9 research outputs found

    ์ง์ง„ ์ฃผํ–‰ ์„ฑ๋Šฅ ํ–ฅ์ƒ์„ ์œ„ํ•œ ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡์˜ ์ƒˆ๋กœ์šด ๋ฐ”ํ€ด ๋ฐฐ์น˜

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€, 2013. 2. ์ฃผ์ข…๋‚จ.๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡์€ 2์ฐจ์› ๊ตฌ๋™ ํ‰๋ฉด์—์„œ 3์ž์œ ๋„๋ฅผ ๊ฐ€์ง€๋ฉฐ ์–ด๋Š ๋ฐฉํ–ฅ์œผ๋กœ๋‚˜ ํšŒ์ „ ๋ฐ ์ด๋™์ด ์ž์œ ๋กœ์šด ๋กœ๋ด‡์ด๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡์˜ ์ง์ง„ ์ฃผํ–‰ ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ์‹œํ‚ค๊ธฐ ์œ„ํ•ด ์ƒˆ๋กœ์šด ๋ฐ”ํ€ด ๋ฐฐ์น˜๋ฅผ ๊ฐ€์ง€๋Š” ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡์„ ์ œ์•ˆํ•œ๋‹ค. ์ƒˆ๋กญ๊ฒŒ ์ œ์•ˆ๋œ ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡์€ ๋ฐ”ํ€ด์˜ ํšŒ์ „๋ฐฉํ–ฅ์ด ๋กœ๋ด‡์˜ ์งˆ๋Ÿ‰์ค‘์‹ฌ์—์„œ ์›์ฃผ๋ฐฉํ–ฅ์„ ํ–ฅํ•˜๋Š” ๋ฐ”ํ€ด ๋ฐฐ์น˜๋ฅผ ๊ฐ€์ง€๋Š” ๊ธฐ์กด์˜ ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡๊ณผ ๋‹ฌ๋ฆฌ ๋ฐ”ํ€ด์˜ ํšŒ์ „๋ฐฉํ–ฅ์ด ๋กœ๋ด‡์˜ ์งˆ๋Ÿ‰์ค‘์‹ฌ์„ ํ–ฅํ•˜๋Š” ๋ฐ”ํ€ด ๋ฐฐ์น˜๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ์ƒˆ๋กญ๊ฒŒ ์ œ์•ˆ๋œ ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡์€ ์ด๋Ÿฌํ•œ ๋ฐ”ํ€ด ๋ฐฐ์น˜๋กœ ์ธํ•˜์—ฌ ์ง์ง„ ์ฃผํ–‰ ์‹œ์— ๋กœ๋ด‡์˜ ํšŒ์ „ ๋ชจ๋ฉ˜ํŠธ๊ฐ€ ์ƒ์„ฑ๋˜์ง€ ์•Š์•„ ์ œ์–ด๊ฐ€ ๊ฐ„๋‹จํ•˜๋‹ค. ๋˜ํ•œ, 3๊ฐœ์˜ ๋ฐ”ํ€ด๋ฅผ ๋ชจ๋‘ ๊ตฌ๋™์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š” ์žฅ์ ์œผ๋กœ ์ธํ•ด ์ง์ง„ ์ฃผํ–‰ ์„ฑ๋Šฅ์ด ๋›ฐ์–ด๋‚  ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๊ธฐ์กด์˜ ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡๊ณผ๋Š” ๋‹ฌ๋ฆฌ ๋ถ€๊ฐ€์ ์œผ๋กœ ์ƒ์„ฑ๋˜๋Š” ์ €ํ•ญ์ด ์—†์–ด ์ถ”๊ฐ€์ ์œผ๋กœ ์žฅ์ฐฉํ•ด์•ผ ํ•  ๋ถ€ํ’ˆ ์ˆ˜๋„ ์ค„์ผ ์ˆ˜ ์žˆ๋‹ค. ์ œ์•ˆ๋œ ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡๊ณผ ๊ธฐ์กด์˜ ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡์˜ ์ง์ง„ ์ฃผํ–‰ ์„ฑ๋Šฅ์„ ๋น„๊ตํ•˜๊ธฐ ์œ„ํ•ด์„œ ๋งˆ์ฐฐ์‹คํ—˜์„ ํ†ตํ•˜์—ฌ ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡์ด ์ฃผํ–‰ ์‹œ์— ํ•„์—ฐ์ ์œผ๋กœ ๋ฐœ์ƒํ•˜๋Š” ๋งˆ์ฐฐ๊ณผ ๋ฏธ๋„๋Ÿฌ์ง์„ ๊ณ ๋ คํ•œ ๋™์  ๋ชจ๋ธ๋ง์„ ์ด๋Œ์–ด ๋‚ด์—ˆ๋‹ค. ์ด๋Œ์–ด๋‚ธ ๋กœ๋ด‡์˜ ๋™์  ๋ชจ๋ธ๋ง์„ ์ด์šฉํ•ด ๋‘ ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡์˜ ์ง์ง„ ์ฃผํ–‰์„ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ•˜์˜€์œผ๋ฉฐ ๊ทธ ๊ฒฐ๊ณผ ์ƒˆ๋กญ๊ฒŒ ์ œ์•ˆ๋œ ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡์˜ ์ง์ง„ ์ฃผํ–‰ ์„ฑ๋Šฅ์ด 1.5๋ฐฐ ์ƒํ–ฅ๋œ ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ์ด๋ฅผ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•ด ์‹ค์ œ ์ œ์ž‘๋œ ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡๊ณผ ์ดˆ๊ณ ์† ์นด๋ฉ”๋ผ๋ฅผ ์ด์šฉํ•ด ์‹ค์ œ ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡์˜ ์ฃผํ–‰๊ณผ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ๋ฅผ ๋น„๊ตํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, ๋งˆ์ฐฐ์‹คํ—˜์„ ์ด์šฉํ•˜์—ฌ ์ด๋Œ์–ด๋‚ธ ๋กœ๋ด‡์˜ ๋™์  ๋ชจ๋ธ๋ง์ด ์‹ค์ œ์˜ ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡์˜ ์ฃผํ–‰๊ณผ ์ผ์น˜ํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ์œผ๋ฉฐ ์ƒˆ๋กญ๊ฒŒ ์ œ์•ˆ๋œ ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡์ด ๊ธฐ์กด์˜ ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡๋ณด๋‹ค ์ง์ง„ ์ฃผํ–‰ ์„ฑ๋Šฅ์ด ์šฐ์ˆ˜ํ•˜๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค.๊ตญ๋ฌธ ์ดˆ๋ก โ…ฐ ๋ชฉ์ฐจ โ…ฒ ๊ทธ๋ฆผ ๋ชฉ์ฐจ โ…ด ํ‘œ ๋ชฉ์ฐจ โ…ถ ์ œ 1 ์žฅ ์„œ๋ก  1 1.1 ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ 1 1.2 ๋กœ๋ด‡์˜ ๊ตฌ๋™๋ ฅ๊ณผ ๋ฏธ๋„๋Ÿฌ์ง 3 1.3 ์—ฐ๊ตฌ ๋ชฉ์  5 ์ œ 2 ์žฅ ๋ฐ”ํ€ด์˜ ๋™์  ๋ชจ๋ธ๋ง 10 2.1 ๋ฐ”ํ€ด์˜ ๊ตฌ๋™๋ ฅ๊ณผ ๋ฏธ๋„๋Ÿฌ์ง 10 2.2 ๋ฐ”ํ€ด์˜ ๊ตฌ๋™๋ฐฉ์ •์‹ 11 2.3 ๋งˆ์ฐฐ์‹คํ—˜ ์žฅ์น˜ ๊ตฌ์„ฑ 13 2.4 ๋งˆ์ฐฐ์‹คํ—˜ ๊ฒฐ๊ณผ 16 ์ œ 3 ์žฅ ๋กœ๋ด‡์˜ ๋™์  ๋ชจ๋ธ๋ง 17 3.1 ๊ธฐ์กด์˜ ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡์˜ ๋™์  ๋ชจ๋ธ๋ง 17 3.2 ์ƒˆ๋กœ์šด ๋‹ค์ค‘ ์ด๋™ ๋กœ๋ด‡์˜ ๋™์  ๋ชจ๋ธ๋ง 19 3.3 ๋กœ๋ด‡์˜ ๋™์  ๋ชจ๋ธ๋ง์˜ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฐ ๊ฒฐ๊ณผ 20 ์ œ 4 ์žฅ ๊ฒ€์ฆ 24 4.1 ๊ฒ€์ฆ์„ ์œ„ํ•œ ์‹คํ—˜ ์žฅ์น˜ ๊ตฌ์„ฑ 24 4.2 ๊ฒ€์ฆ ์‹คํ—˜ ๊ฒฐ๊ณผ 25 ์ œ 5 ์žฅ ๊ฒฐ๋ก  29 ์ฐธ๊ณ  ๋ฌธํ—Œ 31 Abstract 34Maste

    Dynamics and vibration analysis of the interface between a non-rigid sphere and omnidirectional wheel actuators

