Special Issue on Human-Robot Interaction Systems

2011 ◽  
Vol 15 (5) ◽  
pp. 533-533
Author(s):  
Tomomi Hashimoto ◽  
Yoshihito Kagawa
Keyword(s):  
Field Tests ◽  
Human Motion ◽  
Human Robot Interaction ◽  
Force Model ◽  
Control Mechanisms ◽  
Human Beings ◽  
Social Force ◽  
Special Issue ◽  
Model Concept ◽  
Verbal Messages

Opportunities for human beings and robots to work together are increasing. The objective of this special issuefs ten articles is to activate and expand top-quality research. In the first, T. Muto and Y. Miyake explore interpersonal cooperative walking replicated for two human beings and the motor-control mechanisms involved. In the second, Y. Nishikawa, Y. Kagawa, and J. Kurabayashi study control of healthcare equipment and a manipulator using electromyography (EMG) signals. The third contribution, by T. Hashimoto, Y. Takakura, T. Hamada, T. Akazawa, and M. Yamamoto, details a walking simulator using virtual reality. The fourth, by Y. Tang, H. A. Vu, P. Q. Le, D. Masano, O. Thet, C. Fatichah, Z. Liu, M. Yamaguchi, M. L. Tangel, F. Dong, Y. Yamazaki, and K. Hirota, proposes casual communication between humans and robots by integrating nonverbal gestures and verbal messages. Y. Ho, T. Shibano, E. Sato-Shimokawara, and T. Yamaguchi present a system in the fifth article that uses data mining to detect human intent collecting, processing, and analyzing human motion. In the sixth, K. Rattanyu and M. Mizukawa introduce emotion recognition based on electrocardiography (ECG) signals. In the seventh article, K. Ogawa, S. Nishio, K. Koda, G. Balistreri, T. Watanabe, and H. Ishiguro discusses two field tests using the Telenoid android. The eighth contribution, by H. Suzuki and H. Nishi, shows how animal gaits are implemented by quadrupedal robots. K. Zhang, Y. Maeda, and Y. Takahashi propose multiagent reinforcement learning in the ninth article. The closing contribution, by B. Piriyanont, N. Uchiyama, and S. Sano, proposes collision avoidance control for a quadrocopter based on the social force model concept. We thank the referees for their comprehensive reviews and the Fuji Technology Press Ltd. staff for its encouragement and advice.

HUMAN–ROBOT COLLISION AVOIDANCE USING A MODIFIED SOCIAL FORCE MODEL WITH BODY POSE AND FACE ORIENTATION

2013 ◽  
Vol 10 (01) ◽  
pp. 1350008 ◽  
Author(s):  
PHOTCHARA RATSAMEE ◽  
YASUSHI MAE ◽  
KENICHI OHARA ◽  
TOMOHITO TAKUBO ◽  
TATSUO ARAI
Keyword(s):  
Collision Avoidance ◽  
Motion Tracking ◽  
Personal Space ◽  
Human Motion ◽  
Force Model ◽  
Social Force ◽  
Social Force Model ◽  
Face To Face ◽  
The Face ◽  
Social Components

The ability of robots to understand human characteristics and make themselves socially accepted by humans are important issues if smooth collision avoidance between humans and robots is to be achieved. When discussing smooth collision avoidance, robot should understand not only physical components such as human position, but also social components such as body pose, face orientation and proxemics (personal space during motion). We integrated these components in a modified social force model (MSFM) which allows robots to predict human motion and perform smooth collision avoidance. In the modified model, short-term intended direction is described by body pose, and a supplementary force related face orientation is added for intention estimation. Face orientation is also the best indication of the direction of personal space during motion, which was verified in preliminary experiments. Our approach was implemented and tested on a real humanoid robot in a situation in which a human is confronted with the robot in an indoor environment. Experimental results showed that better human motion tracking was achieved with body pose and face orientation tracking. Being provided with the face orientation as an indication of the intended direction, and observing the laws of proxemics in a human-like manner, the robot was able to perform avoidance motions that were more human-like when compared to the original social force model (SFM) in a face-to-face confrontation.

