432 research outputs found

    Virtual Structure Based Formation Tracking of Multiple Wheeled Mobile Robots: An Optimization Perspective

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    Today, with the increasing development of science and technology, many systems need to be optimized to find the optimal solution of the system. this kind of problem is also called optimization problem. Especially in the formation problem of multi-wheeled mobile robots, the optimization algorithm can help us to find the optimal solution of the formation problem. In this paper, the formation problem of multi-wheeled mobile robots is studied from the point of view of optimization. In order to reduce the complexity of the formation problem, we first put the robots with the same requirements into a group. Then, by using the virtual structure method, the formation problem is reduced to a virtual WMR trajectory tracking problem with placeholders, which describes the expected position of each WMR formation. By using placeholders, you can get the desired track for each WMR. In addition, in order to avoid the collision between multiple WMR in the group, we add an attraction to the trajectory tracking method. Because MWMR in the same team have different attractions, collisions can be easily avoided. Through simulation analysis, it is proved that the optimization model is reasonable and correct. In the last part, the limitations of this model and corresponding suggestions are given

    Admittance control for collaborative dual-arm manipulation

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    Human-robot collaboration is an appealing solution to increase the flexibility of production lines. In this context, we propose a kinematic control strategy for dual-arm robotic platforms physically collaborating with human operators. Based on admittance control, our approach aims at improving the performance of object transportation tasks by acting on two levels: estimating and compensating gravity effects on one side, and considering human intention in the cooperative task space on the other. An experimental study using virtual reality reveals the effectiveness of our method in terms of reduced human energy expenditure

    Control of Multiple Arm Systems With Rolling Constraints

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    When multiple arms are used to manipulate a large object, it is necessary to maintain and control contacts between the object and effector(s) on one or more arms. The contacts are characterized by holonomic as well as nonholonomic constraints. This paper addresses the control of mechanical systems subject to nonholonomic constraints, rolling constraints in particular. It has been shown that such a system is always controllable, but cannot be stabilized to a single equilibrium by smooth feedback [l, 2]. In this paper, we show that the system is not input-state linearizable though input-output linearization is possible with appropriate output equations. Further, if the system is position-controlled (i.e., the output equation is a functions of position variables only), it has a zero dynamics which is Lagrange stable but not asymptotically stable. We discuss the analysis and controller design for planar as well as spatial multi-arm systems and present results from computer simulations to demonstrate the theoretical results

    Coordinated Control of a Mobile Manipulator

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    In this technical report, we investigate modeling, control, and coordination of mobile manipulators. A mobile manipulator in this study consists of a robotic manipulator and a mobile platform, with the manipulator being mounted atop the mobile platform. A mobile manipulator combines the dextrous manipulation capability offered by fixed-base manipulators and the mobility offered by mobile platforms. While mobile manipulators offer a tremendous potential for flexible material handling and other tasks, at the same time they bring about a number of challenging issues rather than simply increasing the structural complexity. First, combining a manipulator and a platform creates redundancy. Second, a wheeled mobile platform is subject to nonholonomic constraints. Third, there exists dynamic interaction between the manipulator and the mobile platform. Fourth, manipulators and mobile platforms have different bandwidths. Mobile platforms typically have slower dynamic response than manipulators. The objective of the thesis is to develop control algorithms that effectively coordinate manipulation and mobility of mobile manipulators. We begin with deriving the motion equations of mobile manipulators. The derivation presented here makes use of the existing motion equations of manipulators and mobile platforms, and simply introduces the velocity and acceleration dependent terms that account for the dynamic interaction between manipulators and mobile platforms. Since nonholonomic constraints play a critical role in control of mobile manipulators, we then study the control properties of nonholonomic dynamic systems, including feedback linearization and internal dynamics. Based on the newly proposed concept of preferred operating region, we develop a set of coordination algorithms for mobile manipulators. While the manipulator performs manipulation tasks, the mobile platform is controlled to always bring the configuration of the manipulator into a preferred operating region. The control algorithms for two types of tasks - dragging motion and following motion - are discussed in detail. The effects of dynamic interaction are also investigated. To verify the efficacy of the coordination algorithms, we conduct numerical simulations with representative task trajectories. Additionally, the control algorithms for the dragging motion and following motion have been implemented on an experimental mobile manipulator. The results from the simulation and experiment are presented to support the proposed control algorithms

