi.org/10.1109/MetroInd4.0IoT48571.2020.9138183
Sorgini F, Farulla GA, Lukić N, Danilov I, Roveda L, Milivojević M, Pulikottil TB, Carrozza MC, Prinetto P, Tolio T, Oddo CM, Petrović P, Bojović B. Tactile sensing with gesture-controlled collaborative robot. in 2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2020 -. 2020;:364-368. doi:10.1109/MetroInd4.0IoT48571.2020.9138183 .
Sorgini, Francesca, Farulla, Giuseppe Airo, Lukić, Nikola, Danilov, Ivan, Roveda, Loris, Milivojević, Miloš, Pulikottil, Terrin Babu, Carrozza, Maria Chiara, Prinetto, Paolo, Tolio, Tullio, Oddo, Calogero Maria, Petrović, Petar, Bojović, Božica, "Tactile sensing with gesture-controlled collaborative robot" in 2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2020 - (2020):364-368, https://doi.org/10.1109/MetroInd4.0IoT48571.2020.9138183 . .