Special Issue on Human-Robot Interaction Systems II

2017 ◽  
Vol 21 (4) ◽  
pp. 659-659
Author(s):  
Tomomi Hashimoto ◽  
Yoshihito Kagawa ◽  
Yoshio Nishikawa
Keyword(s):  
Degrees Of Freedom ◽  
Biped Robot ◽  
Human Robot Interaction ◽  
Human Beings ◽  
Special Issue ◽  
Robot Interaction ◽  
High Quality Research ◽  
Staff Members ◽  
Communication Robot ◽  
Episodic Memories

Six years have passed since the publication of our Special Issue on Human-Robot Interaction Systems in 2011. Since then, artificial intelligence and robotics have developed rapidly, and the opportunities for human beings and robots to work together have increased. The objective of this special issue’s twelve articles is to activate and expand high-quality research.In the first article, Y. Tamura, T. Akashi, and H. Osumi propose a computational model of robot’s gaze. In the second article, S. Hoshino and K. Uchida propose an interactive motion planner for robot navigation in dynamic environments. In the third article, T. Iio, Y. Yoshikawa, and H. Ishiguro develop a conversational robotic system based on human response. In the fourth article, K. Sakai, F. Dalla Libera, Y. Yoshikawa, and H. Ishiguro propose a method for generating bystander robots’ actions that is based on an analysis of the relative probabilities of human responses to robot actions. In the fifth article, T. Matsumaru and M. Narita present a newly developed support system for learning calligraphy strokes. In the sixth article, E. Tamura, Y. Yamashita, T. Yamashita, E. Sato-Shimokawara, and T. Yamaguchi present a method of driving a car simply by gesturing. In the seventh article, A. Kurosu and T. Hashimoto develop an eye robot with two degrees of freedom. It is intended for use as a communication robot. In the eighth article, T. Hashimoto, Y. Munakata, R. Yamanaka, and A. Kurosu report on a method for retrieving episodic memories. In the ninth article, Y. Nishikawa, Y. Kagawa, and A. Okazaki develop a spiral movement robot for inpatients. In the tenth article, Y. Umesawa, K. Doi, and H. Fujimoto develop an interface device that creates kinaesthetic illusions by inducing vibrations in muscle tendons, vibrations that coordinate with dual-joint movements. In the eleventh article, R. Horio, N. Uchiyama, and S. Sano propose a human-operated biped robot for transporting objects over rough terrain or up steps. In the closing contribution, T. Sakuraba, N. Uchiyama, S. Sano, and T. Sakaguchi present the design of a spring-based regenerative brake, and they verify its effectiveness by driving a system that uses it.We thank the referees for their comprehensive reviews and the staff members of Fuji Technology Press, Ltd. for their encouragement and advice.

Special Issue on Human Robot Interaction

2002 ◽  
Vol 14 (5) ◽  
pp. 431-431
Author(s):  
Yasushi Nakauchi
Keyword(s):  
Computer Science ◽  
User Interfaces ◽  
Daily Life ◽  
Living Environment ◽  
Human Robot Interaction ◽  
Human Beings ◽  
Special Issue ◽  
Robot Interaction ◽  
Future Directions ◽  
The Social

