191 research outputs found

    Learning dynamic motor skills for terrestrial locomotion

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    The use of Deep Reinforcement Learning (DRL) has received significantly increased attention from researchers within the robotics field following the success of AlphaGo, which demonstrated the superhuman capabilities of deep reinforcement algorithms in terms of solving complex tasks by beating professional GO players. Since then, an increasing number of researchers have investigated the potential of using DRL to solve complex high-dimensional robotic tasks, such as legged locomotion, arm manipulation, and grasping, which are difficult tasks to solve using conventional optimization approaches. Understanding and recreating various modes of terrestrial locomotion has been of long-standing interest to roboticists. A large variety of applications, such as rescue missions, disaster responses and science expeditions, strongly demand mobility and versatility in legged locomotion to enable task completion. In order to create useful physical robots, it is necessary to design controllers to synthesize the complex locomotion behaviours observed in humans and other animals. In the past, legged locomotion was mainly achieved via analytical engineering approaches. However, conventional analytical approaches have their limitations, as they require relatively large amounts of human effort and knowledge. Machine learning approaches, such as DRL, require less human effort compared to analytical approaches. The project conducted for this thesis explores the feasibility of using DRL to acquire control policies comparable to, or better than, those acquired through analytical approaches while requiring less human effort. In this doctoral thesis, we developed a Multi-Expert Learning Architecture (MELA) that uses DRL to learn multi-skill control policies capable of synthesizing a diverse set of dynamic locomotion behaviours for legged robots. We first proposed a novel DRL framework for the locomotion of humanoid robots. The proposed learning framework is capable of acquiring robust and dynamic motor skills for humanoids, including balancing, walking, standing-up fall recovery. We subsequently improved upon the learning framework and design a novel multi-expert learning architecture that is capable of fusing multiple motor skills together in a seamless fashion and ultimately deploy this framework on a real quadrupedal robot. The successful deployment of learned control policies on a real quadrupedal robot demonstrates the feasibility of using an Artificial Intelligence (AI) based approach for real robot motion control

