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    ํƒ€์ด์–ด ๋ชจ๋ธ์„ ์‚ฌ์šฉํ•œ ์ž์œจ ๋“œ๋ฆฌํ”„ํŠธ ์ฃผํ–‰ ์ œ์–ด ์„ค๊ณ„ ๋ฐ ๋ถ„์„

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€, 2019. 2. ์ด๋™์ค€.๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” Wheeled Mobile Robot(WMR)์˜์ž์œจ๋“œ๋ฆฌํ”„ํŠธ ๋“œ๋ผ์ด๋น™ ์ปจํŠธ๋กค๋Ÿฌ๋ฅผ ๋””์ž์ธ ํ•˜๊ณ  ๋ถ„์„ํ•˜๋ฉฐ, ์ด๋ฅผ ์ƒ์šฉ ํ”„๋กœ๊ทธ๋žจ์ธ CarSim์„ ์‚ฌ์šฉํ•œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•˜์—ฌ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ฒ€์ฆ ํ•œ๋‹ค. ์ฒซ์งธ๋กœ, WMR์˜ ๋‹ค์ด๋‚˜๋ฏน์Šค์™€ ํƒ€์ด์–ด ๋ชจ๋ธ์„ ์ •์˜ ํ•˜๊ณ , ์ด๋Ÿฌํ•œ ๋ชจ๋ธ๋กœ ์ธํ•œ ์ œ์•ฝ ์‚ฌํ•ญ์— ๋Œ€ํ•˜์—ฌ ๋…ผ์˜ํ•œ๋‹ค. ๋‹ค์Œ์œผ๋กœ, ์‚ฌ๋žŒ์˜ ๊ด€์ ์—์„œ ๋“œ๋ฆฌํ”„ํŠธ ๋“œ๋ผ์ด๋น™์„ ๋ถ„์„ํ•˜๊ณ , ๋“œ๋ฆฌํ”„ํŠธ ๋“œ๋ผ์ด๋น™ ์ œ์–ด๊ธฐ์˜ ์ œ์–ด ๋ชฉ์ ์„ ์ •์˜ํ•œ๋‹ค. (์ฐจ๋Ÿ‰์˜ ๋ฐฉํ–ฅ๊ณผ ์š” ๊ฐ์†๋„๋ฅผ ์ œ์–ดํ•œ๋‹ค.) ๋“œ๋ฆฌํ”„ํŠธ ๋“œ๋ผ์ด๋น™ ์ œ์–ด๊ธฐ๋Š” ๊ณ -๋ ˆ๋ฒจ ์ œ์–ด, ๋ชฉํ‘œ ๊ฐ’์„ ์ฐพ๊ธฐ ์œ„ํ•œ ์ตœ์ ํ™” ๊ทธ๋ฆฌ๊ณ  ๊ณ -๊ฒŒ์ธ ์ œ์–ด๋กœ ๊ตฌ์„ฑ๋œ๋‹ค. ๋‹ค์Œ์œผ๋กœ, ์ œ์–ดํ•˜์ง€ ์•Š๋Š” ์†๋„์— ๋Œ€ํ•œ ๋ถ„์„์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ์ œ์•ˆํ•œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ CarSim ์‹œ๋ฎฌ ๋ ˆ์ดํ„ฐ๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ์ •์ƒ ์ƒํƒœ์˜ ๋“œ๋ฆฌํ”„ํŠธ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ์™€, ํ—ค์–ดํ•€ ๊ฒฝ๋กœ์— ๋Œ€ํ•œ ๋“œ๋ฆฌํ”„ํŠธ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ๋ฅผ ์ œ์‹œ ํ•œ๋‹ค.Control design and analysis of Wheeled Mobile Robot(WMR) autonomous drift-driving and the simulation experiment using the CarSim simulator are presented and the analysis of the controller proceeds. We first introduce WMR dynamics, tire model and problem formulation of the WMR. We then design drift-driving control using human strategy (control side slip angle and yaw rate). The drift-driving control consists of high-level control, optimization to find desired control input and high-gain control. We analyze the uncontrolled velocity dynamics and stability of the controller. The CarSim simulation results of drift-driving on steady-state equilibriums and the hairpin path with the desired yaw rate are provided.List of Figures - v List of Tables - vi Abbreviations - vii 1 Introduction - 1 1.1 Motivation and related works . . . . . . . . . . . . . . . . . . . . 1 1.2 Contribution of this work . . . . . . . . . . . . . . . . . . . . . . 3 2 System Modeling - 5 2.1 Model dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Tire model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.3 Problemformulation . . . . . . . . . . . . . . . . . . . . . . . . . 9 3 Drift-Driving Control Design - 10 3.1 High-level control . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.2 Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.3 High-gain control . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 4 Analysis of Control - 17 4.1 Internal dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . 17 4.2 Stability analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 5 Simulation Results - 25 5.1 Simulation setup . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 5.2 Steady-state drift-driving . . . . . . . . . . . . . . . . . . . . . . 27 5.3 Hairpin turn drift-driving . . . . . . . . . . . . . . . . . . . . . . 33 6 Conclusion and Future Work - 40 6.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 6.2 Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Maste

    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

    A snake-based scheme for path planning and control with constraints by distributed visual sensors

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    YesThis paper proposes a robot navigation scheme using wireless visual sensors deployed in an environment. Different from the conventional autonomous robot approaches, the scheme intends to relieve massive on-board information processing required by a robot to its environment so that a robot or a vehicle with less intelligence can exhibit sophisticated mobility. A three-state snake mechanism is developed for coordinating a series of sensors to form a reference path. Wireless visual sensors communicate internal forces with each other along the reference snake for dynamic adjustment, react to repulsive forces from obstacles, and activate a state change in the snake body from a flexible state to a rigid or even to a broken state due to kinematic or environmental constraints. A control snake is further proposed as a tracker of the reference path, taking into account the robotโ€™s non-holonomic constraint and limited steering power. A predictive control algorithm is developed to have an optimal velocity profile under robot dynamic constraints for the snake tracking. They together form a unified solution for robot navigation by distributed sensors to deal with the kinematic and dynamic constraints of a robot and to react to dynamic changes in advance. Simulations and experiments demonstrate the capability of a wireless sensor network to carry out low-level control activities for a vehicle.Royal Society, Natural Science Funding Council (China

    Concept and Design of a Hand-held Mobile Robot System for Craniotomy

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    This work demonstrates a highly intuitive robot for Surgical Craniotomy Procedures. Utilising a wheeled hand-held robot, to navigate the Craniotomy Drill over a patient\u27s skull, the system does not remove the surgeons from the procedure, but supports them during this critical phase of the operation

    Climbing and Walking Robots

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    With the advancement of technology, new exciting approaches enable us to render mobile robotic systems more versatile, robust and cost-efficient. Some researchers combine climbing and walking techniques with a modular approach, a reconfigurable approach, or a swarm approach to realize novel prototypes as flexible mobile robotic platforms featuring all necessary locomotion capabilities. The purpose of this book is to provide an overview of the latest wide-range achievements in climbing and walking robotic technology to researchers, scientists, and engineers throughout the world. Different aspects including control simulation, locomotion realization, methodology, and system integration are presented from the scientific and from the technical point of view. This book consists of two main parts, one dealing with walking robots, the second with climbing robots. The content is also grouped by theoretical research and applicative realization. Every chapter offers a considerable amount of interesting and useful information
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