Recent advances in robotics are disseminating robots into the social living environment as humanoids, pets, and caregivers. Novel human-robot interaction techniques and interfaces must be developed, however, to ensure that such robots interact as expected in daily life and work. Unlike conventional personal computers, such robots may assume a variety of configurations, such as industrial, wheel-based, ambulatory, remotely operated, autonomous, and wearable. They may also implement different communications modalities, including voice, video, haptics, and gestures. All of these aspects require that research on human-robot interaction become interdisciplinary, combining research from such fields as robotics, ergonomics, computer science and, psychology. In the field of computer science, new directions in human-computer interaction are emerging as post graphical user interfaces (GUIs). These include wearable, ubiquitous, and real-world computing. Such advances are thereby bridging the gap between robotics and computer science. The open-ended problems that potentially face include the following: What is the most desirable type of interaction between human beings and robots? What sort of technology will enable these interactions? How will human beings accept robots in their daily life and work? We are certain that readers of this special issue will be able to find many of the answers and become open to future directions concerning these problems. Any information that readers find herein will be a great pleasure to its editors.

scholarly journals Special Issue on Augmented Prototyping and Fabrication for Advanced Product Design and Manufacturing

2019 ◽  
Vol 13 (4) ◽  
pp. 451-452 ◽  
Author(s):  
Satoshi Kanai ◽  
Jouke C. Verlinden
Keyword(s):  
Product Design ◽  
Digital Fabrication ◽  
Skills Training ◽  
Well Being ◽  
Human Motion ◽  
Human Robot Interaction ◽  
Special Issue ◽  
Endotracheal Suctioning ◽  
Design And Manufacturing ◽  
Human Skills

“Don’t automate, augment!” This is the takeaway of the seminal book on the future of work by Davenport and Kirby.*1 The emergence of cyber-physical systems makes radical new products and systems possible and challenges the role of humankind. Throughout the design, manufacturing, use, maintenance, and end-of-life stages, digital aspects (sensing, inferencing, connecting) influence the physical (digital fabrication, robotics) and vice versa. A key takeaway is that such innovations can augment human capabilities to extend our mental and physical skills with computational and robotic support – a notion called “augmented well-being.” Furthermore, agile development methods, complemented by mixed-reality systems and 3D-printing systems, enable us to create and adapt such systems on the fly, with almost instant turnaround times. Following this line of thought, our special issue is entitled “Augmented Prototyping and Fabrication for Advanced Product Design and Manufacturing.” Heavily inspired by the framework of Prof. Jun Rekimoto’s Augmented Human framework,*2 we can discern two orthogonal axes: cognitive versus physical and reflective versus active. As depicted in Fig. 1, this creates four different quadrants with important scientific domains that need to be juxtaposed. The contributions in this special issue are valuable steps towards this concept and are briefly discussed below. AR/VR To drive AR to the next level, robust tracking and tracing techniques are essential. The paper by Sumiyoshi et al. presents a new algorithm for object recognition and pose estimation in a strongly cluttered environment. As an example of how AR/VR can reshape human skills training, the development report of Komizunai et al. demonstrates an endotracheal suctioning simulator that establishes an optimized, spatial display with projector-based AR. Robotics/Cyborg Shor et al. present an augmentation display that uses haptics to go beyond the visual senses. The display has all the elements of a robotic system and is directly coupled to the human hand. In a completely different way, the article by Mitani et al. presents a development in soft robotics: a tongue simulator development (smart sensing and production of soft material), with a detailed account of the production and the technical performance. Finally, to consider novel human-robot interaction, human body tracking is essential. The system presented by Maruyama et al. introduces human motion capture based on IME, in this case the motion of cycling. Co-making Augmented well-being has to consider human-centered design and new collaborative environments where the stakeholders involved in whole product life-cycle work together to deliver better solutions. Inoue et al. propose a generalized decision-making scheme for universal design which considers anthropometric diversity. In the paper by Tanaka et al., paper inspection documents are electronically superimposed on 3D design models to enable design-inspection collaboration and more reliable maintenance activities for large-scale infrastructures. Artificial Intelligence Nakamura et al. propose an optimization-based search for interference-free paths and the poses of equipment in cluttered indoor environments, captured by interactive RGBD scans. AR-based guidance is provided to the user. Finally, the editors would like to express their gratitude to the authors for their exceptional contributions and to the anonymous reviewers for their devoted work. We expect that this special issue will encourage a new departure for research on augmented prototyping for product design and manufacturing. *1 T. H. Davenport and J. Kirby, “Only Humans Need Apply: Winners and Losers in the Age of Smart Machines,” Harper Business, 2016. *2 https://lab.rekimoto.org/about/ [Accessed June 21, 2019]

scholarly journals A re-examination of the role of friction in the original Social Force Model