    Advances in Robotics, Automation and Control

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    The book presents an excellent overview of the recent developments in the different areas of Robotics, Automation and Control. Through its 24 chapters, this book presents topics related to control and robot design; it also introduces new mathematical tools and techniques devoted to improve the system modeling and control. An important point is the use of rational agents and heuristic techniques to cope with the computational complexity required for controlling complex systems. Through this book, we also find navigation and vision algorithms, automatic handwritten comprehension and speech recognition systems that will be included in the next generation of productive systems developed by man

    ๊ฐ€์ƒํ˜„์‹ค์—์„œ ๋ชธ์˜ ์ž์„ธ์™€ ๊ณต๊ฐ„์ธ์ง€, ๊ณต๊ฐ„์ด๋™๋ฐฉ๋ฒ•, ์กด์žฌ๊ฐ, ์‚ฌ์ด๋ฒ„๋ฉ€๋ฏธ์˜ ์ƒํ˜ธ์ž‘์šฉ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ธ๋ฌธ๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ์ธ์ง€๊ณผํ•™์ „๊ณต, 2021. 2. ์ด๊ฒฝ๋ฏผ.๊ฐ€์ƒํ˜„์‹ค์€ ๋ชธ๊ณผ ๋งˆ์Œ์ด ๊ณต๊ฐ„์— ํ•จ๊ป˜ ์กด์žฌํ•œ๋‹ค๋Š” ์ผ์ƒ์  ๊ฒฝํ—˜์— ๋Œ€ํ•ด ์ƒˆ๋กœ์šด ๊ด€์ ์„ ์ œ์‹œํ•œ๋‹ค. ์ปดํ“จํ„ฐ๋กœ ๋งค๊ฐœ๋œ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜์—์„œ ๋งŽ์€ ๊ฒฝ์šฐ ์‚ฌ์šฉ์ž๋“ค์€ ๋ชธ์€ ๋ฐฐ์ œ๋˜๋ฉฐ ๋งˆ์Œ์˜ ์กด์žฌ๊ฐ€ ์ค‘์š”ํ•˜๋‹ค๊ณ  ๋Š๋ผ๊ฒŒ ๋œ๋‹ค. ์ด์™€ ๊ด€๋ จํ•˜์—ฌ ๊ฐ€์ƒํ˜„์‹ค์€ ์‚ฌ์šฉ์ž๋“ค์—๊ฒŒ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜์— ์žˆ์–ด ๋ฌผ๋ฆฌ์  ๋ชธ์˜ ์—ญํ• ๊ณผ ๋น„์ฒดํ™”๋œ ์ƒํ˜ธ์ž‘์šฉ์˜ ์ค‘์š”์„ฑ์— ๋Œ€ํ•ด ์—ฐ๊ตฌํ•  ์ˆ˜ ์žˆ๋Š” ๊ธฐํšŒ๋ฅผ ์ œ๊ณตํ•œ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ์— ์˜ํ•˜๋ฉด ์‹คํ–‰, ์ฃผ์˜์ง‘์ค‘, ๊ธฐ์–ต, ์ง€๊ฐ๊ณผ ๊ฐ™์€ ์ธ์ง€๊ธฐ๋Šฅ๋“ค์ด ๋ชธ์˜ ์ž์„ธ์— ๋”ฐ๋ผ ๋‹ค๋ฅด๊ฒŒ ์ž‘์šฉํ•œ๋‹ค๊ณ  ํ•œ๋‹ค. ํ•˜์ง€๋งŒ ์ด์™€ ๊ฐ™์€ ์ธ์ง€๊ธฐ๋Šฅ๋“ค๊ณผ ๋ชธ ์ž์„ธ์˜ ์ƒํ˜ธ์—ฐ๊ด€์„ฑ์€ ์—ฌ์ „ํžˆ ๋ช…ํ™•ํžˆ ๋ฐํ˜€์ง€๊ณ  ์žˆ์ง€ ์•Š๋‹ค. ํŠนํžˆ ๊ฐ€์ƒํ˜„์‹ค์—์„œ ๋ชธ์˜ ์ž์„ธ๊ฐ€ ์ง€๊ฐ๋ฐ˜์‘์— ๋Œ€ํ•œ ์ธ์ง€๊ณผ์ •์— ์–ด๋–ค ์ž‘์šฉ์„ ํ•˜๋Š”์ง€์— ๋Œ€ํ•œ ์ดํ•ด๋Š” ๋งค์šฐ ๋ถ€์กฑํ•œ ์ƒํ™ฉ์ด๋‹ค. ๊ฐ€์ƒํ˜„์‹ค ์—ฐ๊ตฌ์ž๋“ค์€ ์กด์žฌ๊ฐ์„ ๊ฐ€์ƒํ˜„์‹ค์˜ ํ•ต์‹ฌ ๊ฐœ๋…์œผ๋กœ ์ •์˜ํ•˜์˜€์œผ๋ฉฐ ํšจ์œจ์ ์ธ ๊ฐ€์ƒํ˜„์‹ค ์‹œ์Šคํ…œ ๊ตฌ์„ฑ๊ณผ ๋ฐ€์ ‘ํ•œ ๊ด€๊ณ„๊ฐ€ ์žˆ๋‹ค๊ณ  ํ•œ๋‹ค. ์กด์žฌ๊ฐ์€ ๊ฐ€์ƒ๊ณต๊ฐ„์— ์žˆ๋‹ค๊ณ  ๋Š๋ผ๋Š” ์˜์‹์ƒํƒœ๋ฅผ ๋งํ•œ๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ ๊ฐ€์ƒํ˜„์‹ค ์† ๊ฒฝํ—˜์„ ์‹ค์žฌ ์กด์žฌํ•œ๋‹ค๊ณ  ๋Š๋ผ๋Š” ์˜์‹์ƒํƒœ๋ฅผ ๋งํ•œ๋‹ค. ์ด๋Ÿฐ ์กด์žฌ๊ฐ์ด ๋†’์„ ์ˆ˜๋ก ํ˜„์‹ค์ฒ˜๋Ÿผ ์ธ์ง€ํ•˜๊ธฐ์— ์กด์žฌ๊ฐ์€ ๊ฐ€์ƒํ˜„์‹ค ๊ฒฝํ—˜์„ ์ธก์ •ํ•˜๋Š” ์ค‘์š”ํ•œ ์ง€ํ‘œ์ด๋‹ค. ๋”ฐ๋ผ์„œ ๊ฐ€์ƒ๊ณต๊ฐ„์— ์กด์žฌํ•˜๊ณ  ์žˆ๋‹ค๋Š” ์˜์‹์  ๊ฒฝํ—˜ ((๊ฑฐ๊ธฐ์— ์žˆ๋‹ค(being there)), ์ฆ‰ ์กด์žฌ๊ฐ์€ ๋งค๊ฐœ๋œ ๊ฐ€์ƒ๊ฒฝํ—˜๋“ค์˜ ์ธ์ง€ ์—ฐ๊ตฌ์— ์ค‘์š”ํ•œ ๊ฐœ๋…์ด๋‹ค. ๊ฐ€์ƒํ˜„์‹ค์€ ์‚ฌ์ด๋ฒ„๋ฉ€๋ฏธ๋ฅผ ์œ ๋ฐœํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ์ด ์ฆ์ƒ์€ ๊ฐ€์ƒํ˜„์‹ค์˜ ์‚ฌ์šฉ์„ฑ์„ ์ œ์•ฝํ•˜๋Š” ์ฃผ์š” ์š”์ธ์œผ๋กœ ํšจ๊ณผ์ ์ธ ๊ฐ€์ƒํ˜„์‹ค ๊ฒฝํ—˜์„ ์œ„ํ•ด ์‚ฌ์ด๋ฒ„๋ฉ€๋ฏธ์— ๋Œ€ํ•œ ๋‹ค์–‘ํ•œ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ์‚ฌ์ด๋ฒ„๋ฉ€๋ฏธ๋Š” ๊ฐ€์ƒํ˜„์‹ค ์‹œ์Šคํ…œ์„ ์‚ฌ์šฉํ• ๋•Œ ๋‚˜ํƒ€๋‚˜๋ฉฐ ์–ด์ง€๋Ÿฌ์›€, ๋ฐฉํ–ฅ์ƒ์‹ค, ๋‘ํ†ต, ๋•€ํ˜๋ฆผ, ๋ˆˆํ”ผ๋กœ๋„๋“ฑ์˜ ์ฆ์ƒ์„ ํฌํ•จํ•œ๋‹ค. ์ด๋Ÿฐ ์‚ฌ์ด๋ฒ„๋ฉ€๋ฏธ์—๋Š” ๊ฐœ์ธ์ฐจ, ์‚ฌ์šฉ๋œ ๊ธฐ์ˆ , ๊ณต๊ฐ„๋””์ž์ธ, ์ˆ˜ํ–‰๋œ ์—…๋ฌด๋“ฑ ๋งค์šฐ ๋‹ค์–‘ ์š”์ธ๋“ค์ด ๊ด€์—ฌํ•˜๊ณ  ์žˆ์–ด ๋ช…ํ™•ํ•œ ์›์ธ์„ ๊ทœ์ •ํ•  ์ˆ˜ ์—†๋‹ค. ์ด๋Ÿฐ ๋ฐฐ๊ฒฝ์œผ๋กœ ์ธํ•ด ์‚ฌ์ด๋ฒ„๋ฉ€๋ฏธ ์ €๊ฐ๊ณผ ๊ด€๋ จํ•œ ๋‹ค์–‘ํ•œ ์—ฐ๊ตฌ๋“ค์ด ํ•„์š”ํ•˜๋ฉฐ ์ด๋Š” ๊ฐ€์ƒํ˜„์‹ค ๋ฐœ์ „์— ์ค‘์š”ํ•œ ์˜๋ฏธ๋ฅผ ๊ฐ–๋Š”๋‹ค. ๊ณต๊ฐ„์ธ์ง€๋Š” 3์ฐจ์› ๊ณต๊ฐ„์—์„œ ์‹ ์ฒด ์›€์ง์ž„๊ณผ ๋Œ€์ƒ๊ณผ์˜ ์ƒํ˜ธ์ž‘์šฉ์— ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๋Š” ์ธ์ง€์‹œ์Šคํ…œ์ด๋‹ค. ๊ฐ€์ƒ๊ณต๊ฐ„์—์„œ ์‹ ์ฒด ์›€์ง์ž„์€ ๋„ค๋น„๊ฒŒ์ด์…˜, ์‚ฌ๋ฌผ์กฐ์ž‘, ๋‹ค๋ฅธ ์—์ด์ „ํŠธ๋“ค๊ณผ ์ƒํ˜ธ์ž‘์šฉ์— ๊ด€์—ฌํ•œ๋‹ค. ํŠนํžˆ ๊ฐ€์ƒ๊ณต๊ฐ„์—์„œ ๋„ค๋น„๊ฒŒ์ด์…˜์€ ์ž์ฃผ ์‚ฌ์šฉ๋˜๋Š” ์ค‘์š”ํ•œ ์ƒํ˜ธ์ž‘์šฉ ๋ฐฉ์‹์ด๋‹ค. ์ด์— ๊ฐ€์ƒ๊ณต๊ฐ„์„ ๋„ค๋น„๊ฒŒ์ด์…˜ ํ• ๋•Œ ์กด์žฌ๊ฐ์— ์˜ํ–ฅ์„ ์ฃผ์ง€ ์•Š๊ณ  ๋ฉ€๋ฏธ์ฆ์ƒ์„ ์œ ๋ฐœํ•˜์ง€ ์•Š๋Š” ํšจ๊ณผ์ ์ธ ๊ณต๊ฐ„์ด๋™ ๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ๋‹ค์–‘ํ•œ ์—ฐ๊ตฌ๋“ค์ด ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋‹ค. ์ด์ „ ์—ฐ๊ตฌ๋“ค์— ์˜ํ•˜๋ฉด ์‹œ์ ์ด ์กด์žฌ๊ฐ๊ณผ ์ฒดํ™”๊ฐ์— ์˜ํ–ฅ์„ ์ค€๋‹ค๊ณ  ํ•œ๋‹ค. ์ด๋Š” ์‹œ์ ์— ๋”ฐ๋ผ ์‚ฌ์šฉ์ž์˜ ํ–‰๋™๊ณผ ๋Œ€์ƒ๋“ค๊ณผ์˜ ์ƒํ˜ธ์ž‘์šฉ ๋ฐฉ์‹์— ๋‹ฌ๋ผ์ง€๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๋”ฐ๋ผ์„œ ๊ฐ€์ƒ๊ณต๊ฐ„์—์„œ ๊ฒฝํ—˜ ๋˜ํ•œ ์‹œ์ ์— ๋”ฐ๋ผ ๋‹ฌ๋ผ์ง„๋‹ค. ์ด๋Ÿฐ ๋ฐฐ๊ฒฝ์œผ๋กœ ๋ชธ์˜ ์ž์„ธ, ๊ณต๊ฐ„์ธ์ง€, ์ด๋™๋ฐฉ๋ฒ•, ์กด์žฌ๊ฐ, ์‚ฌ์ด๋ฒ„๋ฉ€๋ฏธ์˜ ์ƒํ˜ธ ์—ฐ๊ด€์„ฑ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์‹œ์ ์— ๋”ฐ๋ผ ๋ถ„๋ฅ˜ํ•ด์„œ ์—ฐ๊ตฌํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ๊ฐ€์ƒํ˜„์‹ค ์† ๊ณต๊ฐ„ ๋„ค๋น„๊ฒŒ์ด์…˜์— ๋Œ€ํ•œ ์ธ์ง€๊ณผ์ •์„ ๋ณด๋‹ค ๋‹ค๊ฐ์ ์œผ๋กœ ์ดํ•ด ํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค. ๊ทธ๋™์•ˆ ์กด์žฌ๊ฐ๊ณผ ์‚ฌ์ด๋ฒ„ ๋ฉ€๋ฏธ์— ๋‚ด์žฌ๋œ ๋งค์ปค๋‹ˆ์ฆ˜์„ ์ดํ•ดํ•˜๊ธฐ ์œ„ํ•ด ๋‹ค์–‘ํ•œ ์—ฐ๊ตฌ๋“ค์ด ์ง„ํ–‰๋˜์–ด ์™”๋‹ค. ํ•˜์ง€๋งŒ ๋ชธ์˜ ์ž์„ธ์— ๋”ฐ๋ฅธ ์ธ์ง€์ž‘์šฉ์ด ์กด์žฌ๊ฐ๊ณผ ์‚ฌ์ด๋ฒ„๋ฉ€๋ฏธ์— ์–ด๋–ค ์˜ํ–ฅ์„ ์ฃผ๋Š”์ง€์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ๊ฑฐ์˜ ์ด๋ฃจ์–ด์ง€์ง€ ์•Š์•˜๋‹ค. ์ด์— ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์—์„œ๋Š” 1์ธ์นญ๊ณผ 3์ธ์นญ ์‹œ์ ์œผ๋กœ ๋ถ„๋ฅ˜๋œ ๋ณ„๋„์˜ ์‹คํ—˜๊ณผ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์—ฌ ๊ฐ€์ƒํ˜„์‹ค์—์„œ ๋ชธ์˜ ์ž์„ธ์™€ ๊ณต๊ฐ„์ธ์ง€, ๊ณต๊ฐ„์ด๋™๋ฐฉ๋ฒ•, ์กด์žฌ๊ฐ, ์‚ฌ์ด๋ฒ„๋ฉ€๋ฏธ์˜ ์ƒํ˜ธ์—ฐ๊ด€์„ฑ์„ ๋ณด๋‹ค ์‹ฌ์ธต์ ์œผ๋กœ ์ดํ•ดํ•˜๊ณ ์ž ํ•œ๋‹ค. ์ œ3์žฅ์—์„œ๋Š” 3์ธ์นญ์‹œ์ ์˜ ์‹คํ—˜๊ณผ ๊ฒฐ๊ณผ์— ๋Œ€ํ•œ ๋‚ด์šฉ์„ ๊ธฐ์ˆ ํ–ˆ๋‹ค. 3์ธ์นญ์‹œ์  ์‹คํ—˜์—์„œ๋Š” ๊ฐ€์ƒ๊ณต๊ฐ„์—์„œ ๋ชธ์˜ ์ž์„ธ์™€ ์กด์žฌ๊ฐ์˜ ์ƒํ˜ธ์—ฐ๊ด€์„ฑ ์—ฐ๊ตฌ๋ฅผ ์œ„ํ•ด ์„ธ๊ฐ€์ง€ ๋ชธ์˜ ์ž์„ธ (์„œ์žˆ๋Š” ์ž์„ธ, ์•‰์€ ์ž์„ธ, ๋‹ค๋ฆฌ๋ฅผ ํŽด๊ณ  ์•‰์€ ์ž์„ธ)์™€ 2๊ฐ€์ง€ ํƒ€์ž…์˜ ๊ณต๊ฐ„์ด๋™ ์ž์œ ๋„ (๋ฌดํ•œ, ์œ ํ•œ)๋ฅผ ์ƒํ˜ธ ๋น„๊ตํ–ˆ๋‹ค. ์‹คํ—˜๊ฒฐ๊ณผ์— ์˜ํ•˜๋ฉด ๊ณต๊ฐ„์ด๋™ ์ž์œ ๋„๊ฐ€ ๋ฌดํ•œํ•œ ๊ฒฝ์šฐ ์„œ์žˆ๋Š” ์ž์„ธ์—์„œ ์กด์žฌ๊ฐ์ด ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ถ”๊ฐ€์ ์œผ๋กœ ๊ฐ€์ƒ๊ณต๊ฐ„์—์„œ ๋ชธ์˜ ์ž์„ธ์™€ ์กด์žฌ๊ฐ์€ ๊ณต๊ฐ„์ด๋™์ž์œ ๋„์™€ ๊ด€๋ จ์ด ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ ์—ฌ๋Ÿฌ ์ธ์ง€๊ธฐ๋Šฅ ์ค‘ ์ฃผ์˜์ง‘์ค‘์ด ๋ชธ์˜ ์ž์„ธ, ์กด์žฌ๊ฐ, ๊ณต๊ฐ„์ธ์ง€์˜ ํ†ตํ•ฉ์  ์ƒํ˜ธ์ž‘์šฉ์„ ์ด๋Œ์–ด ๋‚ธ ๊ฒƒ์œผ๋กœ ํŒŒ์•…๋˜์—ˆ๋‹ค. 3์ธ์นญ์‹œ์ ์˜ ๊ฒฐ๊ณผ๋“ค์„ ์ข…ํ•ฉํ•ด ๋ณด๋ฉด ๋ชธ ์ž์„ธ์˜ ์ธ์ง€์  ์˜ํ–ฅ์€ ๊ณต๊ฐ„์ด๋™์ž์œ ๋„์™€ ์ƒ๊ด€๊ด€๊ณ„๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ์ถ”์ธกํ•  ์ˆ˜ ์žˆ๋‹ค. ์ œ4์žฅ์—์„œ๋Š” 1์ธ์นญ์‹œ์ ์˜ ์‹คํ—˜๊ณผ ๊ฒฐ๊ณผ์— ๋Œ€ํ•œ ๋‚ด์šฉ์„ ๊ธฐ์ˆ ํ–ˆ๋‹ค. 1์ธ์นญ์‹œ์  ์‹คํ—˜์—์„œ๋Š” ๊ฐ€์ƒ๊ณต๊ฐ„์—์„œ ๋ชธ์˜ ์ž์„ธ, ๊ณต๊ฐ„์ด๋™๋ฐฉ๋ฒ•, ์กด์žฌ๊ฐ, ์‚ฌ์ด๋ฒ„๋ฉ€๋ฏธ์˜ ์ƒํ˜ธ์—ฐ๊ด€์„ฑ ์—ฐ๊ตฌ๋ฅผ ์œ„ํ•ด ๋‘ ์กฐ๊ฑด์˜ ๋ชธ์˜ ์ž์„ธ (์„œ์žˆ๋Š” ์ž์„ธ, ์•‰์•„ ์žˆ๋Š” ์ž์„ธ)์™€ ๋„ค๊ฐ€์ง€ ํƒ€์ž…์˜ ์ด๋™๋ฐฉ๋ฒ• (์Šคํ‹ฐ์–ด๋ง + ๋ชธ์„ ํ™œ์šฉํ•œ ํšŒ์ „, ์Šคํ‹ฐ์–ด๋ง + ๋„๊ตฌ๋ฅผ ํ™œ์šฉํ•œ ํšŒ์ „, ํ…”๋ ˆํฌํ…Œ์ด์…˜ + ๋ชธ์„ ์ด์šฉํ•œ ํšŒ์ „, ํ…”๋ ˆํฌํ…Œ์ด์…˜ + ๋„๊ตฌ๋ฅผ ํ™œ์šฉํ•œ ํšŒ์ „)์˜ ์ƒํ˜ธ ๋น„๊ต๊ฐ€ ์ด๋ฃจ์–ด ์กŒ๋‹ค. ์‹คํ—˜๊ฒฐ๊ณผ์— ์˜ํ•˜๋ฉด ์œ„์น˜์ด๋™๋ฐฉ์‹๊ณผ ํšŒ์ „๋ฐฉ์‹์— ๋”ฐ๋ฅธ ๊ณต๊ฐ„์ด๋™์ž์œ ๋„๋Š” ์„ฑ๊ณต์ ์ธ ๋„ค๋น„๊ฒŒ์ด์…˜๊ณผ ๊ด€๋ จ์ด ์žˆ์œผ๋ฉฐ ์กด์žฌ๊ฐ์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ถ”๊ฐ€์ ์œผ๋กœ ์—ฐ์†์ ์œผ๋กœ ์‹œ๊ฐ์ •๋ณด๊ฐ€ ์ž…๋ ฅ๋˜๋Š” ์Šคํ‹ฐ์–ด๋ง ๋ฐฉ๋ฒ•์€ ์ž๊ฐ€์šด๋™์„ ๋†’์—ฌ ๋น„์—ฐ์†์  ๋ฐฉ๋ฒ•์ธ ํ…”๋ ˆํฌํ…Œ์ด์…˜๋ณด๋‹ค ์‚ฌ์ด๋ฒ„๋ฉ€๋ฏธ๋ฅผ ๋” ์œ ๋ฐœํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. 