Review
Multidisciplinary Sciences
Haibin Duan, Mengzhen Huo, Yanming Fan
Summary: This article discusses the inspiration of swarm robotics from the collective behaviors of animals and their application in unmanned swarm systems and human-machine systems. Collective behaviors in animals, driven by simple interaction rules, exhibit intelligent properties such as self-organization, robustness, adaptability, and expansibility. These properties have inspired the design of autonomous unmanned swarm systems. The article reviews typical natural collective behaviors, introduces the concept of swarm intelligence, and presents application cases of animal collective behaviors. It also focuses on the progress and bionic achievements of aerial, ground, and marine robotics swarms, mapping biological cooperative mechanisms to cooperative unmanned cluster systems. The significance of coexisting-cooperative-cognitive human-machine systems is considered, and key technologies to be solved are identified as reference directions for future exploration.
NATIONAL SCIENCE REVIEW
(2023)
Article
Computer Science, Artificial Intelligence
Giulia De Masi, Judhi Prasetyo, Raina Zakir, Nikita Mankovskii, Eliseo Ferrante, Elio Tuci
Summary: This paper studies a generalized n model, considering the roles of zealots, informed agents, and uninformed agents in consensus formation, and combines numerical simulations, mathematical models, and physical experiments to demonstrate that having a moderate number of zealots in the decision-making process tends to lead to choosing the highest quality option, and increasing the number of informed agents can offset the impact of adverse zealots.
SWARM INTELLIGENCE
(2021)
Article
Chemistry, Multidisciplinary
Alexandre Campo, Stamatios C. Nicolis, Jean-Louis Deneubourg
Summary: Remembering information is crucial for adaptation and behavior adjustment in both living organisms and artificial systems. Pavlov's experiments demonstrate how single animals can trigger behavioral responses based on memory of stimuli associated with rewards. Researchers propose a novel behavior based on aggregation process to enable robotic swarm to exhibit collective memory.
APPLIED SCIENCES-BASEL
(2021)
Article
Multidisciplinary Sciences
Daniele Carlesso, Justin M. McNab, Christopher J. Lustri, Simon Garnier, Chris R. Reid
Summary: In this study, the researchers combined experimental analyses with theoretical modeling to investigate how animal groups modulate their investment into tasks under uncertain conditions. They found that weaver ants cap their investment into chains and do not form complete chains when the gap is taller than 90 mm. The ants budget the time they spend in chains based on their distance to the ground, and a distance-based model of chain formation explains this tradeoff without invoking complex cognition.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Review
Chemistry, Multidisciplinary
Zool Hilmi Ismail, Mohd Ghazali Mohd Hamami
Summary: This study provides a systematic literature review of swarm robotics (SR) strategies for target search problems with environmental constraints, exploring different approaches for handling various levels of environment complexity and summarizing suitable strategies for real-world applications.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Hardware & Architecture
Zhe Ban, Junyan Hu, Barry Lennox, Farshad Arvin
Summary: This paper proposes an extended model of a self-organised flocking mechanism using heterogeneous swarm system, ensuring a collision-free flocking trajectory for the followers. In addition, an optimal control model is developed to steer the swarm to a desired goal location, with less requirement for power and storage compared to conventional methods.
MOBILE NETWORKS & APPLICATIONS
(2021)
Review
Chemistry, Analytical
Pollyanna G. Faria Dias, Mateus C. Silva, Geraldo P. Rocha Filho, Patricia A. Vargas, Luciano P. Cota, Gustavo Pessin
Summary: Swarm Robotics is a developing study field investigating bio-inspired collaborative control approaches, offering a platform for researchers to explore new knowledge. The paper reviews the essential qualities and features of Swarm Robotics systems, compares them to generic multi-robotic systems, and discusses current hardware platforms and multi-robot simulators.
Article
Computer Science, Artificial Intelligence
Melanie Schranz, Gianni A. Di Caro, Thomas Schmickl, Wilfried Elmenreich, Farshad Arvin, Ahmet Sekercioglu, Micha Sende
Summary: Swarm Intelligence is a multi-agent framework inspired by natural systems, where each agent acts autonomously and collaborates with others without central control. While well-designed swarms have advantages in adaptability, robustness, and scalability, they have not yet transitioned from lab demonstrations to real-world applications, especially in embodied scenarios like swarm robotics.
SWARM AND EVOLUTIONARY COMPUTATION
(2021)
Review
Remote Sensing
Muhammad Muzamal Shahzad, Zubair Saeed, Asima Akhtar, Hammad Munawar, Muhammad Haroon Yousaf, Naveed Khan Baloach, Fawad Hussain
Summary: Swarm robots refer to the coordination of multiple robots to perform collective tasks and problem-solving more efficiently than a single robot. This research area has gained significant interest in the past decade due to its wide range of applications in military and civil fields. By replicating interaction rules from natural swarm systems, such as honey bees and bird flocks, robot swarms can be created.
