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Changes for page Social Robot

Last modified by Sofia Vlachopanou on 2025/04/24 23:04
From version 4.3
edited by Nikolaos Soumpeniotis
on 2025/03/01 20:34
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To version 5.3
edited by Vlad Florea
on 2025/04/23 00:25
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1 -xwiki:XWiki.nsoumpeniotis
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1 +We considered the robots Navel, NAO, Pepper and Miro-E as potential fits for our use case.
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2 -(% style="font-size: 11pt; font-variant: normal; white-space: pre-wrap; font-family: Arial, sans-serif; color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %)The application will use the Pepper robot which has a built-in tablet device. More specifically, this is a humanoid robot(% style="font-size: 11pt; font-variant: normal; white-space: pre-wrap; font-family: Arial, sans-serif; color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); font-weight: 700; font-style: normal; text-decoration: none" %)** ,**(% style="font-size: 11pt; font-variant: normal; white-space: pre-wrap; font-family: Arial, sans-serif; color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); font-weight: 700; font-style: normal; text-decoration: none; font-weight: 400; font-style: normal; text-decoration: none" %)commonly used, because it offers interactive services such as welcoming visitors, providing information, and even dancing. Its ability to recognize faces and interpret emotions enables it to create more natural connections, making it particularly effective in healthcare.Pepper was used before with older adults, including as a coach for those with psychiatric disorders. A lot of studies have proved that the interaction of the elderly people with the Pepper robot is efficient and helps the patient to improve the quality of their lives. [1]
3 +NAO and Miro-E are small and risk appearing toy-like, which is not ideal since elderly users usually prefer life-sized humanoid robots [1].
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5 +While Navel provides advanced interaction capabilities and a human-like figure, it is difficult to program for and does not offer a tablet interface to assist as a visual aid.
6 +Therefore, we decided on Pepper, since it outperforms NAO in studies [2], is easy to program for using Python and offers an expressive humanoid form and a large tablet to assist as a visual aid and for touch controls.
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5 -(% style="font-size: 11pt; font-variant: normal; white-space: pre-wrap; font-family: Arial, sans-serif; color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %)Pepper is equipped with a lot of advanced sensors that enable it to interact with its environment effectively. It features four microphones, two RGB cameras, and a 3D sensor on its head, along with touch sensors on its hands and chest. Additionally, Pepper's legs are equipped with sonar, laser, and bumper sensors, along with a gyro sensor for balance. These sensors work together to allow Pepper to recognize faces, interpret emotions, and navigate its surroundings with precision [2].
8 +(% style="background-color:#ffffff; color:#000000; font-family:Arial,sans-serif; font-size:11pt; font-style:normal; font-variant:normal; font-weight:400; text-decoration:none; white-space:pre-wrap" %)The application will use the Pepper robot which has a built-in tablet device. More specifically, this is a humanoid robot(% style="background-color:#ffffff; color:#000000; font-family:Arial,sans-serif; font-size:11pt; font-style:normal; font-variant:normal; font-weight:700; text-decoration:none; white-space:pre-wrap" %)** ,**(% style="background-color:#ffffff; color:#000000; font-family:Arial,sans-serif; font-size:11pt; font-style:normal; font-variant:normal; font-weight:400; text-decoration:none; white-space:pre-wrap" %)commonly used, because it offers interactive services such as welcoming visitors, providing information, and even dancing. Its ability to recognize faces and interpret emotions enables it to create more natural connections, making it particularly effective in healthcare.Pepper was used before with older adults, including as a coach for those with psychiatric disorders. A lot of studies have proved that the interaction of elderly people with the Pepper robot is efficient and helps the patients improve the quality of their lives. [3]
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7 -[[image:1740857394953-812.png]]
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11 +(% style="background-color:#ffffff; color:#000000; font-family:Arial,sans-serif; font-size:11pt; font-style:normal; font-variant:normal; font-weight:400; text-decoration:none; white-space:pre-wrap" %)Pepper is equipped with a lot of advanced sensors that enable it to interact with its environment effectively. It features four microphones, two RGB cameras, and a 3D sensor on its head, along with touch sensors on its hands and chest. Additionally, Pepper's legs are equipped with sonar, laser, and bumper sensors, along with a gyro sensor for balance. These sensors work together to allow Pepper to recognize faces, interpret emotions, and navigate its surroundings with precision [4].
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13 +[[1.1 Pepper Robot>>image:1740857394953-812.png]]
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11 -(% style="line-height:1.38; margin-top:16px; margin-bottom:16px" %)
12 -(% style="font-size: 11pt; font-variant: normal; white-space: pre-wrap; font-family: Arial, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %)Another important technology to consider is Cloud Computing, which enables access to external libraries, enhancing the robot’s ability to interact by enriching dialogues. Additionally, cloud computing allows for real-time monitoring of the robot’s interactions and facilitates adaptive decision-making when needed [1].