1์ธ์นญ์‹œ์ ์˜ ๊ฒฐ๊ณผ๋“ค์„ ์ข…ํ•ฉํ•ด ๋ณด๋ฉด ๊ฐ€์ƒ๊ณต๊ฐ„์—์„œ ๋„ค๋น„๊ฒŒ์ด์…˜์„ ํ• ๋•Œ ์กด์žฌ๊ฐ๊ณผ ์‚ฌ์ด๋ฒ„๋ฉ€๋ฏธ๋Š” ๊ณต๊ฐ„์ด๋™๋ฐฉ๋ฒ•๊ณผ ๊ด€๋ จ์ด ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๊ฐ€์ •ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ œ3์žฅ์˜ 3์ธ์นญ ์‹œ์  ์‹คํ—˜๊ฒฐ๊ณผ์— ์˜ํ•˜๋ฉด ๋ชธ์˜ ์ž์„ธ์™€ ์กด์žฌ๊ฐ์€ ์ƒ๊ด€๊ด€๊ณ„๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ์ œ์‹œ๋˜์—ˆ๋‹ค. ๋ฐ˜๋ฉด ์ œ4์žฅ์˜ ์‹คํ—˜๊ฒฐ๊ณผ์— ์˜ํ•˜๋ฉด 1์ธ์นญ์‹œ์ ์œผ๋กœ ๊ฐ€์ƒ๊ณต๊ฐ„์„ ๋„ค๋น„๊ฒŒ์ด์…˜ ํ•  ๋•Œ๋Š” ๊ณต๊ฐ„์ด๋™๋ฐฉ๋ฒ•์ด ์กด์žฌ๊ฐ๊ณผ ์‚ฌ์ด๋ฒ„๋ฉ€๋ฏธ์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด ๋‘ ์‹คํ—˜์— ๋Œ€ํ•œ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ๊ฐ€์ƒํ˜„์‹ค์—์„œ ๋ชธ์˜ ์ž์„ธ์™€ ๊ณต๊ฐ„์ธ์ง€ (๋„ค๋น„๊ฒŒ์ด์…˜)์˜ ์ƒํ˜ธ์—ฐ๊ด€์„ฑ์— ๋Œ€ํ•œ ์ดํ•ด๋ฅผ ํ™•๋Œ€ํ•˜๊ณ  ์กด์žฌ๊ฐ ๋ฐ ์‚ฌ์ด๋ฒ„๋ฉ€๋ฏธ์™€ ๊ณต๊ฐ„์ด๋™๋ฐฉ๋ฒ•์˜ ๊ด€๋ จ์„ฑ์„ ๋ฐํž ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€ํ•œ๋‹ค.Immersive virtual environments (VEs) can disrupt the everyday connection between where our senses tell us we are and where we are actually located. In computer-mediated communication, the user often comes to feel that their body has become irrelevant and that it is only the presence of their mind that matters. However, virtual worlds offer users an opportunity to become aware of and explore both the role of the physical body in communication, and the implications of disembodied interactions. Previous research has suggested that cognitive functions such as execution, attention, memory, and perception differ when body position changes. However, the influence of body position on these cognitive functions is still not fully understood. In particular, little is known about how physical self-positioning may affect the cognitive process of perceptual responses in a VE. Some researchers have identified presence as a guide to what constitutes an effective virtual reality (VR) system and as the defining feature of VR. Presence is a state of consciousness related to the sense of being within a VE; in particular, it is a โ€˜psychological state in which the virtuality of the experience is unnoticedโ€™. Higher levels of presence are considered to be an indicator of a more successful media experience, thus the psychological experience of โ€˜being thereโ€™ is an important construct to consider when investigating the association between mediated experiences on cognition. VR is known to induce cybersickness, which limits its application and highlights the need for scientific strategies to optimize virtual