Jan Carlo Barca

Deakin University

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A survey of dynamic parameter setting methods for nature-inspired swarm intelligence algorithms

Neural Computing and Applications (2019)

Han Duy Phan Kirsten Ellis Jan Carlo Barca Alan Dorin

Swarm intelligence

10.1007/s00521-019-04229-2

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Citations (40)

A Comparison of Clustering vs YOLO for Drone Swarm Centroid Detection

Nisha Kumari Kevin Lee Chathurika Ranaweera Jan Carlo Barca

The rapid advancement of drones has led to the emergence of drone swarm applications in various domains, including surveillance, search and rescue, and package delivery. Efficient coordination and formation control of drone swarms is crucial for accomplishing complex tasks. The research presented in this paper proposes a novel approach for detecting individual drones in drone swarm formations through the utilisation of the K-means clustering algorithm. The algorithm assigns drones to the nearest centroids, creating cohesive subgroups and optimizing formation quality. To assess its efficacy, a comparative analysis is conducted between the K-means clustering algorithm and you only look once (YOLO) based computer vision detection algorithm. Through extensive simulation experiments, it is found that the K-means clustering algorithm outperforms the YOLO-based detection algorithm in terms of formation quality and computational efficiency. It consistently achieves more accurate and stable swarm formations making it suitable for real-time swarm control applications. The results of this presented research open the way for the effective use of drone swarms in a wide range of real-world applications and contribute to the development of cutting-edge swarm control approaches.

Centroid

Drone

10.1109/icrae59816.2023.10458512

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Citations (1)

What is Known from a Network?: Digital Contact Tracing, Privacy, and Pandemics in the Digital Age

SSRN Electronic Journal (2020)

Kelsie Nabben Marta Poblet Jan Carlo Barca

COVID-19 is an unprecedented crisis that has sparked unprecedented responses from governments around the world. These responses pose a threat to democratic stability and civil liberties. Digital contact tracing is just one example of a technology-based crisis response measure that has been rapidly deployed but could have far-reaching negative consequences for society. This paper explores the risks and consequences of collecting, collating, and storing digital data on people’s networks of contacts as a crisis response measure. We aim to inform a discussion on the tradeoffs between the value of creating the data for public health outcomes and the risks to public trust in government and democratic stability. We ask, “What are the privacy risks of digital contact tracing, and what consequences does this have for national security and democratic stability?” We analyze the considerations that governments are taking in designing and deploying digital responses to the crisis in the case of digital contact tracing, and we explore what information can be derived from the data on populations and how this information could be misused in ways that harm democratic principles. We argue that government collection of digital contact tracing data poses a serious threat to civil liberties owing to the potential for the data to become a geopolitical target for hacking and interference in democratic stability through information warfare. We then propose a number of technical considerations and policy settings that are transparent, temporary, and proportionate to limit data vulnerabilities and provide a framework to better safeguard civil liberties and democracy in the digital age.

Contact tracing

Pandemic

Tracing

10.2139/ssrn.3719288

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Citations (0)

Selection of Building Blocks for Adaptive Grammatical Evolution in PSO

Research Square (Research Square) (2022)

Jyotheesh Gaddam Jan Carlo Barca Richard Dazeley Maia Angelova

Abstract In this study, we used grammatical evolution to develop a customised particle swarm optimiser by incorporating adaptive building blocks. This makes the algorithm self-adaptable to the problem instance. Our objective is to provide the means to automatically generate novel population-based meta-heuristics by scoring the building blocks. We propose a new self-adapting algorithm by adaptive selection and scoring of the building blocks to solve multiple problem instances by reducing computation time and iteration count. To achieve our objective, we ranked building blocks that were extracted from a broad set of existing particle swarm optimisers and scored these during the evolutionary process. These scores were provided as an input to the evolutionary process that enabled the replacement of blocks of evolved solutions in cases where they were unable to improve the overall fitness. Our numerical experiments demonstrated that the proposed algorithm with adaptive building blocks reduced the iteration count and computation time with respect to PSO.

Heuristics

Grammatical evolution

10.21203/rs.3.rs-1215035/v1

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Citations (3)

Swarm robotics reviewed

Robotica (2012)

Jan Carlo Barca Y. Ahmet Şekercioğlu

SUMMARY We present a review of recent activities in swarm robotic research, and analyse existing literature in the field to determine how to get closer to a practical swarm robotic system for real world applications. We begin with a discussion of the importance of swarm robotics by illustrating the wide applicability of robot swarms in various tasks. Then a brief overview of various robotic devices that can be incorporated into swarm robotic systems is presented. We identify and describe the challenges that should be resolved when designing swarm robotic systems for real world applications. Finally, we provide a summary of a series of issues that should be addressed to overcome these challenges, and propose directions for future swarm robotic research based on our extensive analysis of the reviewed literature.

