Research Advance in Swarm Robotics
TL;DR: The current research on the swarm robotic algorithms are presented in detail, including cooperative control mechanisms in swarm robotics for flocking, navigating and searching applications.
About: This article is published in Defence Technology.The article was published on 2013-03-01 and is currently open access. It has received 282 citations till now. The article focuses on the topics: Swarm robotics & Swarm behaviour.
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TL;DR: This paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies which are adaptive, distributed, asynchronous, and verifiably correct.
Abstract: This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.
2,198 citations
TL;DR: The main focus is on studies characterized by distributed control, simplicity of individual robots and locality of sensing and communication, and distributed algorithms are shown to bring cooperation between agents.
337 citations
Cites background from "Research Advance in Swarm Robotics"
...Previous works have been classified on the problem dimension also in other surveys [9, 10]; Mohan and Ponnambalam [11] analyzed various research domains in swarm robotics, however their review does not provide a clear categorization of the state of the art, mixing a classification of some studies in the problem dimension with a description of how other studies differ on aspects such as biological inspiration, communication between robots, control approach and learning....
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TL;DR: This paper presents the basics of swarm robotics and introduces HSI from the perspective of a human operator by discussing the cognitive complexity of solving tasks with swarm systems and identifies the core concepts needed to design a human-swarm system.
Abstract: Recent advances in technology are delivering robots of reduced size and cost. A natural outgrowth of these advances are systems comprised of large numbers of robots that collaborate autonomously in diverse applications. Research on effective autonomous control of such systems, commonly called swarms, has increased dramatically in recent years and received attention from many domains, such as bioinspired robotics and control theory. These kinds of distributed systems present novel challenges for the effective integration of human supervisors, operators, and teammates that are only beginning to be addressed. This paper is the first survey of human–swarm interaction (HSI) and identifies the core concepts needed to design a human–swarm system. We first present the basics of swarm robotics. Then, we introduce HSI from the perspective of a human operator by discussing the cognitive complexity of solving tasks with swarm systems. Next, we introduce the interface between swarm and operator and identify challenges and solutions relating to human–swarm communication, state estimation and visualization, and human control of swarms. For the latter, we develop a taxonomy of control methods that enable operators to control swarms effectively. Finally, we synthesize the results to highlight remaining challenges, unanswered questions, and open problems for HSI, as well as how to address them in future works.
312 citations
Cites background from "Research Advance in Swarm Robotics"
...regarding the performance of a swarm in real applications are not available, apart from some early results in [141], [142], and their general need is identified in several swarm surveys [5], [6], [7]....
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...Another recent survey [7] also includes a list of recent projects and descriptions of physical robots, projects, and simulation platforms....
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...Swarm robotics was originally studied in the context of biological swarms found in nature, but has since become its own distinctive engineering discipline [4], [5], [6], [7], since it promises to be useful in a wide range of potential applications including reconnaissance, environmental monitoring, tracking,...
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TL;DR: A widespread review on various platform and image processing approaches for asphalt surface interpretation based on crack interpretation related to asphalt pavements and a survey of the developed pavement inspection systems up to date are presented.
Abstract: Pavement condition information is a significant component in Pavement Management Systems. The labeling and quantification of the type, severity, and extent of surface cracking is a challenging area for weighing the asphalt pavements. This paper presents a widespread review on various platform and image processing approaches for asphalt surface interpretation. The main part of this study presents a comprehensive combination of the state of the art in image processing based on crack interpretation related to asphalt pavements. An attempt is made to study the existing methodologies from different points of views accompanied by extensive comparisons on three stages of methods—distress detection, classification, and quantification to facilitate further research studies. This paper presents a survey of the developed pavement inspection systems up to date. Additionally, emerging and evolution technologies considered to automate the processes are discussed.
163 citations
TL;DR: This review of seminal works that addressed the problem of target search and tracking in the area of swarm robotics, which is the application of swarm intelligence principles to the control of multi-robot systems, finds variations of the search andtracking problem addressed in the literature.