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14 -(% style="line-height:1.38; margin-top:16px; margin-bottom:16px" %)
15 -(% style="font-size: 11pt; font-variant: normal; white-space: pre-wrap; font-family: Arial, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %)Equally important aspect of our system is speech recognition, which begins with signal processing through feature extraction. Feature extraction transforms raw audio into a format that machines can process, typically using spectrograms. Spectrograms provide a visual representation of sound frequency over time.
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17 -(% style="line-height:1.38; margin-top:16px; margin-bottom:16px" %)
18 -(% style="font-size: 11pt; font-variant: normal; white-space: pre-wrap; font-family: Arial, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %)After the feature extraction, Deep Neural Networks (DNNs) play a crucial role in mapping these features to words.Additionally, Convolutional Neural Networks (CNNs) are often utilized to process spectrograms, helping to extract meaningful spatial patterns from the data [3].
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20 -(% style="line-height:1.38; margin-top:16px; margin-bottom:16px" %)
21 -(% style="font-size: 11pt; font-variant: normal; white-space: pre-wrap; font-family: Arial, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %) After the neural network processes the speech, a language model is applied to improve recognition accuracy by selecting the most probable word sequence. Traditional approaches relied on n-gram models.
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23 23  **References:**
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25 -[1] Neerincx, M.A., van Vught, W., Blanson Henkemans, O., Oleari, E., Broekens, J., Peters, R., Kaptein, F., Demiris, Y., Kiefer, B., Fumagalli, D. and Bierman, B. (2019). Socio-Cognitive Engineering of a Robotic Partner for Child’s Diabetes Self-Management. //Frontiers in Robotics and AI//, 6. doi:https:~/~/doi.org/10.3389/frobt.2019.00118.
20 +[1]Broekens, Joost, Marcel Heerink, and Henk Rosendal. "Assistive social robots in elderly care: a review." //Gerontechnology// 8.2 (2009): 94-103.
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27 -[2] (% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %)Abdel-Hamid, O., Mohamed, A., Jiang, H., & Penn, G. (2014). Convolutional neural networks for speech recognition. (% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: italic; text-decoration: none" %)//IEEE/ACM Transactions on Audio, Speech, and Language Processing//(% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %), 22(10), 1533-1545.
22 +[2]Liao Y-J, Jao Y-L, Boltz M, et al. Use of a Humanoid Robot in Supporting Dementia Care: A Qualitative Analysis. SAGE Open Nursing. 2023;9. doi:10.1177/23779608231179528
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29 -[3]  (% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %)Faisal, M., Alharbi, A., Alhamadi, A., Almutairi, S., Alenezi, S., Alsulaili, A., Khan, M., & Khan, F. (2024). Robot-based solution for helping Alzheimer patients. (% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: italic; text-decoration: none" %)//SLAS technology//(% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %), (% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: italic; text-decoration: none" %)//29//(% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %)(3), 100140. (%%)[[(% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(17, 85, 204); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none" %)https:~~/~~/doi.org/10.1016/j.slast.2024.100140>>url:https://doi.org/10.1016/j.slast.2024.100140||style="text-decoration:none"]]
24 +[3] Neerincx, M.A., van Vught, W., Blanson Henkemans, O., Oleari, E., Broekens, J., Peters, R., Kaptein, F., Demiris, Y., Kiefer, B., Fumagalli, D. and Bierman, B. (2019). Socio-Cognitive Engineering of a Robotic Partner for Child’s Diabetes Self-Management. //Frontiers in Robotics and AI//, 6. doi:https:~/~/doi.org/10.3389/frobt.2019.00118.
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26 +[4]** **Abdel-Hamid, Ossama, et al. “Convolutional Neural Networks for Speech Recognition.” //IEEE/ACM Transactions on Audio, Speech, and Language Processing//, vol. 22, no. 10, Oct. 2014, pp. 1533–1545, www.microsoft.com/en-us/research/wp-content/uploads/2016/02/CNN_ASLPTrans2-14.pdf, https:~/~/doi.org/10.1109/taslp.2014.2339736. Accessed 20 Nov. 2019.
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XWiki.XWikiComments[0]
Author
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1 +xwiki:XWiki.BerndDudzik
Comment
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1 +See comment on previous section in the "Technology" part. It applies here too (i.e. why this technology and what alternatives did you consider?)
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1 +2025-04-19 16:23:39.517