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2020, ArXiv
We present a new version of our previously proposed algorithm enabling a swarm of robots to construct a desired shape from objects in the plane. We also describe a hardware realization for this system which makes use of simple and readily sourced components. We refer to the task as planar construction which is the gathering of ambient objects into some desired shape. As an example application, a swarm of robots could use this algorithm to not only gather waste material into a pile, but shape that pile into a line for easy collection. The shape is specified by an image known as the scalar field. The scalar field serves an analogous role to the template pheromones that guide the construction of complex natural structures such as termite mounds. In addition to describing the algorithm and hardware platform, we develop some performance insights using a custom simulation environment and present experimental results on physical robots.
2020
We present an algorithm by which a swarm of unicycle robots can simultaneously fill multiple planar solid polygonal shapes and also morph between different shapes. By decomposing the desired shape into triangles and defining formation points that lie on each triangle, the robots fill the shape using a divide-and-conquer strategy. Each robot is equipped with limited range and bearing sensors that are used for localized communication and for collision avoidance. The proposed algorithm also allows the swarm to operate in and adapt to dynamic environments, for example, while navigating through narrow passages or avoiding dynamic obstacles. The algorithm is designed to prevent oscillatory behaviour and deadlocks while enabling collision avoidance. We demonstrate the effectiveness of the algorithm through simulations using the iRobot Create mobile robots.
2016
Traditional architecture relies on construction processes that require careful planning and strictly defined outcomes at every stage; yet in nature, millions of relatively simple social insects collectively build large complex nests without any global coordination or blueprint. Here, we present a testbed designed to explore how emergent structures can be assembled using swarms of active robots manipulating passive building blocks in two dimensions. The robot swarm is based on the toy “bristlebot”; a simple vibrating motor mounted on top of bristles to propel the body forward. Since shape largely determines the details of physical interactions, the robot behavior is altered by carefully designing its geometry instead of uploading a digital program. Through this mechanical programming, we plan to investigate how to tune emergent structural properties such as the size and temporal stability of assemblies. Alongside a physical testbed with 200 robots, this work involves comprehensive si...
International Joint Conference on Artificial Intelligence, 2005
We describe a system in which simple, identi- cal, autonomous robots assemble two-dimensional structures using prefabricated modules as build- ing blocks. Modules are capable of some infor- mation processing, enabling them to share long- range structural information and communicate it to robots. This communication allows arbitrary solid structures to be rapidly built using a few x ed, local robot behaviors.
2002
Abstract We introduce a new robotic system, called swarm-bot. The system consists of a swarm of mobile robots with the ability to connect to/disconnect from each other to self-assemble into different kinds of structures. First, we describe our vision and the goals of the project. Then we present preliminary results on the formation of patterns obtained from a grid-world simulation of the system.
2020
This paper investigates a restricted version of robot motion planning, in which particles on a board uniformly respond to global signals that cause them to move one unit distance in a particular direction. We look at the problem of assembling patterns within this model. We first derive upper and lower bounds on the worst-case number of steps needed to reconfigure a general purpose board into a target pattern. We then show that the construction of k-colored patterns of size-n requires Ω(n log k) steps in general, and Ω(n log k+ √ k) steps if the constructed shape must always be placed in a designated output location. We then design algorithms to approach these lower bounds: We show how to construct k-colored 1×n lines in O(n log k+k) steps with unique output locations. For general colored shapes within a w×h bounding box, we achieve O(wh log k+hk) steps.
International Journal of Electrical and Computer Engineering (IJECE), 2020
This project presents a swarming and herding behaviour using simple robots. The main goal is to demonstrate the applicability of artificial intelligence (AI) in simple robotics that can then be scaled to industrial and consumer markets to further the ability of automation. AI can be achieved in many different ways; this paper explores the possible platforms on which to build a simple AI robots from consumer grade microcontrollers. Emphasis on simplicity is the main focus of this paper. Cheap and 8 bit microcontrollers were used as the brain of each robot in a decentralized swarm environment were each robot is autonomous but still a part of the whole. These simple robots don't communicate directly with each other. They will utilize simple IR sensors to sense each other and simple limit switches to sense other obstacles in their environment. Their main objective is to assemble at certain location after initial start from random locations, and after converging they would move as a single unit without collisions. Using readily available microcon-trollers and simple circuit design, semi-consistent swarming behaviour was achieved. These robots don't follow a set path but will react dynamically to different scenarios, guided by their simple AI algorithm.
Neural Computing and Applications, 2010
2007
There are examples of robotic systems in which autonomous mobile robots self-assemble into larger connected entities. However, existing systems display little or no autonomous control over the shape of the connected entity thus formed. We describe a novel distributed mechanism that allows autonomous mobile robots to self-assemble into pre-specified patterns. Global patterns are 'grown'using locally applicable rules and local visual perception only.
Applied Artificial Intelligence, 2004
In this paper we focus on the problem of having a multitude of very simple mobile robots self-organize their relative positions so as to obtain a variety of spatial configurations. The problem has a variety of applications in mobile robotics, modular robots, sensor networks, and computational self-assembly. The approach we investigate in this paper attempts at minimizing the local capability of robots and at verifying how and to which extent a variety of global shapes can be obtained by exploiting simple self-organizing algorithms and emergent behaviors. Several experiments are reported showing the effectiveness of the approach.
