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    ๊ฒฝ์ฒฉ๋ฌธ์„ ์—ฌ๋Š” ๋น„ํ–‰ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ์— ๋Œ€ํ•œ ๋ชจ๋ธ ์˜ˆ์ธก ์ œ์–ด

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€, 2020. 8. ๊น€ํ˜„์ง„.From aerial pick-and-place to aerial transportation, aerial manipulation has been extensively studied in recent years thanks to its mobility and dexterity, each of which is a merit of an aerial vehicle and a robotic arm. However, to fully harness the concept of aerial manipulation, more complex tasks including interaction with movable structures should also be considered. Among various types of movable structures, this paper presents a multirotor-based aerial manipulator opening a daily-life moving structure, a hinged door. Two additional issues that would arise in interaction with a movable structure are addressed: 1) a constrained motion of the structure, and 2) collision avoidance with a moving structure. To handle these issues, we formulate a model predictive control (MPC) problem with a system dynamics constraint and state constraints for collision avoidance. A coupled system dynamics of a multirotor-based aerial manipulator and a hinged door is derived and later simplified for faster computation in MPC. State constraints for collision avoidance with itself, a door, and a doorframe are generated. By implementing a constrained version of differential dynamic programming (DDP), we can generate reference trajectories through MPC in real-time. The proposed method is validated through simulation results and experiments with a real-like hinged door in which a disturbance observer (DOB) based robust motion controller is employed.๋น„ํ–‰ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ๋Š” 3์ฐจ์› ๊ณต๊ฐ„ ์†์— ๋น ๋ฅด๊ฒŒ ์œ„์น˜ํ•  ์ˆ˜ ์žˆ๋Š” ๋น„ํ–‰์ฒด์˜ ์žฅ์ ๊ณผ ์™ธ๋ถ€์™€์˜ ์ƒํ˜ธ์ž‘์šฉ์ด ๊ฐ€๋Šฅํ•œ ๋กœ๋ด‡ํŒ”์˜ ์žฅ์ ์ด ๊ฒฐํ•ฉ๋œ ๋น„ํ–‰์ฒด๋กœ, ์ตœ๊ทผ ๋ฌผ๊ฑด ์ง‘๊ณ  ์˜ฎ๊ธฐ๊ธฐ๋ถ€ํ„ฐ ๋ฌผํ’ˆ ์šด์†ก๊นŒ์ง€ ๋‹ค์–‘ํ•œ ์ž„๋ฌด๋ฅผ ์ˆ˜ํ–‰ํ•˜๊ธฐ ์œ„ํ•ด ํ™œ๋ฐœํ•˜๊ฒŒ ์—ฐ๊ตฌ๋˜์–ด ์™”๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ์˜จ์ „ํžˆ ๋น„ํ–‰ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ์˜ ๊ฐ€๋Šฅ์„ฑ์„ ํ™œ์šฉํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์›€์ง์ผ ์ˆ˜ ์žˆ๋Š” ์™ธ๋ถ€ ๊ตฌ์กฐ์™€์˜ ์ƒํ˜ธ์ž‘์šฉ๊ณผ ๊ฐ™์ด ๋”์šฑ ๋ณต์žกํ•œ ์ž„๋ฌด ๋˜ํ•œ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ์–ด์•ผ ํ•  ๊ฒƒ์ด๋‹ค. ์—ฌ๋Ÿฌ ์ข…๋ฅ˜์˜ ์›€์ง์ผ ์ˆ˜ ์žˆ๋Š” ๊ตฌ์กฐ๋ฌผ ์ค‘ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ผ์ƒ ์†์—์„œ ์‰ฝ๊ฒŒ ๋งˆ์ฃผ์น  ์ˆ˜ ์žˆ๋Š” ๊ฒฝ์ฒฉ๋ฌธ์„ ์—ฌ๋Š” ๋ฉ€ํ‹ฐ๋กœํ„ฐ ๊ธฐ๋ฐ˜์˜ ๋น„ํ–‰ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ์— ๋Œ€ํ•ด ์ œ์‹œํ•œ๋‹ค. ์ •์ ์ธ ๊ตฌ์กฐ๋ฌผ๊ณผ์˜ ์ƒํ˜ธ์ž‘์šฉ๊ณผ๋Š” ๋‹ฌ๋ฆฌ ๋™์ ์ธ ๊ตฌ์กฐ๋ฌผ๊ณผ์˜ ์ƒํ˜ธ์ž‘์šฉ์— ์žˆ์–ด์„œ ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋Š” 1) ๊ตฌ์กฐ๋ฌผ์˜ ์ œ์•ฝ๋œ ์›€์ง์ž„, ๊ทธ๋ฆฌ๊ณ  2) ์›€์ง์ด๋Š” ๊ตฌ์กฐ๋ฌผ๊ณผ์˜ ์ถฉ๋Œ ํšŒํ”ผ์˜ 2๊ฐ€์ง€ ์ถ”๊ฐ€์ ์ธ ๋ฌธ์ œ์— ๋Œ€ํ•ด ๋‹ค๋ฃจ์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ๋‹ค๋ฃจ๊ธฐ ์œ„ํ•ด ๋ชจ๋ธ ์˜ˆ์ธก ์ œ์–ด (MPC)๋ฅผ ์ ์šฉํ•˜์˜€์œผ๋ฉฐ, ์‹œ์Šคํ…œ ๋™์—ญํ•™์— ๋Œ€ํ•œ ์ œ์•ฝ์กฐ๊ฑด ๋ฐ ์ถฉ๋Œ ํšŒํ”ผ์— ๋Œ€ํ•œ ์ œ์•ฝ ์กฐ๊ฑด์„ ๋ถ€์—ฌํ•˜์˜€๋‹ค. ๋ฉ€ํ‹ฐ๋กœํ„ฐ ๊ธฐ๋ฐ˜์˜ ๋น„ํ–‰ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ์™€ ๊ฒฝ์ฒฉ๋ฌธ์˜ ๊ฒฐํ•ฉ ์‹œ์Šคํ…œ์— ๋Œ€ํ•œ ๋™์—ญํ•™์„ ์œ ๋„ํ•˜์˜€์œผ๋ฉฐ, ์ดํ›„ ๋ชจ๋ธ ์˜ˆ์ธก ์ œ์–ด์—์„œ์˜ ๋น ๋ฅธ ๊ณ„์‚ฐ ์†๋„๋ฅผ ์œ„ํ•ด ๋‹จ์ˆœํ™”๋˜์—ˆ๋‹ค. ์ถฉ๋Œ ํšŒํ”ผ์— ๋Œ€ํ•œ ์ œ์•ฝ ์กฐ๊ฑด์€ ๋ชจ๋‘ ์ƒํƒœ ๋ณ€์ˆ˜๋กœ ํ‘œํ˜„๋˜์—ˆ์œผ๋ฉฐ, ๋น„ํ–‰ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ์˜ ๋ฉ€ํ‹ฐ๋กœํ„ฐ ํ”„๋ ˆ์ž„๊ณผ ๋กœ๋ด‡ํŒ” ์‚ฌ์ด์˜ ์ถฉ๋Œ (์ž๊ธฐ ์ถฉ๋Œ), ๋ฌธ๊ณผ์˜ ์ถฉ๋Œ, ๊ทธ๋ฆฌ๊ณ  ๋ฌธํ‹€๊ณผ์˜ ์ถฉ๋Œ์„ ๊ณ ๋ คํ•˜์˜€๋‹ค. ๋ฏธ๋ถ„ ๊ธฐ๋ฐ˜์˜ ๋™์  ํ”„๋กœ๊ทธ๋ž˜๋ฐ ๊ธฐ๋ฒ• (differential dynamic programming)์— ์ œ์•ฝ์กฐ๊ฑด์ด ๊ณ ๋ ค๋œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ตฌํ˜„ํ•จ์œผ๋กœ์จ ๋ชจ๋ธ ๊ธฐ๋ฐ˜ ์˜ˆ์ธก ์ œ์–ด๋ฅผ ํ†ตํ•ด ์‹ค์‹œ๊ฐ„์œผ๋กœ ๊ฒฝ๋กœ๋ฅผ ๊ณ„ํšํ•  ์ˆ˜ ์žˆ๋‹ค. ์ œ์•ˆ๋œ ๋ฐฉ๋ฒ•์€ ์‹œ๋ฎฌ๋ ˆ์ด์…˜๊ณผ ์‹ค์ œ ํฌ๊ธฐ์˜ ๋ฌธ์„ ํ™œ์šฉํ•œ ์‹คํ—˜์„ ํ†ตํ•ด ๊ฒ€์ฆ๋˜์—ˆ์œผ๋ฉฐ, ์™ธ๋ž€ ๊ด€์ธก๊ธฐ ๊ธฐ๋ฐ˜์˜ ๊ฐ•๊ฑด ์ œ์–ด ๊ธฐ๋ฒ•์ด ์‹คํ—˜์— ํ™œ์šฉ๋˜์—ˆ๋‹ค.1 Introduction 1 1.1 Literature review 2 1.2 Thesis contribution 3 1.3 Thesis outline 3 2 Equations of motion 4 2.1 Assumption 4 2.2 Kinematics 5 2.3 Dynamics 6 2.4 Simpli ed dynamics 8 3 Model predictive control 10 3.1 Problem formulation 10 3.1.1 Objective function 11 3.1.2 Hard constraints 11 3.2 Collision avoidance constraints 11 3.2.1 Self collision avoidance 13 3.2.2 Door collision avoidance 13 3.2.3 Doorframe collision avoidance 14 3.3 Optimal control solver 14 3.3.1 Differential dynamic programming 14 3.3.2 DDP with augmented Lagrangian method 15 4 Experimental setup 17 4.1 Door state estimation 17 4.2 Multirotor robust controller 18 4.3 Hardware setup 19 5 Results 20 5.1 Simulation results 20 5.2 Experimental results 25 6 Conclusion 29Maste

    NASA Tech Briefs, December 1989

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    Topics include: Electronic Components and Circuits. Electronic Systems, Physical Sciences, Materials, Computer Programs, Mechanics, Machinery, Fabrication Technology, Mathematics and Information Sciences, and Life Sciences
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