216 research outputs found

    Vision based leader-follower formation control for mobile robots

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    Creating systems with multiple autonomous vehicles places severe demands on the design of control schemes. Robot formation control plays a vital role in coordinating robots. As the number of members in a system rise, the complexity of each member increases. There is a proportional increase in the quantity and complexity of onboard sensing, control and computation. This thesis investigates the control of a group of mobile robots consisting of a leader and several followers to maintain a desired geometric formation --Abstract, page iii

    Design and Development of an Integrated Mobile Robot System for Use in Simple Formations

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    In recent years, formation control of autonomous unmanned vehicles has become an active area of research with its many broad applications in areas such as transportation and surveillance. The work presented in this thesis involves the design and implementation of small unmanned ground vehicles to be used in leader-follower formations. This mechatronics project involves breadth in areas of mechanical, electrical, and computer engineering design. A vehicle with a unicycle-type drive mechanism is designed in 3D CAD software and manufactured using 3D printing capabilities. The vehicle is then modeled using the unicycle kinematic equations of motion and simulated in MATLAB/Simulink. Simple motion tasks are then performed onboard the vehicle utilizing the vehicle model via software, and leader-follower formations are implemented with multiple vehicles

    Comprehensive review on controller for leader-follower robotic system

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    985-1007This paper presents a comprehensive review of the leader-follower robotics system. The aim of this paper is to find and elaborate on the current trends in the swarm robotic system, leader-follower, and multi-agent system. Another part of this review will focus on finding the trend of controller utilized by previous researchers in the leader-follower system. The controller that is commonly applied by the researchers is mostly adaptive and non-linear controllers. The paper also explores the subject of study or system used during the research which normally employs multi-robot, multi-agent, space flying, reconfigurable system, multi-legs system or unmanned system. Another aspect of this paper concentrates on the topology employed by the researchers when they conducted simulation or experimental studies

    Mobile Robots

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    The objective of this book is to cover advances of mobile robotics and related technologies applied for multi robot systems' design and development. Design of control system is a complex issue, requiring the application of information technologies to link the robots into a single network. Human robot interface becomes a demanding task, especially when we try to use sophisticated methods for brain signal processing. Generated electrophysiological signals can be used to command different devices, such as cars, wheelchair or even video games. A number of developments in navigation and path planning, including parallel programming, can be observed. Cooperative path planning, formation control of multi robotic agents, communication and distance measurement between agents are shown. Training of the mobile robot operators is very difficult task also because of several factors related to different task execution. The presented improvement is related to environment model generation based on autonomous mobile robot observations

    Proposal for the Initiation of General and Military Specific Benchmarking of Robotic Convoys

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    This paper identifies the need for a standard method of benchmarking emerging robotic systems with a focus on military, multi-robot convoys. Benchmarking is commonly used throughout academia and industry as a method of evaluating and comparing products. In this paper we propose a generic form that these benchmarks may take in the future. Classification categories, such as, obstacle avoidance, area mapping, and convoy coherence are all possible elements of this benchmark. The goal is a standard benchmark that can be used to evaluate military multi-robot convoy systems

    Assistive Formation Maintenance for Human-Led Multi-Robot Systems

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    ©2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Presented at the 2009 IEEE International Conference on Systems, Man and Cybernetics,11-14 Oct. 2009, San Antonio, TX.DOI: 10.1109/ICSMC.2009.5346357In ground-based military maneuvers, group formations require flexibility when traversing from one point to the next. For a human-led team of semi-autonomous agents, a certain level of awareness demonstrated by the agents regarding the quality of the formation is preferable. Through the use of a Multi-Robot System (MRS), this work combines leader-follower principles augmented by an assistive formation maintenance (AFM) method to improve formation keeping and demonstrate a formation-in-motion concept. This is achieved using the Robot Mean Task Allocation method (RTMA), a strategy used to allocate formation positions to each unit within a continuously mobile MRS. The end goal is to provide a military application that allows a soldier to efficiently tele-operate a semi-autonomous MRS capable of holding formation amidst a cluttered environment. Baseline simulation is performed in Player/Stage to show the applicability of our developed model and its potential for expansive research

    Control and coordination for a group of mobile robots in unknown environments

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    This thesis studies the trajectory tracking and cooperative behavior for a team of mobile robots using nonlinear and intelligent algorithms to more efficiently achieve the mission outcome. There are many practical applications where specific tasks are more resourcefully achieved by using a group of mobile robots rather than a single robot. Mobile robots can subdivide and multi-task the mission with speed and accuracy and the ability to be individually modified for precise tasks makes them ideally suited for applications such as search and rescue, exploration or entertainment. When comparing the mission outcome of a group of multi mobile robots (MMR) to that of a single robot, we see that the performance of the MMR group improves the specific task allocation, safety, the time duration required and the system effectiveness to achieve the outcome. In order to create the most effective control algorithm for trajectory tracking, we present three different techniques including Lyapunov technique, intelligent control (fuzzy control) and the exponential version of sliding mode. The developed algorithms instruct a robot to keep moving on their desired trajectory while simultaneously reducing tracking errors. The experimental results when using a single mobile robot are presented to demonstrate the potential and capability of the developed algorithms. In order to coordinate a group of mobile robots to achieve a common outcome, the goal is to create efficient system architecture and a control algorithm that enables them to work both individually and in meaningful robot formations. This is achieved by employing coordination and trajectory tracking techniques with the knowledge derived by the localization of the robots from their environment. Three different hierarchical controllers are presented based on nonlinear and intelligent techniques in order to construct an algorithm that exhibits both group cooperation and coordination for a team of mobile robots. These controllers consist of Lyapunov technique, intelligent control (fuzzy control) and the exponential version of sliding mode. For improved trajectory tracking, each robot is fitted with onboard sensors. When an obstacle is detected by any of the robots’ sensors, they direct that robot to move around the obstacle by changing its velocity and direction. As well as obstacle avoidance, the controllers work to make the MMR group arrive concurrently at their target points by adjusting each of the individual robots’ velocities as they move along their desired trajectories. This means the group will arrive at their destination within the same time duration, regardless of the length of each individual trajectory or number of obstacles that confront each robot. The experimental results obtained using three mobile robots display the performance of these control algorithms in producing a cooperative and coordinated behavior for the robot group
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