Swarm Robotics

Ant robotics

10.1017/s026357471200032x

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Citations (178)

An efficient pose estimation for limited-resourced MAVs using sufficient statistics

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2015)

Ilankaikone Senthooran Jan Carlo Barca Joarder Kamruzzaman Manzur Murshed Hoam Chung

We present a computationally efficient RGB-D based pose estimation solution for less computationally resourced MAVs, which are ideally suited as members in a swarm. Our approach applies the sufficient statistics derived for a least-squares problem to our problem context. RANSAC-based outlier detection in aligning corresponding feature points is a time consuming operation in visual pose estimation. The additive nature of the used sufficient statistics significantly reduces the computation time of the RANSAC procedure since the pose estimation in each test loop can be computed by reusing previously computed sufficient statistics. This eliminates the need for recomputing estimates from scratch each time. A simpler hypotheses testing method gave similar performance in terms of speed but less accurate than our proposed method. We further increase the efficiency by reducing the problem size to four dimensions using attitude data from an Attitude and Heading Reference System (AHRS). Using a real-world dataset, we show that our algorithm saves up to 94% of computation time for the RANSAC-based procedure in pose estimation while improving the accuracy.

RANSAC

Feature (linguistics)

10.1109/iros.2015.7353900

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Citations (3)

Distributed formation control of networked mobile robots in environments with obstacles

Robotica (2014)

Whye Leon Seng Jan Carlo Barca Y. Ahmet Şekercioğlu

SUMMARY A distributed control mechanism for ground moving nonholonomic robots is proposed. It enables a group of mobile robots to autonomously manage formation shapes while navigating through environments with obstacles. The mechanism consists of two stages, with the first being formation control that allows basic formation shapes to be maintained without the need of any inter-robot communication. It is followed by obstacle avoidance, which is designed with maintaining the formation in mind. Every robot is capable of performing basic obstacle avoidance by itself. However, to ensure that the formation shape is maintained, formation scaling is implemented. If the formation fails to hold its shape when navigating through environments with obstacles, formation morphing has been incorporated to preserve the interconnectivity of the robots, thus reducing the possibility of losing robots from the formation. The algorithm has been implemented on a nonholonomic multi-robot system for empirical analysis. Experimental results demonstrate formations completing an obstacle course within 12 s with zero collisions. Furthermore, the system is capable of withstanding up to 25% sensor noise.

Morphing

Obstacle avoidance

Interconnectivity

Nonholonomic system

10.1017/s0263574714002380

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Citations (14)

Hyper-heuristic Online Learning for Self-assembling Swarm Robots

Lecture notes in computer science (2018)

Shuang Yu Aldeida Aleti Jan Carlo Barca Andy Song

Swarm Robotics

10.1007/978-3-319-93698-7_13

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Citations (11)

A distributed framework for supporting 3D swarming applications

Ghazaleh Pour Sadrollah Jan Carlo Barca Asad I. Khan Jens Eliasson Ilankaikone Senthooran

In-flight wireless sensor networks (WSN) are of increased interest owing to efficiency gains in weight and operational lifetime of IP-enabled computers. High impact 3D swarming applications for such systems include autonomous mapping, surveying, servicing, environmental monitoring and disaster site management. For distributed robotic applications, such as quad copter swarms, it is critical that the robots are able to localise themselves autonomously with respect to other robots and to share information. The importance of fast and reliable dissemination of localised information in these elastic three-dimensional networks provides us sufficient reason to present a distributed framework and hardware settings for passing this information pervasively through the swarm. The research field of Internet of Things (IoT) have for several years been addressing issues around low-power, low-bandwidth wireless communication. By applying IoT technologies to the challenges around swarming, new opportunities are created. However, since IoT have been primarily used with stationary devices, the introduction of flying sensors will add more challenges to address.

Swarming (honey bee)

10.1109/iccoins.2014.6868347

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Citations (12)

Flexible Morphogenesis based Formation Control for Multi-Robot Systems

IAES International Journal of Robotics and Automation (IJRA) (2013)

Jan Carlo Barca Eugene Eu-Juin Lee Y. Ahmet Şekercioğlu

10.11591/ijra.v2i1.1459

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Citations (0)