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Biomimetics
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Intelligent Human-Robot Interaction: 2nd Edition
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Intelligent Human-Robot Interaction: 2nd Edition

A special issue of Biomimetics (ISSN 2313-7673). This special issue belongs to the section "Locomotion and Bioinspired Robotics".

Deadline for manuscript submissions: closed (25 March 2024) | Viewed by 10681

Special Issue Editors

Prof. Dr. Yisheng Guan

E-Mail Website
Guest Editor
School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510006, China
Interests: bionic robotics; motion planning; automation and robotics; mechatronics robot motion planning; cognitive robotics; space robotics
Special Issues, Collections and Topics in MDPI journals
Dr. Weiwei Wan

E-Mail Website
Co-Guest Editor
School of Engineering Science, Osaka University, Osaka 565-0871, Japan
Interests: robot manipulation; motion planning; intelligent robot
Special Issues, Collections and Topics in MDPI journals
Dr. Li He

E-Mail Website
Co-Guest Editor
Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen 518055, China
Interests: SLAM; machine learning; mobile robot; LiDAR; autonomous driving
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Human–robot interaction (HRI) is a multi-disciplinary field that encompasses artificial intelligence, robotics, human–computer interaction, machine vision, natural language understanding, and social science. With the rapid development of AI and robotics, intelligent HRI has become an increasingly attractive issue in the field of robotics.

Intelligent HRI involves many challenges in science and technology, particularly in human-centered aspects. These include human expectations of, attitudes towards, and perceptions of robots; the safety, acceptability, and comfortability of robotic behaviors; and the closeness of robots to humans. On the other hand, it is desired that robots can understand the attention, intention, and even emotion of humans, and make prompt corresponding responses under the support of AI. Achieving excellent intelligent HRI requires R&D in this multi- and cross-disciplinary field, with efforts expected to be made in all relevant aspects, such as actuation, sensing, perception, control, recognition, planning, learning, AI algorithms, intelligent IO, integrated systems, and so on.

The aim of this Special Issue is to reveal new concepts, ideas, findings, and the latest achievements in both theoretical research and technical development in intelligent HRI. We invite scientists and engineers from robotics, AI, computer science, and other relevant disciplines to present the latest results of their research and developments in the field of intelligent HRI. The topics of interest include, but are not limited to, the following:

  • Intelligent sensors and systems;
  • Bio-inspired sensing and learning;
  • Multi-modal perception and recognition;
  • Social robotics;
  • Autonomous behaviors of robots;
  • AI algorithms in robotics;
  • Collaboration between humans and robots;
  • Advances and future challenges of HRI.

Prof. Dr. Yisheng Guan
Dr. Weiwei Wan
Dr. Li He
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomimetics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • intelligent sensors and systems
  • bio-inspired sensing and learning
  • multi-modal perception and recognition
  • social robotics
  • autonomous behaviors of robots
  • AI algorithms in robotics
  • collaboration between humans and robots
  • advances and future challenges of HRI

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Published Papers (7 papers)

