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Selected Papers from the 5th Workshop on Collaboration of Humans, Agents, Robots, Machines and Sensors (CHARMS 2019)

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (31 July 2019) | Viewed by 28908

Special Issue Editors

Prof. Dr. Eric Matson

E-Mail Website
Guest Editor
Department of Computer and Information Technology, Purdue University, 401 North Grant Street, West Lafayette, IN 47907-2121, USA
Interests: multiagent systems and agent organizations; autonomous robotics and intelligent systems
Special Issues, Collections and Topics in MDPI journals
Dr. Donghan Kim

E-Mail Website
Guest Editor
Department of Robotics, Hanyang University ERICA Campus, Ansan, Republic of Korea
Interests: robot navigation; human-robot interaction; service robot; multi-robot system
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Sebastian Rodriguez

E-Mail Website
Guest Editor
Department of Computer Science, Universidad Tecnológica Nacional (UTN), Rivadavia 1050, San Miguel de Tucumán, CPA T4001JJD, Argentina
Interests: agent-oriented software engineering; complex systems modeling and simulation; multiagent systems methodologies; holonic multiagent systems; formal methods for multiagent systems
Prof. Dr. Stéphane Galland

E-Mail Website
Guest Editor
Laboratoire Connaissance et Intelligence Artificielle Distribuées (CIAD), Université de Technologie de Belfort-Montbéliard, 90010 Belfort, France
Interests: multiagent systems; agent-based simulation; Janus multi-agent platform; ASPECS agent-based methodology; Holonic systems; virtual life simulation; 3D and virtual reality; multilevel simulation; urban simulation; transport system simulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Cyber physical systems (CPSs) are becoming more involved in the lives of humans. All indications point to a future where many varieties of CPSs and humans co-exist, and, at a minimum, must interact consistently through life’s tasks with massive amounts of sensors and effectors, and generate massive sensor data. Specifically, how to model, design, validate, implement, and experiment with these complex systems of interaction, communication, and networked relationships are to be explored in this Special Issue. This Special Issue will include ideas of the future that are relevant for understanding, discerning, and developing the relationship between humans and CPSs, as well as the practical nature of the systems that facilitate the integration between humans, agents, robots, machines, and sensors (HARMS).

Papers showing human integration with sensors, machines, robots, and agents, as well as practical experimental results are particularly encouraged, as are papers setting advances in the wider context of large, complex systems, including those involving multiple, heterogeneous actors.

Prof. Dr. Eric Matson
Prof. Dr. Donghan Kim
Prof. Dr. Sebastian Rodriguez
Prof. Dr. Stéphane Galland
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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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

  • Sensors
  • Robot
  • Human–robot interaction
  • HARMS
  • Cyber-physical systems

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Published Papers (6 papers)