2020 ◽  
Vol 121 ◽  
pp. 42-53 ◽  
Author(s):  
I.M. Sticco ◽  
G.A. Frank ◽  
F.E. Cornes ◽  
C.O. Dorso
Keyword(s):  
Force Model ◽  
Social Force ◽  
Social Force Model

scholarly journals Crowd Evacuation Guidance Based on Combined Action Reinforcement Learning

Algorithms ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 26
Author(s):  
Yiran Xue ◽  
Rui Wu ◽  
Jiafeng Liu ◽  
Xianglong Tang
Keyword(s):  
Reinforcement Learning ◽  
Guidance System ◽  
Force Model ◽  
Interactive Simulation ◽  
Social Force ◽  
Novel Approach ◽  
Learning Agent ◽  
Network Output ◽  
Combined Action ◽  
Crowd Evacuation

Existing crowd evacuation guidance systems require the manual design of models and input parameters, incurring a significant workload and a potential for errors. This paper proposed an end-to-end intelligent evacuation guidance method based on deep reinforcement learning, and designed an interactive simulation environment based on the social force model. The agent could automatically learn a scene model and path planning strategy with only scene images as input, and directly output dynamic signage information. Aiming to solve the “dimension disaster” phenomenon of the deep Q network (DQN) algorithm in crowd evacuation, this paper proposed a combined action-space DQN (CA-DQN) algorithm that grouped Q network output layer nodes according to action dimensions, which significantly reduced the network complexity and improved system practicality in complex scenes. In this paper, the evacuation guidance system is defined as a reinforcement learning agent and implemented by the CA-DQN method, which provides a novel approach for the evacuation guidance problem. The experiments demonstrate that the proposed method is superior to the static guidance method, and on par with the manually designed model method.

scholarly journals The “Intrinsic Value” of Cultural Heritage as Driver for Circular Human-Centered Adaptive Reuse

2021 ◽  
Vol 13 (6) ◽  
pp. 3231
Author(s):  
Luigi Fusco Girard ◽  
Marilena Vecco
Keyword(s):  
Cultural Heritage ◽  
Intrinsic Value ◽  
Investment Decision ◽  
Adaptive Reuse ◽  
Living Organism ◽  
Integrated Approach ◽  
Human Beings ◽  
Model Concept ◽  
Investment Decision Making ◽  
Instrumental Values

By referring to the European Green Deal, this paper analyzes the “intrinsic value” of cultural heritage by investigating the human-centered adaptive reuse of this heritage. This implies questions such as how to improve the effectiveness of reuse, restoration, and valorization interventions on cultural heritage/landscapes and how to transform a cultural asset into a place, interpreted as a living ecosystem, to be managed as a living organism. The autopoietic characteristic of the eco-bio-systems, specifically focusing on the intrinsic versus instrumental values of cultural heritage ecosystem is discussed in detail. Specifically, the notion of complex social value is introduced to express the above integration. In ecology, the notion of intrinsic value (or “primary value”) relates to the recognition of a value that “pre-exists” any exploitation by human beings. The effectiveness of transforming a heritage asset into a living ecosystem is seen to follow from an integration of these two values. In this context, the paper provides an overview of the different applications of the business model concept in the circular economy, for a better investment decision-making and management in heritage adaptive reuse. Matera case is presented as an example of a cultural heritage ecosystem. To conclude, recommendations toward an integrated approach in managing the adaptive reuse of heritage ecosystem as a living organism are proposed.

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