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Research

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16 pages, 1013 KiB  
Article
EEG Motor Imagery Classification: Tangent Space with Gate-Generated Weight Classifier
by Sara Omari, Adil Omari, Fares Abu-Dakka and Mohamed Abderrahim
Biomimetics 2024, 9(8), 459; https://doi.org/10.3390/biomimetics9080459 - 27 Jul 2024
Viewed by 659
Abstract
Individuals grappling with severe central nervous system injuries often face significant challenges related to sensorimotor function and communication abilities. In response, brain–computer interface (BCI) technology has emerged as a promising solution by offering innovative interaction methods and intelligent rehabilitation training. By leveraging electroencephalographic [...] Read more.
Individuals grappling with severe central nervous system injuries often face significant challenges related to sensorimotor function and communication abilities. In response, brain–computer interface (BCI) technology has emerged as a promising solution by offering innovative interaction methods and intelligent rehabilitation training. By leveraging electroencephalographic (EEG) signals, BCIs unlock intriguing possibilities in patient care and neurological rehabilitation. Recent research has utilized covariance matrices as signal descriptors. In this study, we introduce two methodologies for covariance matrix analysis: multiple tangent space projections (M-TSPs) and Cholesky decomposition. Both approaches incorporate a classifier that integrates linear and nonlinear features, resulting in a significant enhancement in classification accuracy, as evidenced by meticulous experimental evaluations. The M-TSP method demonstrates superior performance with an average accuracy improvement of 6.79% over Cholesky decomposition. Additionally, a gender-based analysis reveals a preference for men in the obtained results, with an average improvement of 9.16% over women. These findings underscore the potential of our methodologies to improve BCI performance and highlight gender-specific performance differences to be examined further in our future studies. Full article
(This article belongs to the Special Issue Intelligent Human-Robot Interaction: 2nd Edition)
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18 pages, 5107 KiB  
Article
Perceptive Recommendation Robot: Enhancing Receptivity of Product Suggestions Based on Customers’ Nonverbal Cues
by Masaya Iwasaki, Akiko Yamazaki, Keiichi Yamazaki, Yuji Miyazaki, Tatsuyuki Kawamura and Hideyuki Nakanishi
Biomimetics 2024, 9(7), 404; https://doi.org/10.3390/biomimetics9070404 - 2 Jul 2024
Viewed by 1006
Abstract
Service robots that coexist with humans in everyday life have become more common, and they have provided customer service in physical shops around the world in recent years. However, their potential in effective sales strategies has not been fully realized due to their [...] Read more.
Service robots that coexist with humans in everyday life have become more common, and they have provided customer service in physical shops around the world in recent years. However, their potential in effective sales strategies has not been fully realized due to their low social presence. This study aims to clarify what kind of robot behavior enhances the social presence of service robots and how it affects human–robot interaction and purchasing behavior. We conducted two experiments with a sales robot, Pepper, at a retail shop in Kyoto. In Experiment 1, we showed that the robot’s social presence increased and that customers looked at the robot longer when the robot understood human gaze information and was capable of shared attention. In Experiment 2, we showed that the probability of customers picking up products increased when the robot suggested products based on the humans’ degree of attention from gaze and posture information. These results indicate that the robot’s ability to understand and make utterances about a customer’s orientation and attention effectively enhances human–robot communication and purchasing motivation. Full article
(This article belongs to the Special Issue Intelligent Human-Robot Interaction: 2nd Edition)
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28 pages, 6576 KiB  
Article
Assessment of Pepper Robot’s Speech Recognition System through the Lens of Machine Learning
by Akshara Pande and Deepti Mishra
Biomimetics 2024, 9(7), 391; https://doi.org/10.3390/biomimetics9070391 - 27 Jun 2024
Viewed by 1882
Abstract
Speech comprehension can be challenging due to multiple factors, causing inconvenience for both the speaker and the listener. In such situations, using a humanoid robot, Pepper, can be beneficial as it can display the corresponding text on its screen. However, prior to that, [...] Read more.
Speech comprehension can be challenging due to multiple factors, causing inconvenience for both the speaker and the listener. In such situations, using a humanoid robot, Pepper, can be beneficial as it can display the corresponding text on its screen. However, prior to that, it is essential to carefully assess the accuracy of the audio recordings captured by Pepper. Therefore, in this study, an experiment is conducted with eight participants with the primary objective of examining Pepper’s speech recognition system with the help of audio features such as Mel-Frequency Cepstral Coefficients, spectral centroid, spectral flatness, the Zero-Crossing Rate, pitch, and energy. Furthermore, the K-means algorithm was employed to create clusters based on these features with the aim of selecting the most suitable cluster with the help of the speech-to-text conversion tool Whisper. The selection of the best cluster is accomplished by finding the maximum accuracy data points lying in a cluster. A criterion of discarding data points with values of WER above 0.3 is imposed to achieve this. The findings of this study suggest that a distance of up to one meter from the humanoid robot Pepper is suitable for capturing the best speech recordings. In contrast, age and gender do not influence the accuracy of recorded speech. The proposed system will provide a significant strength in settings where subtitles are required to improve the comprehension of spoken statements. Full article
(This article belongs to the Special Issue Intelligent Human-Robot Interaction: 2nd Edition)
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18 pages, 2937 KiB  
Article
Whole-Body Dynamics for Humanoid Robot Fall Protection Trajectory Generation with Wall Support
by Weilong Zuo, Junyao Gao, Jiongnan Liu, Taiping Wu and Xilong Xin
Biomimetics 2024, 9(4), 245; https://doi.org/10.3390/biomimetics9040245 - 19 Apr 2024
Cited by 1 | Viewed by 1355
Abstract
When humanoid robots work in human environments, they are prone to falling. However, when there are objects around that can be utilized, humanoid robots can leverage them to achieve balance. To address this issue, this paper established the state equation of a robot [...] Read more.
When humanoid robots work in human environments, they are prone to falling. However, when there are objects around that can be utilized, humanoid robots can leverage them to achieve balance. To address this issue, this paper established the state equation of a robot using a variable height-inverted pendulum model and implemented online trajectory optimization using model predictive control. For the arms’ optimal joint angles during movement, this paper took the distributed polygon method to calculate the arm postures. To ensure that the robot reached the target position smoothly and rapidly during its motion, this paper adopts a whole-body motion control approach, establishing a cost function for multi-objective constraints on the robot’s movement. These constraints include whole-body dynamics, center of mass constraints, arm’s end effector constraints, friction constraints, and center of pressure constraints. In the simulation, four sets of methods were compared, and the experimental results indicate that compared to free fall motion, adopting the method proposed in this paper reduces the maximum acceleration of the robot when it touches the wall to 69.1 m/s2, effectively reducing the impact force upon landing. Finally, in the actual experiment, we positioned the robot 0.85 m away from the wall and applied a forward pushing force. We observed that the robot could stably land on the wall, and the impact force was within the range acceptable to the robot, confirming the practical effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Intelligent Human-Robot Interaction: 2nd Edition)
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17 pages, 9389 KiB  
Article
Teleoperated Grasping Using Data Gloves Based on Fuzzy Logic Controller
by Chunxiao Lu, Lei Jin, Yufei Liu, Jianfeng Wang and Weihua Li
Biomimetics 2024, 9(2), 116; https://doi.org/10.3390/biomimetics9020116 - 15 Feb 2024
Viewed by 1454
Abstract
Teleoperated robots have attracted significant interest in recent years, and data gloves are one of the commonly used devices for their operation. However, existing solutions still encounter two challenges: the ways in which data gloves capture human operational intentions and achieve accurate mapping. [...] Read more.
Teleoperated robots have attracted significant interest in recent years, and data gloves are one of the commonly used devices for their operation. However, existing solutions still encounter two challenges: the ways in which data gloves capture human operational intentions and achieve accurate mapping. In order to address these challenges, we propose a novel teleoperation method using data gloves based on fuzzy logic controller. Firstly, the data are collected and normalized from the flex sensors on data gloves to identify human manipulation intentions. Then, a fuzzy logic controller is designed to convert finger flexion information into motion control commands for robot arms. Finally, experiments are conducted to demonstrate the effectiveness and precision of the proposed method. Full article
(This article belongs to the Special Issue Intelligent Human-Robot Interaction: 2nd Edition)
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21 pages, 179914 KiB  
Article
Integrating Egocentric and Robotic Vision for Object Identification Using Siamese Networks and Superquadric Estimations in Partial Occlusion Scenarios
by Elisabeth Menendez, Santiago Martínez, Fernando Díaz-de-María and Carlos Balaguer
Biomimetics 2024, 9(2), 100; https://doi.org/10.3390/biomimetics9020100 - 8 Feb 2024
Cited by 2 | Viewed by 1617
Abstract
This paper introduces a novel method that enables robots to identify objects based on user gaze, tracked via eye-tracking glasses. This is achieved without prior knowledge of the objects’ categories or their locations and without external markers. The method integrates a two-part system: [...] Read more.
This paper introduces a novel method that enables robots to identify objects based on user gaze, tracked via eye-tracking glasses. This is achieved without prior knowledge of the objects’ categories or their locations and without external markers. The method integrates a two-part system: a category-agnostic object shape and pose estimator using superquadrics and Siamese networks. The superquadrics-based component estimates the shapes and poses of all objects, while the Siamese network matches the object targeted by the user’s gaze with the robot’s viewpoint. Both components are effectively designed to function in scenarios with partial occlusions. A key feature of the system is the user’s ability to move freely around the scenario, allowing dynamic object selection via gaze from any position. The system is capable of handling significant viewpoint differences between the user and the robot and adapts easily to new objects. In tests under partial occlusion conditions, the Siamese networks demonstrated an 85.2% accuracy in aligning the user-selected object with the robot’s viewpoint. This gaze-based Human–Robot Interaction approach demonstrates its practicality and adaptability in real-world scenarios. Full article
(This article belongs to the Special Issue Intelligent Human-Robot Interaction: 2nd Edition)
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Other

