Swarm robotics reviewed

Barca, Jan Carlo; Şekercioğlu, Y. Ahmet

doi:10.1017/s026357471200032x

Cited by 169 publications

(116 citation statements)

References 121 publications

Supporting

Mentioning

108

Contrasting

Order By: Relevance

“…Regarding the energy consumption problem, researchers have approached this problem in different ways, including minimizing the weight of robots, pre-positioning energy sources into the environments, minimizing communication ranges of robots, sending data in a simple form [28], reducing the direct communication and the use of multi-hop communication links between robots [29], minimizing the distrance of the traveling path [30,31]. For example, Barca et al addressed the problems related to energy consumption in [32].…”

Section: Related Workmentioning

confidence: 99%

Comparison of bio-inspired algorithms applied to the coordination of mobile robots considering the energy consumption

Palmieri

Yang

Rango

et al. 2017

Neural Comput & Applic

View full text Add to dashboard Cite

Many applications related to autonomous mobile robots require to explore in an unknown environment searching for static targets, without any a priori information about the environment topology and target locations. Targets in such rescue missions can be fire, mines, human victims, or dangerous material that the robots have to handle. In these scenarios, some cooperation among the robots is required for accomplishing the mission. This paper focuses on the application of different bio-inspired metaheuristics for the coordination of a swarm of mobile robots that have to explore an unknown area in order to rescue some distributed targets. This problem is formulated by first defining an optimization model and then considering two subproblems: exploration and recruiting. Firstly, the environment is incrementally explored by robots using a modified version of ant colony optimization. Then, when a robot detects a target, a recruiting mechanism is carried out to recruit more robots to carry out the disarm task together. For this purpose, we have proposed and compared three approaches based on three different bio-inspired algorithms (Firefly Algorithm, Particle Swarm Optimization and Artificial Bee Algorithm). A computational study and extensive simulations have been carried out to assess the behavior of the proposed approaches and to analyze their performance in terms of total energy consumed by the robots to complete

show abstract

Section: Related Workmentioning

confidence: 99%

Comparison of bio-inspired algorithms applied to the coordination of mobile robots considering the energy consumption

Palmieri

Yang

Rango

et al. 2017

Neural Comput & Applic

View full text Add to dashboard Cite

show abstract

“…Swarm robots consist of a large number robotic modules coordinating among each other in a way analogous to the collective behavior of social insects such as ants and bees. In comparison of reconfigurable robots discussed above, individuals in a swarm robotic system may not physically connected to one another (e.g., UAVs) and their collective behaviors are generally guided by simple control mechanisms to collectively execute a complex task Barca and Sekercioglu 2012) like local sensing and communication capabilities, parallelism in task execution, robustness, scalability, heterogeneousness, flexibility and decentralized control (Yogeswaran and Ponnambalam 2010). Swarms of robots have been deployed in many applications.…”

Section: Swarm Roboticsmentioning

confidence: 99%

Reconfigurable swarm robots for structural health monitoring: a brief review

Jahanshahi

Shen

Mondal

et al. 2017

Int J Intell Robot Appl

View full text Add to dashboard Cite

Autonomous monitoring of infrastructure systems offers a promising alternative to manual inspection techniques which are mostly tedious, expensive and prone to error. Robot-based autonomous monitoring systems not only provide higher precision, but they also allow frequent inspection of infrastructure systems at a much lower cost. Recent advancements in robotic systems have led to the development of reconfigurable swarm robots (RSR) that can change their shape and functionality dynamically, without any external intervention. RSR have the advantages of being modular, on-site reconfigurable, multifunctional, incrementally assemble-able, reusable, faulttolerant, and even repairable on the orbit. Newly-developed reconfigurable robots are expected to bring a radical change in the prevailing structural health monitoring techniques, thus augmenting the efficiency, accuracy and affordability of inspection operations. This paper presents a holistic review of the previous studies and state-of-the-art technologies in the field of RSR, and argues that RSR offer great potential advantages from the perspective of monitoring and assessment of civil and mechanical systems. A roadmap for future research has also been outlined based on the limitations of the current methods and anticipated needs of future inspection systems.

show abstract

“…Such interaction schemes are pointed out as desirable in [4] and [2]. It is not clear, however, what the cost of such an interaction scheme is with regard to the operator's ability to observe and control the swarm effectively.…”

Section: Related Workmentioning

confidence: 99%

Human-Robot Swarm Interaction with Limited Situational Awareness

Kapellmann-Zafra

Salomons

Kolling

et al. 2016

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. This paper studies how an operator with limited situational awareness can collaborate with a swarm of simulated robots. The robots are distributed in an environment with wall obstructions. They aggregate autonomously but are unable to form a single cluster due to the obstructions. The operator lacks the bird's-eye perspective, but can interact with one robot at a time, and influence the behavior of other nearby robots. We conducted a series of experiments. They show that untrained participants had marginal influence on the performance of the swarm. Expert participants succeeded in aggregating 85% of the robots while untrained participants, with bird's-eye view, succeeded in aggregating 90%. This demonstrates that the controls are sufficient for operators to aid the autonomous robots in the completion of the task and that lack of situational awareness is the main difficulty. An analysis of behavioral differences reveals that trained operators learned to gain superior situational awareness.

show abstract

Swarm robotics reviewed

Cited by 169 publications

References 121 publications

Comparison of bio-inspired algorithms applied to the coordination of mobile robots considering the energy consumption

Comparison of bio-inspired algorithms applied to the coordination of mobile robots considering the energy consumption

Reconfigurable swarm robots for structural health monitoring: a brief review

Human-Robot Swarm Interaction with Limited Situational Awareness

Contact Info

Product

Resources

About