    Research on a semiautonomous mobile robot for loosely structured environments focused on transporting mail trolleys

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    In this thesis is presented a novel approach to model, control, and planning the motion of a nonholonomic wheeled mobile robot that applies stable pushes and pulls to a nonholonomic cart (York mail trolley) in a loosely structured environment. The method is based on grasping and ungrasping the nonholonomic cart, as a result, the robot changes its kinematics properties. In consequence, two robot configurations are produced by the task of grasping and ungrasping the load, they are: the single-robot configuration and the robot-trolley configuration. Furthermore, in order to comply with the general planar motion law of rigid bodies and the kinematic constraints imposed by the robot wheels for each configuration, the robot has been provided with two motorized steerable wheels in order to have a flexible platform able to adapt to these restrictions. [Continues.

    ๋ถ„์‚ฐ ์ œ์•ฝํ•˜์—์„œ ์›๊ฒฉ ์ œ์–ด๋˜๋Š” ๋‹ค์ˆ˜์˜ ๋…ผํ™€๋กœ๋…ธ๋ฏน ์ด๋™ํ˜• ๋กœ๋ด‡ ๋Œ€ํ˜• ์žฌ๊ตฌ์„ฑ ์ œ์–ด

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€, 2019. 2. ์ด๋™์ค€.๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋ณ€ํ™”ํ•˜๋Š” ์ฃผํ–‰ ํ™˜๊ฒฝ์—์„œ ๋ถ„์‚ฐ ์ œ์•ฝ ํ•˜์— ๋‹ค์ˆ˜์˜ ์›๊ฒฉ์œผ๋กœ ์ œ์–ด๋˜๋Š” ๋…ผํ™€๋กœ๋…ธ๋ฏน ์ด๋™ํ˜• ๋กœ๋ด‡ ๋Œ€ํ˜• ์žฌ๊ตฌ์„ฑ ์ œ์–ด์— ๋Œ€ํ•œ ์ƒˆ๋กœ์šด ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ์ œ์‹œํ•˜์˜€๋‹ค. ์„ผ์‹ฑ๊ณผ ์ปดํ“จํŒ… ๋Šฅ๋ ฅ์ด ๊ฐ–์ถ”์–ด์ง„ ์˜จ๋ณด๋“œ ์‹œ์Šคํ…œ ๋กœ๋ด‡๋“ค์„ ํ™œ์šฉํ•˜์—ฌ ์ตœ๊ทผ ๊ฐœ๋ฐœ๋œ ์˜ˆ์ธก ๋””์Šคํ”Œ๋ ˆ์ด ๊ธฐ๋ฒ•์„ ์ ์šฉ, ํšจ์œจ์ ์ธ ๊ตฐ์ง‘ ๋กœ๋ด‡์˜ ์›๊ฒฉ ์ œ์–ด๊ฐ€ ๊ฐ€๋Šฅํ•˜๋„๋ก ํ•˜์˜€๋‹ค. ์ž˜ ์•Œ๋ ค์ง„ ๋…ผํ™€๋กœ๋…ธ๋ฏน ํŒจ์‹œ๋ธŒ ๋””์ปดํฌ์ง€์…˜ ๊ธฐ๋ฒ•์„ ๊ธฐ๋ฐ˜์œผ๋กœ ๋Œ€ํ˜• ๋ณ€๊ฒฝ์ด ๊ฐ€๋Šฅํ•˜๋„๋ก ์ƒˆ๋กœ์šด ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์ถ”๊ฐ€, ๋Œ€ํ˜• ๋ณ€๊ฒฝ๊ฐ„ ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋Š” ๋ฌธ์ œ๋“ค์— ๋Œ€ํ•ด ํŒŒ์•…ํ•˜๊ณ  ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ํฌํ…์…œ ํ•„๋“œ๋ฅผ ํ™œ์šฉํ•˜์˜€๋‹ค. n๋Œ€์˜ ๋กœ๋ด‡์œผ๋กœ ๋‹ค์–‘ํ•œ ๋Œ€ํ˜• ๋ณ€๊ฒฝ์ด ๊ฐ€๋Šฅํ† ๋ก ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ํ™˜๊ฒฝ์„ ์กฐ์„ฑ, 39๋Œ€์˜ ํƒฑํฌ๋ฅผ ์ด์šฉํ•˜์—ฌ์—ฌ 5๊ฐ€์ง€์˜ ๊ฐ๊ธฐ ๋‹ค๋ฅธ ๋Œ€ํ˜•์œผ๋กœ์˜ ๋ณ€ํ™˜์„ ์ƒˆ๋กœ์ด ์ œ์‹œํ•œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ ์šฉํ•˜์—ฌ ๊ตฌํ˜„ํ•˜์˜€๋‹ค. ๋˜ํ•œ ์‹ค์ œ ๋กœ๋ด‡ 3๋Œ€๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ํšจ์šฉ์„ฑ์— ๋Œ€ํ•œ ์‹คํ—˜์„ ํ•„๋‘๋กœ ์ข์€ ๊ธธ๋ชฉ, ๊ฐœํ™œ์ง€ ๋“ฑ ์—ฐ์†์ ์œผ๋กœ ๋ณ€ํ™”ํ•˜๋Š” ํ™˜๊ฒฝ ์†์—์„œ์˜ ๊ตฌ๋™์„ ํ†ตํ•ด ์ตœ์ข…์ ์œผ๋กœ ์ œ์‹œํ•œ ํ”„๋ ˆ์ž„์›Œํฌ์˜ ํƒ€๋‹น์„ฑ์— ๋Œ€ํ•ด ๊ฒ€์ฆํ•˜์˜€๋‹ค.We propose a novel framework for formation reconguration of multiple nonholonomic wheeled mobile robots (WMRs) in the changing driving environment. We utilize an onboard system of WMRs with the capability of sensing and computing. Each WMR has the same computing power for visualizing the driving environment, handling the sensing information and calculating the control action. One of the WMRs is the leader with the FPV camera and SLAM, while others with monocular cameras with limited FoV, as the followers, keep a certain desired formation during driving in a distributed manner. We set two control objectives, one is group driving and the