Swarm Intelligence, 2008
In certain multi-robot systems, the physical limitations of the individual robots can be overcome using self-assembly-the autonomous creation of physical connections between individual robots to form a larger composite robotic entity. However, existing robotic systems capable of self-assembly have little or no control over the morphology of the self-assembled entities. This restricts the adaptability of such systems, since robots can carry out certain tasks more efficiently if their morphology is specialized to the task. In this paper, we extend the distributed mechanism presented in (Christensen et al. in IEEE Robot. Autom. Mag. 14(4):18-25, 2007) that allows autonomous mobile robots to self-assemble into specific morphologies. We present a simple language, SWARMORPH-script, that allows for concise descriptions of the rules that govern the distributed morphology growth process. Local visual communication allows physically connected robots to send and receive strings. A string can be a rule identifier that triggers execution of predefined logic for extending a morphology. Alternatively, whole scripts can be communicated and subsequently executed on the receiving robot. On real self-propelled robots capable of self-assembly, we demonstrate how specific morphologies can be constructed, how the size of a morphology can be regulated, and how multiple morphologies can be assembled. We also show how the transmission of entire scripts gives the robots the capacity to participate in the formation of morphologies of which they had no a priori knowledge.
2021 7th International Conference on Control, Automation and Robotics (ICCAR), 2021
Social insects in nature such as ants, termites and bees construct their colonies collaboratively in a very efficient process. In these swarms, each insect contributes to the construction task individually showing redundant and parallel behavior of individual entities. But the robotics adaptations of these swarm's behaviors haven't yet made it to the real world at a large enough scale of commonly being used due to the limitations in the existing approaches to the swarm robotics construction. This paper presents an approach that combines the existing swarm construction approaches which results in a swarm robotic system, capable of constructing a given 2 dimensional shape in an optimized manner.
Autonomous Robots, 2018
We address the problem of progressively deploying a set of robots to a formation defined as a point cloud, in a decentralized manner. To achieve this, we present an algorithm that transforms a given point cloud into an acyclic directed graph. This graph is used by the control law to allow a swarm of robots to progressively form the target shape based only on local decisions. This means that free robots (i.e., not yet part of the formation) find their location based on the perceived location of the robots already in the formation. We prove that for a 2D shape it is sufficient for a free robot to compute its distance from two robots in the formation to achieve this objective. We validate our method using physics-based simulations and robotic experiments, showing consistent convergence and minimal formation placement error.
2006
Swarm robotics [3] is a relatively new and rapidly growing field in collective robotics. It involves the study of robotic systems made up of cooperating robots. I have been invited here to report on work we carried out in the SWARM-BOTS project, a project funded by the Future and Emerging Technologies program of the European Commission. This work is directly inspired by the collective behavior of social insect colonies and other animal societies [1, 2].
2008
We address the synthesis of controllers for a swarm of robots to generate a desired two-dimensional geometric pattern specified by a simple closed planar curve with local interactions for avoiding collisions or maintaining specified relative distance constraints. The controllers are decentralized in the sense that the robots do not need to exchange or know each other's state information. Instead, we assume that the robots have sensors allowing them to obtain information about relative positions of neighbors within a known range. We establish stability and convergence properties of the controllers for a certain class of simple closed curves. We illustrate our approach through simulations and consider extensions to more general planar curves.
2002
We present a new robotic concept, called SWARM-BOT, based on a swarm of small and simple autonomous mobile robots called S-BOTs. S-BOTs have a particular assembling capability that allows them to connect physically to other S-BOTs and form a bigger robot entity, the SWARM-BOT. A SWARM-BOT is typically composed by 10 to 30 S-BOTs physically interconnected. S-BOTs can autonomously assemble into a SWARM-BOT but also disassemble again.
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.
2021
We introduce Swarm Fabrication, a novel concept of creating ondemand, scalable, and reconfigurable fabrication machines made of swarm robots. We present ways to construct an element of fabrication machines, such as motors, elevator, table, feeder, and extruder, by leveraging toio robots and 3D printed attachments. By combining these elements, we demonstrate constructing a X-Y-Z plotter with multiple toio robots, which can be used for drawing plotters and 3D printers. We also show the possibility to extend our idea to more general-purpose fabrication machines, which include 3D printers, CNC machining, foam cutters, line drawing devices, pick and place machines, 3D scanning, etc. Through this, we draw a future vision, where the swarm robots can construct a scalable and reconfigurable fabrication machines on-demand, which can be deployed anywhere the user wishes. We believe this fabrication technique will become a means of interactive and highly flexible fabrication in the future.
2003
Swarm-bots are a collection of mobile robots able to self-assemble and to self-organize in order to solve problems that cannot be solved by a single robot. These robots combine the power of swarm intelligence with the flexibility of self-reconfiguration as aggregate swarm-bots can dynamically change their structure to match environmental variations.
Swarm robotics is a fast growing field of multi-robotics. In thisnumber of robots are coordinated in a distributed and uncentralised way. It is based on the use common rules, and simple robots compared to the nature of the task which is to achieve, this task may be complex.Swarm robotics is inspired by social insects. Large number of simple robots is able to perform complex tasks in a more efficient way than a single robot. This improves the efficiency and provides flexibility the group. In this article, an overview of swarm robotics is given, describing its main properties and characteristics and comparing it to general multi-robotic systems. A discussion of the future swarm robotics in real world applications completes this work.
Research in Computing Science, 2019
Swarm robotics is inspired by the behavior of social animals for the coordination of a large number of low cost and insufficient robots that in performing a task requires collaboration. The behavior in a swarm of robots can be manipulated by changing the parameters of repulsion, attraction, orientation and influence (RAOI). In the case of repulsion, attraction and orientation modify the basic behavior of the swarm creating functional groups of robots keeping them close or dispersed, even forming chains. While the influence parameter is associated with specific stimuli to guide the swarm to perform simple tasks. To demonstrate this, a simulation platform presents the impact of these parameters in a swarm of builder robots considering a task of transporting materials.
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