Article
Robotics
Ahmed Abdelli, Ali Yachir, Abdenour Amamra, Belkacem Khaldi
Summary: Collective decision-making by a swarm of robots is crucial, especially in the problem of collective perception. This problem has recently been formulated as a discrete collective estimation scenario. Existing strategies to resolve this scenario have poor performance or require higher communication bandwidth. In this work, we propose a novel decision-making strategy based on maximum likelihood estimate sharing (MLES) to resolve the discrete collective estimation scenario.
Article
Computer Science, Artificial Intelligence
Roman Miletitch, Andreagiovanni Reina, Marco Dorigo, Vito Trianni
Summary: This study investigates the emergence of naming conventions within a swarm of robots that collectively forage. The research shows that a correlation between language and foraging dynamics is necessary to obtain a useful vocabulary.
SWARM INTELLIGENCE
(2022)
Article
Robotics
Nikolaj Horsevad, Hian Lee Kwa, Roland Bouffanais
Summary: In the study of collective animal behavior, the use of multi-robot systems experiments can provide a powerful tool to deepen our understanding of various forms of swarming and other social animal organizations.
FRONTIERS IN ROBOTICS AND AI
(2022)
Article
Chemistry, Multidisciplinary
Manar Hosny, Rafa Hayel, Najwa Altwaijry
Summary: Online education has become increasingly important in recent years, especially during the COVID-19 pandemic, as a flexible and adaptable means of continuous learning. Online examinations, particularly multiple-choice questions, have become the norm for universities worldwide. However, creating online tests can be a laborious task, leading to the proposal of using the Bees Algorithm (BA), a metaheuristic algorithm, to generate online exams that match the desired difficulty level while considering various constraints. The BA demonstrates superior performance in achieving the desired difficulty level and exhibits robustness across different test cases, but does have limitations in terms of successful solutions and overlap percentage.
APPLIED SCIENCES-BASEL
(2023)
Review
Entomology
Thomas D. Seeley
Summary: Thomas Seeley's research focuses on collective intelligence and natural lives of honey bees. By studying their behavior and social life, he reveals how a honey bee colony functions as a single decision-making unit in the wild.
ANNUAL REVIEW OF ENTOMOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Shanu K. Rakesh, Manish Shrivastava
Summary: Swarm robotics is a field inspired by natural swarms, aiming to study swarm intelligence and collaboration. This paper proposes a fault-tolerant pattern formation algorithm, and through simulations and experiments, it demonstrates the algorithm's ability to successfully form and maintain geometric patterns in the presence of faulty agents.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Hannes Hornischer, Joshua Cherian Varughese, Ronald Thenius, Franz Wotawa, Manfred Fuellsack, Thomas Schmickl
Summary: Robotic swarms and mobile sensor networks are utilized for environmental monitoring, with the CIMAX algorithm facilitating collective decision-making to maximize information gathering in the swarm. The algorithm has been tested in underwater swarm robots for addressing oxygen depletion issues.
Article
Chemistry, Multidisciplinary
Thomas Schmickl, Payam Zahadat, Heiko Hamann
Summary: Evolutionary robotics uses stochastic optimization methods to design control software, which is beneficial when a priori model is not available; it is advantageous for robots operating in unpredictable environments; the Wankelmut task is a benchmark for measuring the evolvability of robot control software towards increasing complexity.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Artificial Intelligence
Melanie Schranz, Gianni A. Di Caro, Thomas Schmickl, Wilfried Elmenreich, Farshad Arvin, Ahmet Sekercioglu, Micha Sende
Summary: Swarm Intelligence is a multi-agent framework inspired by natural systems, where each agent acts autonomously and collaborates with others without central control. While well-designed swarms have advantages in adaptability, robustness, and scalability, they have not yet transitioned from lab demonstrations to real-world applications, especially in embodied scenarios like swarm robotics.