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20 pages, 5668 KiB  
Opinion
Living Lab-Based Service Interaction Design for a Companion Robot for Seniors in South Korea
by Ju Yeong Kwon and Da Young Ju
Biomimetics 2023, 8(8), 609; https://doi.org/10.3390/biomimetics8080609 - 14 Dec 2023
Cited by 2 | Viewed by 1850
Abstract
A living lab is a valuable method for designing tangible and intangible service elements, ensuring a comprehensive user experience. Developing a digital companion service, which users may be unfamiliar with, requires observing user behavior in real-world environments and analyzing living and behavioral patterns. [...] Read more.
A living lab is a valuable method for designing tangible and intangible service elements, ensuring a comprehensive user experience. Developing a digital companion service, which users may be unfamiliar with, requires observing user behavior in real-world environments and analyzing living and behavioral patterns. A living lab starts with understanding user characteristics and behaviors. Living lab methods have an impact on the accuracy and precision of service design. The number of seniors in South Korea is rapidly increasing, leading to a rise in social issues like solitary deaths and suicide. Addressing these problems has led to a growing demand for companion robots. To design effective companion services, understanding seniors’ living environments and their cognitive and behavioral traits is essential. This opinion piece, based on a national R&D project, presents the development of a digital companion for seniors. It offers insights, providing a comprehensive overview of living lab-based service interaction design and proposing methodologies about living lab environment construction and experimentation and considerations when designing robot interaction functions and appearance. The living lab environment includes real living spaces, laboratories, virtual reality settings, and senior welfare centers. Using the research findings, we created service scenarios, analyzed senior language characteristics, and developed the concept and facial expressions of the digital companion. To successfully introduce a novel service, it is crucial to analyze users’ real-life behavior and adjust the service accordingly. Full article
(This article belongs to the Special Issue Intelligent Human-Robot Interaction: 2nd Edition)
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