experiences. Cybersickness refers to the sickness associated with the use of VR systems, which has a range of symptoms including nausea, disorientation, headaches, sweating and eye strain. This is a complicated problem because the experience of cybersickness varies greatly between individuals, the technology being used, the design of the environment, and the task being performed. Thus, avoiding cybersickness represents a major challenge for VR development. Spatial cognition is an invariable precursor to action because it allows the formation of the necessary mental representations that code the positions of and relationships among objects. Thus, a number of bodily actions are represented mentally within a depicted VR space, including those functionally related to navigation, the manipulation of objects, and/or interaction with other agents. Of these actions, navigation is one of the most important and frequently used interaction tasks in VR environments. Therefore, identifying an efficient locomotion technique that does not alter presence nor cause motion sickness has become the focus of numerous studies. Though the details of the results have varied, past research has revealed that viewpoint can affect the sense of presence and the sense of embodiment. VR experience differs depending on the viewpoint of a user because this vantage point affects the actions of the user and their engagement with objects. Therefore, it is necessary to investigate the association between body position, spatial cognition, locomotion method, presence, and cybersickness based on viewpoint, which may clarify the understanding of cognitive processes in VE navigation. To date, numerous detailed studies have been conducted to explore the mechanisms underlying presence and cybersickness in VR. However, few have investigated the cognitive effects of body position on presence and cybersickness. With this in mind, two separate experiments were conducted in the present study on viewpoint within VR (i.e., third-person and first-person perspectives) to further the understanding of the effects of body position in relation to spatial cognition, locomotion method, presence, and cybersickness in VEs. In Chapter 3 (Experiment 1: third-person perspective), three body positions (standing, sitting, and half-sitting) were compared in two types of VR game with a different degree of freedom in navigation (DFN; finite and infinite) to explore the association between body position and the sense of presence in