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Research

15 pages, 5766 KiB  
Article
Intention Detection Using Physical Sensors and Electromyogram for a Single Leg Knee Exoskeleton
by Dae-Hoon Moon, Donghan Kim and Young-Dae Hong
Sensors 2019, 19(20), 4447; https://doi.org/10.3390/s19204447 - 14 Oct 2019
Cited by 11 | Viewed by 4399
Abstract
In this paper, we present a knee exoskeleton. Due to the complicated structure of the knee, an exoskeleton can limit the wearer’s movement (e.g., when completely sitting down). To prevent this, the proposed exoskeleton is designed to move the ankle part prismatically, so [...] Read more.
In this paper, we present a knee exoskeleton. Due to the complicated structure of the knee, an exoskeleton can limit the wearer’s movement (e.g., when completely sitting down). To prevent this, the proposed exoskeleton is designed to move the ankle part prismatically, so the movement of the wearer is not limited. In addition, the developed exoskeleton could be worn on only one leg, but in this case, it is difficult to detect the intention because the relative relationship information of the two legs is unknown. For this purpose, the length between the knee center of rotation and the ankle (LBKA) was measured and used for intention detection. Using a physical sensor—an encoder and an LBKA sensor, the success rate of intention detection was 82.1%. By additionally using an electromyogram (EMG) sensor, the success rate of intention detection was increased to 92%, and the intention detection was also 27.1 ms faster on average. Full article
(This article belongs to the Special Issue Selected Papers from the 5th Workshop on Collaboration of Humans, Agents, Robots, Machines and Sensors (CHARMS 2019))
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11 pages, 1947 KiB  
Article
A Virtual Pressure and Force Sensor for Safety Evaluation in Collaboration Robot Application
by Heonseop Shin, Sanghoon Kim, Kwang Seo and and Sungsoo Rhim
Sensors 2019, 19(19), 4328; https://doi.org/10.3390/s19194328 - 7 Oct 2019
Cited by 9 | Viewed by 4258
Abstract
Recent developments in robotics have resulted in implementations that have drastically increased collaborative interactions between robots and humans. As robots have the potential to collide intentionally and/or unexpectedly with a human during the collaboration, effective measures to ensure human safety must be devised. [...] Read more.
Recent developments in robotics have resulted in implementations that have drastically increased collaborative interactions between robots and humans. As robots have the potential to collide intentionally and/or unexpectedly with a human during the collaboration, effective measures to ensure human safety must be devised. In order to estimate the collision safety of a robot, this study proposes a virtual sensor based on an analytical contact model that accurately estimates the peak collision force and pressure as the robot moves along a pre-defined path, even before the occurrence of a collision event, with a short computation time. The estimated physical interaction values that would be caused by the (hypothetical) collision were compared to the collision safety thresholds provided within ISO/TS 15066 to evaluate the safety of the operation. In this virtual collision sensor model, the nonlinear physical characteristics and the effect of the contact surface shape were included to assure the reliability of the prediction. To verify the effectiveness of the virtual sensor model, the force and pressure estimated by the model were compared with various experimental results and the numerical results obtained from a finite element simulation. Full article
(This article belongs to the Special Issue Selected Papers from the 5th Workshop on Collaboration of Humans, Agents, Robots, Machines and Sensors (CHARMS 2019))
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19 pages, 8448 KiB  
Article
Development of a Single Leg Knee Exoskeleton and Sensing Knee Center of Rotation Change for Intention Detection
by Dae-Hoon Moon, Donghan Kim and Young-Dae Hong
Sensors 2019, 19(18), 3960; https://doi.org/10.3390/s19183960 - 13 Sep 2019
Cited by 20 | Viewed by 8735
Abstract
In this study, we developed a single leg knee joint assistance robot. Commonly used exoskeletons have a left-right pair, but when only one leg of the wearer is uncomfortable, it is effective to wear the exoskeleton on only the uncomfortable leg. The designed [...] Read more.
In this study, we developed a single leg knee joint assistance robot. Commonly used exoskeletons have a left-right pair, but when only one leg of the wearer is uncomfortable, it is effective to wear the exoskeleton on only the uncomfortable leg. The designed exoskeleton uses a lightweight material and uses a wire-driven actuator, which reduces the weight of the driving section that is attached on the knee directly. Therefore, proposed exoskeleton reduces the force of inertia that the wearer experiences. In addition, the lower frame length of the exoskeleton can be changed to align with the complex movement of the knee. Furthermore, the length between the knee center of rotation and the ankle (LBKA) is measured by using this structure, and the LBKA values are used as the data for intention detection. These value helps to detect the intention because it changes faster than a motor encoder value. A neural network was trained using the motor encoder values, and LBKA values. Neural network detects the intention of three motions (stair ascending, stair descending, and walking), Training results showed that intention detection was good in various environments. Full article
(This article belongs to the Special Issue Selected Papers from the 5th Workshop on Collaboration of Humans, Agents, Robots, Machines and Sensors (CHARMS 2019))