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    This paper presents analysis of the dynamics and vibration of an orientation motion platform utilizing a sphere actuated by omnidirectional wheels. The purpose of the analysis is to serve as a design tool for the construction of a six-degree-of-freedom motion platform with unlimited rotational motion. The equations of motion are presented taking flexibility of the system into account. The behaviour of the system is illustrated by sample configurations with a range of omnidirectional wheel types and geometries. Vibration analysis follows, and

    Stability analysis of non-holonomic inverted pendulum system

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    The inverted pendulum is doubtlessly one of the most famous control problems found in most control text books and laboratories worldwide. This popularity comes from the fact that the inverted pendulum exhibits nonlinear, unstable and non-minimum phase dynamics. The basic control objective of the study is to design a controller in order to maintain the upright position of the pendulum while also controlling the position of the cart. In our study we explored the relationship that the tuning parameters (weight on the position of the car and the angle that the pendulum makes with the vertical) of a classical inverted pendulum on a cart has on the pole placement and hence on the stability of the system. We then present a family of curves showing the local root-locus and develop relationships between the weight changes and the system performance. We describe how these locus trends provide insight that is useful to the control designer during the effort to optimize the system performance. Finally, we use our general results to design an effective feedback controller for a new system with a longer pendulum, and present experiment results that demonstrate the effectiveness of our analysis. We then designed a simulation-based study to determine the stability characteristics of a holonomic inverted pendulum system. Here we decoupled the system using geometry as two independent one dimensional inverted pendulum and observed that the system can be stabilized using this method successfully with and without noise added to the system. Next, we designed a linear system for the highly complex inverted pendulum on a non-holonomic cart system. Overall, the findings will provide valuable input to the controller designers for a wide range of applications including tuning of the controller parameters to design of a linear controller for nonlinear systems

    Design of a Mobile Robotic Platform with Variable Footprint

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    This thesis presents an in-depth investigation to determine the most suitable mobile base design for a powerful and dynamic robotic manipulator. It details the design process of such a mobile platform for use in an indoor human environment that is to carry a two-arm upper-body humanoid manipulator system. Through systematic dynamics analysis, it was determined that a variable footprint holonomic wheeled mobile platform is the design of choice for such an application. Determining functional requirements and evaluating design options is performed for the platformโ€™s general configuration, geometry, locomotion system, suspension, and propulsion, with a particularly in-depth evaluation of the problem of overcoming small steps. Other aspects such as processing, sensing and the power system are dealt with sufficiently to ensure the feasibility of the overall proposed design. The control of the platform is limited to that necessary to determine the appropriate mechanical components. Simulations are performed to investigate design problems and verify performance. A basic CAD model of the system is included for better design visualization. The research carried out in this thesis was performed in cooperation with the German Aerospace Center (Deutsches Zentrum fรผr Luft- und Raumfahrt)โ€™s Robotics and Mechatronics Institute (DLR RM). The DLR RM is currently utilizing the findings of this research to finish the development of the platform with a target completion date of May 2008

    Mobile Robot Localization Based on Kalman Filter

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    Robot localization is one of the most important subjects in the Robotics science. It is an interesting and complicated topic. There are many algorithms to solve the problem of localization. Each localization system has its own set of features, and based on them, a solution will be chosen. In my thesis, I want to present a solution to find the best estimate for a robot position in certain space for which a map is available. The thesis started with an elementary introduction to the probability and the Gaussian theories. Simple and advanced practical examples are presented to illustrate each concept related to localization. Extended Kalman Filter is chosen to be the main algorithm to find the best estimate of the robot position. It was presented through two chapters with many examples. All these examples were simulated in Matlab in this thesis in order to give the readers and future students a clear and complete introduction to Kalman Filter. Fortunately, I applied this algorithm on a robot that I have built its base from scratch. MCECS-Bot was a project started in Winter 2012 and it was assigned to me from my adviser, Dr. Marek Perkowski. This robot consists of the base with four Mecanum wheels, the waist based on four linear actuators, an arm, neck and head. The base is equipped with many sensors, which are bumper switches, encoders, sonars, LRF and Kinect. Additional devices can provide extra information as backup sensors, which are a tablet and a camera. The ultimate goal of this thesis is to have the MCECS-Bot as an open source system accessed by many future classes, capstone projects and graduate thesis students for education purposes. A well-known MRPT software system was used to present the results of the Extended Kalman Filter (EKF). These results are simply the robot positions estimated by EKF. They are demonstrated on the base floor of the FAB building of PSU. In parallel, simulated results to all different solutions derived in this thesis are presented using Matlab. A future students will have a ready platform and a good start to continue developing this system
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