VEs. The results of the analysis revealed that standing has the most significant effect on presence for the three body positions that were investigated. In addition, the outcomes of this study indicated that the cognitive effect of body position on presence is associated with the DFN in a VE. Specifically, cognitive activity related to attention orchestrates the cognitive processes associated with body position, presence, and spatial cognition, consequently leading to an integrated sense of presence in VR. It can thus be speculated that the cognitive effects of body position on presence are correlated with the DFN in a VE. In Chapter 4 (Experiment 2: first-person perspective), two body positions (standing and sitting) and four types of locomotion method (steering + embodied control [EC], steering + instrumental control [IC], teleportation + EC, and teleportation + IC) were compared to examine the relationship between body position, locomotion method, presence, and cybersickness when navigating a VE. The results of Experiment 2 suggested that the DFN for translation and rotation is related to successful navigation and affects the sense of presence when navigating a VE. In addition, steering locomotion (continuous motion) increases self-motion when navigating a VE, which results in stronger cybersickness than teleportation (non-continuous motion). Overall, it can be postulated that presence and cybersickness are associated with the method of locomotion when navigating a VE. In this dissertation, the overall results of Experiment 1 suggest that the cognitive influence of presence is body-dependent in the sense that mental and brain processes rely on or are affected by the physical body. On the other hand, the outcomes of Experiment 2 illustrate the significant effects of locomotion method on the sense of presence and cybersickness during VE navigation. Taken together, the results of this study provide new insights into the cognitive effects of body position on spatial cognition (i.e., navigation) in VR and highlight the important implications of locomotion method on presence and cybersickness in VE navigation.Chapter 1. Introduction 1 1.1. An Introductory Overview of the Conducted Research 1 1.1.1. Presence and Body Position 1 1.1.2. Navigation, Cybersickness, and Locomotion Method 3 1.2. Research Objectives 6 1.3. Research Experimental Approach 7 Chapter 2. Theoretical Background 9 2.1. Presence 9 2.1.1. Presence and Virtual Reality 9 2.1.2. Presence