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In this paper we described the hardware architecture of an inexpensive, heterogeneous, mobile robot swarm, designed and developed at RISC lab, University of Bridgeport. Each UB robot swarm is equipped with sensors, actuators, control and communication units, power supply, and interconnection mechanism. Robot swarms have become a new research paradigm in the last ten years offering novel approaches, such as self-reconfigurabity, self-assembly, self-replication and self-learning. Developing a multi-agent robot system with heterogeneity and larger behavioral repertoire is a great challenge. This robot swarm is capable of performing user defined tasks such as wall painting, mapping, human rescue operations, task allocation, obstacle avoidance, and object transportation.
2016
In this paper we described the hardware architecture of an inexpensive, heterogeneous, mobile robot swarm, designed and developed at RISC lab, University of Bridgeport. Each UB robot swarm is equipped with sensors, actuators, control and communication units, power supply, and interconnection mechanism. Robot swarms have become a new research paradigm in the last ten years offering novel approaches, such as self-reconfigurabity, self-assembly, selfreplication and self-learning. Developing a multi-agent robot system with heterogeneity and larger behavioral repertoire is a great challenge.
In this work we present the hardware architecture of a mobile heterogeneous robot swarm, designed and implemented at the Interdisciplinary Robotics, Intelligent Sensing and Control (RISC) Laboratory, University of Bridgeport. Most of the recent advances in swarm robotics have mainly focused on homogeneous robot swarms and their applications. Developing and coordinating a multi-agent robot system with heterogeneity and a larger behavioral repertoire is a great challenge. To give swarm hardware heterogeneity we have equipped each swarm robot with different set of sensors, actuators, control and communication units, power supply, and an interconnection mechanism. This paper discusses the hardware heterogeneity of the robotic swarm and its challenges. Another issue addressed in paper is the active power management of the robotic agents. The power consumption of each robot in the UB robot swarm is calculated and the power management technique is also explained in this paper. We applied this heterogeneous robot swarm to perform three sample tasks – Mapping task, human rescue task and wall painting task. Copyright © Research Institute for Intelligent Computer Systems, 2015. All rights reserved.
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.
This paper describes the design, development and implementation procedures of a swarm-robotics project at the Machine Intelligence Laboratory (MIL) at the University of Florida. The main objective of this work is to develop a multipurpose and powerful platform for the study and improvement of swarm robotics techniques. The first objective is to produce a set of at least eight small expandable (and easily replicated) robots with on-robot sensory and processing abilities, and with a communication system for off-robot sensors and processing. The second goal is the creation of a cross language platform composed of code written in C, C++ and C#; with a well designed objectoriented platform that closely follows the main paradigms and ideas of object-oriented programming techniques. This paper presents the current state of the ongoing project to create a lowcost, reliable, robust, reusable, movable, size-efficient, powersaving, wireless-capable, and dynamically programmable multiuse research project.
Innovations and Advances in Computing, Informatics, Systems Sciences, Networking and Engineering, 2014
Swarm robotics is one of the most fascinating and new research areas of recent decades, and one of the grand challenges of robotics is the design of swarm robots that are self-sufficient. This can be crucial for robots exposed to environments that are unstructured or not easily accessible for a human operator, such as the inside of a blood vessel, a collapsed building, the deep sea, or the surface of another planet. In this paper, we present a comprehensive study on hardware architecture and several other important aspects of modular swarm robots, such as self-reconfigurability, self-replication, and self-assembly. The key factors in designing and building a group of swarm robots are cost and miniaturization with robustness, flexibility, and scalability. In robotics intelligence, self-assembly and self-reconfigurability are among the most important characteristics as they can add additional capabilities and functionality to swarm robots. Simulation and model design for swarm robotics is highly complex and expensive, especially when attempting to model the behavior of large swarm robot groups.
2013
Swarm robotics is one of the most fascinating and new research areas of recent decades, and one of the grand challenges of robotics is the design of swarm robots that are self-sufficient. This can be crucial for robots exposed to environments that are unstructured or not easily accessible for a human operator, such as the inside of a blood vessel, a collapsed building, the deep sea, or the surface of another planet. In this paper, we present a comprehensive study on hardware architecture and several other important aspects of modular swarm robots, such as self-reconfigurability, self-replication, and self-assembly. The key factors in designing and building a group of swarm robots are cost and miniaturization with robustness, flexibility, and scalability. In robotics intelligence, self-assembly and self-reconfigurability are among the most important characteristics as they can add additional capabilities and functionality to swarm robots. Simulation and model design for swarm robotics is highly complex and expensive, especially when attempting to model the behavior of large swarm robot groups.
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.
2010
We study how a swarm robotic system consisting of two different types of robots can solve a foraging task. The first type of robots are small wheeled robots, called foot-bots, and the second type are flying robots that can attach to the ceiling, called eye-bots. While the footbots perform the actual foraging, i.e. they move back and forth between a source and a target location, the eye-bots are deployed in stationary positions against the ceiling, with the goal of guiding the foot-bots. The key component of our approach is a process of mutual adaptation, in which foot-bots execute instructions given by eye-bots, and eye-bots observe the behavior of foot-bots to adapt the instructions they give. Through a simulation study, we show that this process allows the system to find a path for foraging in a cluttered environment. Moreover, it is able to converge onto the shortest of two paths, and spread over different paths in case of congestion. Since our approach involves mutual adaptation between two sub-swarms of different robots, we refer to it as cooperative self- * Corresponding author. This work was partially supported by the SWARMANOID project, funded by the Future and Emerging Technologies programme (IST-FET) of the European Commission under grant IST-022888. The information provided is the sole responsibility of the authors and does not reflect the European Commissions opinion. The European Commission is not responsible for any use that might be made of data appearing in this publication.
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.
Autonomous …, 2004
The swarm intelligence paradigm has proven to have very interesting properties such as robustness, flexibility and ability to solve complex problems exploiting parallelism and self-organization. Several robotics implementations of this paradigm confirm that these properties can be exploited for the control of a population of physically independent mobile robots.
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