SWARM AND EVOLUTIONARY COMPUTATION
(2021)
Article
Biotechnology & Applied Microbiology
Thomas Schmickl, Martina Szopek, Francesco Mondada, Rob Mills, Martin Stefanec, Daniel N. Hofstadler, Dajana Lazic, Rafael Barmak, Frank Bonnet, Payam Zahadat
Summary: The study introduces a hypothesis suggesting autonomous robots as a potential solution to counteract ecological mass extinction. Through showcasing research projects and developing mathematical models, the study aims to stabilize and support broken ecosystems by introducing robots and assisting in regulating biological behaviors. The research emphasizes the importance of predicting the effects of robotic interventions on the environment in order to successfully apply such technology in the wild.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2021)
Article
Physics, Multidisciplinary
Martin Stefanec, Hannes Oberreiter, Matthias A. Becher, Gundolf Haase, Thomas Schmickl
Summary: Vibratory signals can alter honeybee behavior, with different frequency-amplitude combinations inducing varying responses and influencing the motion activity of individual bees within the colony. This may offer a novel pathway for human-animal interaction and smart beehive technology in future beekeeping.
FRONTIERS IN PHYSICS
(2021)
Article
Electrochemistry
Serge Kernbach
Summary: The para- and ortho-isomers of water and dissolved molecular oxygen have different spin configurations and can be excited to change macroscopically measurable properties of aqueous solutions. This study characterizes the ionic dynamics and surface tension effects of dissolving carbon dioxide and hydrogen peroxide in pure water using electrochemical impedance spectroscopy. The results show distinguishable reaction pathways and anomalous quasi-periodical fluctuations, indicating potential applications in affordable electrochemical sensors and quantum biology.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY
(2022)
Article
Engineering, Multidisciplinary
Serge Kernbach
Summary: This study explores the application of weakly electric fish-inspired coupled nonlinear oscillators in water, which can be used for sensing global environmental parameters, spatial dynamics and distances of AUVs, dielectric object perception, and behavior synchronization. This technology can create global awareness in a group of robots and extend the range limitations of individual AUVs.
BIOINSPIRATION & BIOMIMETICS
(2022)
Article
Biology
S. Kernbach, O. Kernbach
Summary: This work investigates fluctuations in potentiometric pH dynamics under different geomagnetic field configurations. Results show that the dielectric permittivity of environmental objects affects the pH dynamics, and the effects can be explained by the Earth's electric and magnetic fields.
ELECTROMAGNETIC BIOLOGY AND MEDICINE
(2022)
Article
Mathematics, Interdisciplinary Applications
Thomas Schmickl
Summary: This study demonstrates that predictions of emergent phenomena on the macroscopic layer of a complex system can fail when made by a microscopic model. A well-known complex system, Conway's Game of Life, is used to analyze and support this claim. Macroscopic mean-field models are capable of predicting emergent properties after fitting them to simulation data, while micro-to-macro models and mesoscopic modeling approaches fail to make correct predictions. This suggests that some macroscopic system properties should be interpreted as examples of strong emergence due to the lack of a consistent micro-to-macro model that can explain them in advance.
Article
Engineering, Multidisciplinary
Eduard Buss, Till Aust, Mostafa Wahby, Tim-Lucas Rabbel, Serge Kernbach, Heiko Hamann
Summary: Electrical potential and tissue impedance are simple measurement techniques that can be used for studying plant physiology on a macroscopic level. Using statistical and machine learning methods, we successfully classified different stimuli that plants were exposed to. This blackbox approach shows the feasibility of using these techniques for plant research.
BIOINSPIRATION & BIOMIMETICS
(2023)
Article
Robotics
Rafael Barmak, Martin Stefanec, Daniel N. Hofstadler, Louis Piotet, Stefan Schoenwetter-Fuchs-Schistek, Francesco Mondada, Thomas Schmickl, Rob Mills
Summary: Robotic technologies have the capability to interact with living organisms and form integrated mixed societies with them. Biocompatible robots can be used to study collective behaviors previously unattainable with traditional techniques. In this study, a robotic system was designed to observe and modulate the collective behaviors of a bee cluster, effectively influencing its spatiotemporal reorganization. This research opens the door to investigating and interacting with animals in a complete social context, and has potential applications in enhancing the survivability of pollinators crucial to ecosystems and food supply.
Proceedings Paper
Computer Science, Artificial Intelligence
Michael Vogrin, Martin Stefanec, Thomas Schmickl
2020 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI)
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Tomas Luneckas, Mindaugas Luneckas, Ziad Salem, Martina Szopek, Thomas Schmickl
2020 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI)
(2020)
Article
Engineering, Multidisciplinary
Joshua Cherian Varughese, Hannes Hornischer, Payam Zahadat, Ronald Thenius, Franz Wotawa, Thomas Schmickl
BIOINSPIRATION & BIOMIMETICS
(2020)
Article
Computer Science, Theory & Methods
Daniela Kengyel, Payam Zahadat, Franz Wotawa, Thomas Schmickl
INTERNATIONAL JOURNAL OF PARALLEL EMERGENT AND DISTRIBUTED SYSTEMS
(2019)