other is holding the shape of the formation. We have to capture the control objectives separately and simultaneously, we make the best use of nonholonomic passive decomposition to split the WMRs' kinematics into those of the formation maintaining and group driving. The repulsive potential function to prevent the collision among WMRs and attractive potential function to restrict the boundary of follower WMRs' moving space due to limited FoV range of the monocular cameras while switching their formation are also used. Simulation with 39 tanks and experiments with three WMRs are also performed to verify the proposed framework.Acknowledgements iii List of Figures vii Abbreviations ix 1 Introduction 1 2 Formation Reconguration Control Design 5 2.1 Nonholonomic Passive Decomposition . . . . . . . . . . . . . . . 5 2.2 Attractive and Repulsive Potential Function . . . . . . . . . . . . 10 2.3 Control Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.4 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3 Estimation and Predictive Display 20 3.1 Distributed Pose Estimation . . . . . . . . . . . . . . . . . . . . . 20 3.1.1 EKF Pose Estimation of Leader WMR . . . . . . . . . . . 20 3.1.2 EKF Pose Estimation of Follower WMRs . . . . . . . . . 22 3.2 Predictive Display for Distributed WMRs Teleoperation . . . . . 23 4 Experiment 27 4.1 Test Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 4.2 Demonstrate the Proposed Algorithm . . . . . . . . . . . . . . . 30 4.3 Teleoperation Experiment with the Algorithm . . . . . . . . . . . 33 5 Conclusion 40Maste

    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

    Cooperative Material Handling by Human and Robotic Agents:Module Development and System Synthesis

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    In this paper we present the results of a collaborative effort to design and implement a system for cooperative material handling by a small team of human and robotic agents in an unstructured indoor environment. Our approach makes fundamental use of human agents\u27 expertise for aspects of task planning, task monitoring, and error recovery. Our system is neither fully autonomous nor fully teleoperated. It is designed to make effective use of human abilities within the present state of the art of autonomous systems. It is designed to allow for and promote cooperative interaction between distributed agents with various capabilities and resources. Our robotic agents refer to systems which are each equipped with at least one sensing modality and which possess some capability for self-orientation and/or mobility. Our robotic agents are not required to be homogeneous with respect to either capabilities or function. Our research stresses both paradigms and testbed experimentation. Theory issues include the requisite coordination principles and techniques which are fundamental to the basic functioning of such a cooperative multi-agent system. We have constructed a testbed facility for experimenting with distributed multi-agent architectures. The required modular components of this testbed are currently operational and have been tested individually. Our current research focuses on the integration of agents in a scenario for cooperative material handling
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