157 citations
References
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01 Aug 1987
TL;DR: In this article, an approach based on simulation as an alternative to scripting the paths of each bird individually is explored, with the simulated birds being the particles and the aggregate motion of the simulated flock is created by a distributed behavioral model much like that at work in a natural flock; the birds choose their own course.
Abstract: The aggregate motion of a flock of birds, a herd of land animals, or a school of fish is a beautiful and familiar part of the natural world. But this type of complex motion is rarely seen in computer animation. This paper explores an approach based on simulation as an alternative to scripting the paths of each bird individually. The simulated flock is an elaboration of a particle systems, with the simulated birds being the particles. The aggregate motion of the simulated flock is created by a distributed behavioral model much like that at work in a natural flock; the birds choose their own course. Each simulated bird is implemented as an independent actor that navigates according to its local perception of the dynamic environment, the laws of simulated physics that rule its motion, and a set of behaviors programmed into it by the "animator." The aggregate motion of the simulated flock is the result of the dense interaction of the relatively simple behaviors of the individual simulated birds.
7,365 citations
Book•
01 Jan 2004
TL;DR: Ant colony optimization (ACO) is a relatively new approach to problem solving that takes inspiration from the social behaviors of insects and of other animals as discussed by the authors In particular, ants have inspired a number of methods and techniques among which the most studied and the most successful is the general purpose optimization technique known as ant colony optimization.
Abstract: Swarm intelligence is a relatively new approach to problem solving that takes inspiration from the social behaviors of insects and of other animals In particular, ants have inspired a number of methods and techniques among which the most studied and the most successful is the general purpose optimization technique known as ant colony optimization Ant colony optimization (ACO) takes inspiration from the foraging behavior of some ant species These ants deposit pheromone on the ground in order to mark some favorable path that should be followed by other members of the colony Ant colony optimization exploits a similar mechanism for solving optimization problems From the early nineties, when the first ant colony optimization algorithm was proposed, ACO attracted the attention of increasing numbers of researchers and many successful applications are now available Moreover, a substantial corpus of theoretical results is becoming available that provides useful guidelines to researchers and practitioners in further applications of ACO The goal of this article is to introduce ant colony optimization and to survey its most notable applications
6,861 citations
TL;DR: This paper reformulated the manipulator con trol problem as direct control of manipulator motion in operational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and geometric transformation.
Abstract: This paper presents a unique real-time obstacle avoidance approach for manipulators and mobile robots based on the artificial potential field concept. Collision avoidance, tradi tionally considered a high level planning problem, can be effectively distributed between different levels of control, al lowing real-time robot operations in a complex environment. This method has been extended to moving obstacles by using a time-varying artificial patential field. We have applied this obstacle avoidance scheme to robot arm mechanisms and have used a new approach to the general problem of real-time manipulator control. We reformulated the manipulator con trol problem as direct control of manipulator motion in oper ational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and kine matic transformation. Outside the obstacles' regions of influ ence, we caused the end effector to move in a straight line with an...
6,515 citations
"Research Advance in Swarm Robotics" refers background in this paper
...[143] Khatib O....
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...Khatib [143] first introduced this concept in real-time obstacle avoidance in 1986....
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01 Mar 2001
TL;DR: This book is a self-contained introduction to self-organization and complexity in biology - a field of study at the forefront of life sciences research.
Abstract: From the Publisher:
"Broad in scope, thorough yet accessible, this book is a self-contained introduction to self-organization and complexity in biology - a field of study at the forefront of life sciences research."--BOOK JACKET.
2,914 citations
"Research Advance in Swarm Robotics" refers background in this paper
...Of course, in such organism without organizer, there still exist some mechanisms yet undiscovered which promise to divide the whole task into the small pieces for individuals to handle the outputs of agents and aggregates them into the collective behaviors [2]....
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...The group behaviors emerging in the swarms show great flexibility and robustness [2], such as path planning [3], nest constructing [4], task allocation [5] and many...
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