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15 pages, 8162 KiB  
Article
Stability Control and Turning Algorithm of an Alpine Skiing Robot
by Si-Hyun Kim, Bumjoo Lee and Young-Dae Hong
Sensors 2019, 19(17), 3664; https://doi.org/10.3390/s19173664 - 23 Aug 2019
Cited by 6 | Viewed by 3706
Abstract
This paper proposes a general stability control method that uses the concept of zero-moment-point (ZMP) and a turning algorithm with a light detection and ranging (LiDAR) sensor for a bipedal alpine skiing robot. There is no elaborate simulator for skiing robots since the [...] Read more.
This paper proposes a general stability control method that uses the concept of zero-moment-point (ZMP) and a turning algorithm with a light detection and ranging (LiDAR) sensor for a bipedal alpine skiing robot. There is no elaborate simulator for skiing robots since the snow has complicated characteristics, such as compression and melting. However, real experiments are laborious because of the many varied skiing conditions. The proposed skiing simulator could be used, so that a humanoid robot can track its desired turning radius by modeled forces that are similar to real ones in the snow. Subsequently, the robot will be able to pass through gates with LiDAR sensors. By using ZMP control, the robot can avoid falling down while tracking its desired path. The performance of the proposed stabilization method and autonomous turning algorithm are verified by a dynamics simulation software, Webots, and the simulation results are obtained while using the small humanoid robot platform DARwIn-OP. Full article
(This article belongs to the Special Issue Selected Papers from the 5th Workshop on Collaboration of Humans, Agents, Robots, Machines and Sensors (CHARMS 2019))
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7 pages, 1573 KiB  
Communication
Logarithmic Strain Model for Nonlinear Load Cell
by Young-Dae Hong and Bumjoo Lee
Sensors 2019, 19(16), 3486; https://doi.org/10.3390/s19163486 - 9 Aug 2019
Cited by 1 | Viewed by 2877
Abstract
General load cells have typically constant sensitivity throughout the measurement range, which is acceptable for common force measurement systems. However, it is not adequate for high-performance control and high-stroke applications such as robotic systems. It is required to have a higher sensitivity in [...] Read more.
General load cells have typically constant sensitivity throughout the measurement range, which is acceptable for common force measurement systems. However, it is not adequate for high-performance control and high-stroke applications such as robotic systems. It is required to have a higher sensitivity in a small force range than that in a large force range. In contrast, for large loading force, it is more important to increase the measurement range than the sensitivity. To cope with these characteristics, the strain curve versus the force measurement should be derived as a logarithmic graph. To implement this nonlinear nature, the proposed load cell is composed of two mechanical components: an activator, which has a curved surface profile to translocate the contact point, and a linear torque measurement unit with a moment lever to measure the loading force. To approximate the logarithmic deformation, the curvature of the activator was designed by an exponential function. Subsequent design parameters were optimized by an evolutionary computation. Full article
(This article belongs to the Special Issue Selected Papers from the 5th Workshop on Collaboration of Humans, Agents, Robots, Machines and Sensors (CHARMS 2019))
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18 pages, 8432 KiB  
Article
Capture Point-Based Controller Using Real-Time Zero Moment Point Manipulation for Stable Bipedal Walking in Human Environment
by Young-Dae Hong
Sensors 2019, 19(15), 3407; https://doi.org/10.3390/s19153407 - 3 Aug 2019
Cited by 12 | Viewed by 4241
Abstract
For collaboration of humans and bipedal robots in human environments, this paper proposes a stability control method for dynamically modifiable bipedal walking using a capture point (CP) tracking controller. A reasonable reference CP trajectory for the CP tracking control is generated using the [...] Read more.
For collaboration of humans and bipedal robots in human environments, this paper proposes a stability control method for dynamically modifiable bipedal walking using a capture point (CP) tracking controller. A reasonable reference CP trajectory for the CP tracking control is generated using the real-time zero moment point (ZMP) manipulation without information on future footstep commands. This trajectory can be modified at any time during the single support phase according to a given footstep command. Accordingly, this makes it possible for the robot to walk stably with dynamically modifiable walking patterns, including sudden changes in navigational commands during the single support phase. A reference CP trajectory during the double support phase is also generated for continuity. The CP of the robot is controlled to track the reference trajectory using a ZMP-based CP tracking controller. The ZMP while walking is measured by the force-sensing resistor sensors mounted on the sole of each foot. A handling method for infeasible footstep commands is utilized so that the manipulated ZMP satisfies the allowable ZMP region for stability. The validity of the proposed method is verified through simulations and experiments. Full article
(This article belongs to the Special Issue Selected Papers from the 5th Workshop on Collaboration of Humans, Agents, Robots, Machines and Sensors (CHARMS 2019))
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