and Spatiality 10 2.1.3. Presence and Action 12 2.1.4. Presence and Attention 14 2.2. Body Position 16 2.2.1. Body Position and Cognitive Effects 16 2.2.2. Body Position and Postural Control 18 2.2.3. Body Position and Postural Stability 19 2.3. Spatial Cognition: Degree of Freedom in Navigation 20 2.3.1. Degree of Freedom in Navigation and Decision-Making 20 2.4. Cybersickness 22 2.4.1. Cybersickness and Virtual Reality 22 2.4.2. Sensory Conflict Theory 22 2.4.3. Postural Instability Theory 23 2.5. Self-Motion 25 2.5.1. Vection and Virtual Reality 25 2.5.2. Self-Motion and Navigation in a VE 27 2.6. Navigation in Virtual Environments 29 2.6.1. Translation and Rotation in Navigation 29 2.6.2. Spatial Orientation and Embodiment 32 2.6.3. Locomotion Methods 37 2.6.4. Steering and Teleportation 38 Chapter 3. Experiment 1: Third-Person Perspective 40 3.1. Quantification of the Degree of Freedom in Navigation 40 3.2. Experiment 3.2.1. Experimental Design and Participants 41 3.2.2. Stimulus Materials 42 3.2.2.1. First- and Third-person Perspectives in Gameplay 43 3.2.3. Experimental Setup and Process 44 3.2.4. Measurements 45 3.3. Results 45 3.3.1. Presence: two-way ANOVA 45 3.3.2. Presence: one-way ANOVA 46 3.3.2.1. Finite Navigation Freedom 46 3.3.2.2. Infinite Navigation Freedom 47 3.3.3. Summary of the Results 48 3.4. Discussion 49 3.4.1. Presence and Body Position 49 3.4.2. Degree of Freedom in Navigation and Decision-Making 50 3.4.3. Gender Difference and Gameplay 51 3.5. Limitations 52 Chapter 4. Experiment 2: First-Person Perspective 53 4.1. Experiment 53 4.1.1. Experimental Design and Participants 53 4.1.2. Stimulus Materials 54 4.1.3. Experimental Setup and Process 55 4.1.4. Measurements 56 4.2. Results 57 4.2.1. Presence: two-way ANOVA 58 4.2.2. Cybersickness: two-way ANOVA 58 4.2.3. Presence: one-way ANOVA 60 4.2.3.1. Standing Position 60 4.2.3.2. Sitting Position 60 4.2.4. Cybersickness: one-way ANOVA 62 4.2.4.1. Standing Position 62 4.2.4.2. Sitting Position 62 4.2.5. Summary of the Results 63 4.3. Discussion 65 4.3.1. Presence 4.3.1.1. Presence and Locomotion Method 66 4.3.1.2. Presence and Body Position 68 4.3.2. Cybersickness 4.3.2.1. Cybersickness and Locomotion Method 69 4.3.2.2. Cybersickness and Body Position 70 4.4. Limitations 71 Chapter 5. Conclusion 72 5.1. Summary of Findings 72 5.2. Future Research Direction 73 References 75 Appendix A 107 Appendix B 110 ๊ตญ๋ฌธ์ดˆ๋ก 111Docto

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