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Swarm Robot - UB Heterogeneous Swarm Robots

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Tamer Abukhalil
added a research item
Adoption of new innovated technologies has become an important requirement for a successful development and implementation of computer systems. Mobile cloud learning is a relatively recent paradigm shift that provides significant promise for meeting future education development and delivery requirements based on mobile cloud computing. The focal point of this study is to develop a conceptual model which highlights the effects of information cultural factors on the adoption of mobile cloud learning in higher education environments. The proposed model is developed based on four identified information cultural variables, namely information integrity, formality, control and pro-activeness. A pilot survey is conducted to test the questionnaire using a small sample of information systems experts and university lecturers. The results show acceptable reliability and validity of the instrument. Finally, conclusions, possible practical contributions of this study and some of the directions for upcoming research are discussed.
Tamer Abukhalil
added 2 research items
This article presents a high-level configuration and task assignment software package that distributes algorithms on a swarm of robots. The software allows the robots to operate in a swarm fashion. When the swarm robotic system adopts a decentralized approach, the desired collective behaviors emerge from local decisions made by the robots themselves according to their environment. Using its GUI, the proposed system expects the operator to select between several available robot agents and assign the swarm of robots a particular task from a set of available tasks.
Madhav Patil
added a research item
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.
Madhav Patil
added a research item
Swarmrobotics is one of themost 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 swarmrobots, such as self-reconfigurability, self-replication, and self-assembly.The key factors in designing and building a group of swarmrobots are cost and miniaturizationwith 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.
Madhav Patil
added 7 research items
The objective of this work is to develop a framework that can deploy and provide coordination between multiple heterogeneous agents when a swarm robotic system adopts a decentralized approach; each robot evaluates its relative rank among the other robots in terms of travel distance and cost to the goal. Accordingly, robots are allocated to the sub-tasks for which they have the highest rank (utility). This paper provides an analysis of existing swarm control environments and proposes a software environment that facilitates a rapid deployment of multiple robotic agents. The framework (UBSwarm) exploits our utility-based task allocation algorithm. UBSwarm configures these robots and assigns the group of robots a particular task from a set of available tasks. Two major tasks have been introduced that show the performance of a robotic group. This robotic group is composed of heterogeneous agents. In the results, a premature example that has prior knowledge about the experiment shows whether or not the robots are able to accomplish the task.
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.