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    ๊ธฐ๊ตฌํ•™์  ๋ฐ ๋™์  ์ œํ•œ์กฐ๊ฑด๋“ค์„ ๊ณ ๋ คํ•œ ๋ชจ๋ฐ”์ผ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ์˜ ์ž‘์—… ์ค‘์‹ฌ ์ „์‹  ๋™์ž‘ ์ƒ์„ฑ ์ „๋žต

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์œตํ•ฉ๊ณผํ•™๊ธฐ์ˆ ๋Œ€ํ•™์› ์œตํ•ฉ๊ณผํ•™๋ถ€(์ง€๋Šฅํ˜•์œตํ•ฉ์‹œ์Šคํ…œ์ „๊ณต), 2023. 2. ๋ฐ•์žฌํฅ.๋ชจ๋ฐ”์ผ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ๋Š” ๋ชจ๋ฐ”์ผ ๋กœ๋ด‡์— ์žฅ์ฐฉ๋œ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ์ž…๋‹ˆ๋‹ค. ๋ชจ๋ฐ”์ผ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ๋Š” ๊ณ ์ •ํ˜• ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ์— ๋น„ํ•ด ๋ชจ๋ฐ”์ผ ๋กœ๋ด‡์˜ ์ด๋™์„ฑ์„ ์ œ๊ณต๋ฐ›๊ธฐ ๋•Œ๋ฌธ์— ๋‹ค์–‘ํ•˜๊ณ  ๋ณต์žกํ•œ ์ž‘์—…์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋‘ ๊ฐœ์˜ ์„œ๋กœ ๋‹ค๋ฅธ ์‹œ์Šคํ…œ์„ ๊ฒฐํ•ฉํ•จ์œผ๋กœ์จ ๋ชจ๋ฐ”์ผ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ์˜ ์ „์‹ ์„ ๊ณ„ํšํ•˜๊ณ  ์ œ์–ดํ•  ๋•Œ ์—ฌ๋Ÿฌ ํŠน์ง•์„ ๊ณ ๋ คํ•ด์•ผ ํ•ฉ๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ํŠน์ง•๋“ค์€ ์—ฌ์ž์œ ๋„, ๋‘ ์‹œ์Šคํ…œ์˜ ๊ด€์„ฑ ์ฐจ์ด ๋ฐ ๋ชจ๋ฐ”์ผ ๋กœ๋ด‡์˜ ๋น„ํ™€๋กœ๋…ธ๋ฏน ์ œํ•œ ์กฐ๊ฑด ๋“ฑ์ด ์žˆ์Šต๋‹ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์˜ ๋ชฉ์ ์€ ๊ธฐ๊ตฌํ•™์  ๋ฐ ๋™์  ์ œํ•œ์กฐ๊ฑด๋“ค์„ ๊ณ ๋ คํ•˜์—ฌ ๋ชจ๋ฐ”์ผ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ์˜ ์ „์‹  ๋™์ž‘ ์ƒ์„ฑ ์ „๋žต์„ ์ œ์•ˆํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๋จผ์ €, ๋ชจ๋ฐ”์ผ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ๊ฐ€ ์ดˆ๊ธฐ ์œ„์น˜์—์„œ ๋ฌธ์„ ํ†ต๊ณผํ•˜์—ฌ ๋ชฉํ‘œ ์œ„์น˜์— ๋„๋‹ฌํ•˜๊ธฐ ์œ„ํ•œ ์ „์‹  ๊ฒฝ๋กœ๋ฅผ ๊ณ„์‚ฐํ•˜๋Š” ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. ์ด ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ๋กœ๋ด‡๊ณผ ๋ฌธ์— ์˜ํ•ด ์ƒ๊ธฐ๋Š” ๊ธฐ๊ตฌํ•™์  ์ œํ•œ์กฐ๊ฑด์„ ๊ณ ๋ คํ•ฉ๋‹ˆ๋‹ค. ์ œ์•ˆํ•˜๋Š” ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ๋‘ ๋‹จ๊ณ„๋ฅผ ๊ฑฐ์ณ ์ „์‹ ์˜ ๊ฒฝ๋กœ๋ฅผ ์–ป์Šต๋‹ˆ๋‹ค. ์ฒซ ๋ฒˆ์งธ ๋‹จ๊ณ„์—์„œ๋Š” ๊ทธ๋ž˜ํ”„ ํƒ์ƒ‰ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ด์šฉํ•˜์—ฌ ๋ชจ๋ฐ”์ผ ๋กœ๋ด‡์˜ ์ž์„ธ ๊ฒฝ๋กœ์™€ ๋ฌธ์˜ ๊ฐ๋„ ๊ฒฝ๋กœ๋ฅผ ๊ณ„์‚ฐํ•ฉ๋‹ˆ๋‹ค. ํŠนํžˆ, ๊ทธ๋ž˜ํ”„ ํƒ์ƒ‰์—์„œ area indicator๋ผ๋Š” ์ •์ˆ˜ ๋ณ€์ˆ˜๋ฅผ ์ƒํƒœ์˜ ๊ตฌ์„ฑ ์š”์†Œ๋กœ์„œ ์ •์˜ํ•˜๋Š”๋ฐ, ์ด๋Š” ๋ฌธ์— ๋Œ€ํ•œ ๋ชจ๋ฐ”์ผ ๋กœ๋ด‡์˜ ์ƒ๋Œ€์  ์œ„์น˜๋ฅผ ๋‚˜ํƒ€๋ƒ…๋‹ˆ๋‹ค. ๋‘ ๋ฒˆ์งธ ๋‹จ๊ณ„์—์„œ๋Š” ๋ชจ๋ฐ”์ผ ๋กœ๋ด‡์˜ ๊ฒฝ๋กœ์™€ ๋ฌธ์˜ ๊ฐ๋„๋ฅผ ํ†ตํ•ด ๋ฌธ์˜ ์†์žก์ด ์œ„์น˜๋ฅผ ๊ณ„์‚ฐํ•˜๊ณ  ์—ญ๊ธฐ๊ตฌํ•™์„ ํ™œ์šฉํ•˜์—ฌ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ์˜ ๊ด€์ ˆ ์œ„์น˜๋ฅผ ๊ณ„์‚ฐํ•ฉ๋‹ˆ๋‹ค. ์ œ์•ˆ๋œ ํ”„๋ ˆ์ž„์›Œํฌ์˜ ํšจ์œจ์„ฑ์€ ๋น„ํ™€๋กœ๋…ธ๋ฏน ๋ชจ๋ฐ”์ผ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ๋ฅผ ์‚ฌ์šฉํ•œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฐ ์‹ค์ œ ์‹คํ—˜์„ ํ†ตํ•ด ๊ฒ€์ฆ๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ๋‘˜ ์งธ, ์ตœ์ ํ™” ๋ฐฉ๋ฒ•์„ ๊ธฐ๋ฐ˜์œผ๋กœํ•œ ์ „์‹  ์ œ์–ด๊ธฐ๋ฅผ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. ์ด ๋ฐฉ๋ฒ•์€ ๋“ฑ์‹ ๋ฐ ๋ถ€๋“ฑ์‹ ์ œํ•œ์กฐ๊ฑด ๋ชจ๋‘์— ๋Œ€ํ•ด ๊ฐ€์ค‘ ํ–‰๋ ฌ์„ ๋ฐ˜์˜ํ•œ ๊ณ„์ธต์  ์ตœ์ ํ™” ๋ฌธ์ œ์˜ ํ•ด๋ฅผ ๊ณ„์‚ฐํ•ฉ๋‹ˆ๋‹ค. ์ด ๋ฐฉ๋ฒ•์€ ๋ชจ๋ฐ”์ผ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ ๋˜๋Š” ํœด๋จธ๋…ธ์ด๋“œ์™€ ๊ฐ™์ด ์ž์œ ๋„๊ฐ€ ๋งŽ์€ ๋กœ๋ด‡์˜ ์—ฌ์ž์œ ๋„๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๊ฐœ๋ฐœ๋˜์–ด ์ž‘์—… ์šฐ์„  ์ˆœ์œ„์— ๋”ฐ๋ผ ๊ฐ€์ค‘์น˜๊ฐ€ ๋‹ค๋ฅธ ๊ด€์ ˆ ๋™์ž‘์œผ๋กœ ์—ฌ๋Ÿฌ ์ž‘์—…์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ œ์•ˆ๋œ ๋ฐฉ๋ฒ•์€ ๊ฐ€์ค‘ ํ–‰๋ ฌ์„ ์ตœ์ ํ™” ๋ฌธ์ œ์˜ 1์ฐจ ์ตœ์  ์กฐ๊ฑด์„ ๋งŒ์กฑํ•˜๋„๋ก ํ•˜๋ฉฐ, Active-set ๋ฐฉ๋ฒ•์„ ํ™œ์šฉํ•˜์—ฌ ๋“ฑ์‹ ๋ฐ ๋ถ€๋“ฑ์‹ ์ž‘์—…์„ ์ฒ˜๋ฆฌํ•ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ, ๋Œ€์นญ์ ์ธ ์˜๊ณต๊ฐ„ ์‚ฌ์˜ ํ–‰๋ ฌ์„ ์‚ฌ์šฉํ•˜์—ฌ ๊ณ„์‚ฐ์ƒ ํšจ์œจ์ ์ž…๋‹ˆ๋‹ค. ๊ฒฐ๊ณผ์ ์œผ๋กœ, ์ œ์•ˆ๋œ ์ œ์–ด๊ธฐ๋ฅผ ํ™œ์šฉํ•˜๋Š” ๋กœ๋ด‡์€ ์šฐ์„  ์ˆœ์œ„์— ๋”ฐ๋ผ ๊ฐœ๋ณ„์ ์ธ ๊ด€์ ˆ ๊ฐ€์ค‘์น˜๋ฅผ ๋ฐ˜์˜ํ•˜์—ฌ ์ „์‹  ์›€์ง์ž„์„ ํšจ๊ณผ์ ์œผ๋กœ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ์ œ์•ˆ๋œ ์ œ์–ด๊ธฐ์˜ ํšจ์šฉ์„ฑ์€ ๋ชจ๋ฐ”์ผ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ์™€ ํœด๋จธ๋…ธ์ด๋“œ๋ฅผ ์ด์šฉํ•œ ์‹คํ—˜์„ ํ†ตํ•ด ๊ฒ€์ฆํ•˜์˜€์Šต๋‹ˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๋ชจ๋ฐ”์ผ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ์˜ ๋™์  ์ œํ•œ์กฐ๊ฑด๋“ค ์ค‘ ํ•˜๋‚˜๋กœ์„œ ์ž๊ฐ€ ์ถฉ๋Œ ํšŒํ”ผ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. ์ œ์•ˆ๋œ ๋ฐฉ๋ฒ•์€ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ์™€ ๋ชจ๋ฐ”์ผ ๋กœ๋ด‡ ๊ฐ„์˜ ์ž๊ฐ€ ์ถฉ๋Œ์— ์ค‘์ ์„ ๋‘ก๋‹ˆ๋‹ค. ๋ชจ๋ฐ”์ผ ๋กœ๋ด‡์˜ ๋ฒ„ํผ ์˜์—ญ์„ ๋‘˜๋Ÿฌ์‹ธ๋Š” 3์ฐจ์› ๊ณก๋ฉด์ธ distance buffer border์˜ ๊ฐœ๋…์„ ์ •์˜ํ•ฉ๋‹ˆ๋‹ค. ๋ฒ„ํผ ์˜์—ญ์˜ ๋‘๊ป˜๋Š” ๋ฒ„ํผ ๊ฑฐ๋ฆฌ์ž…๋‹ˆ๋‹ค. ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ์™€ ๋ชจ๋ฐ”์ผ ๋กœ๋ด‡ ์‚ฌ์ด์˜ ๊ฑฐ๋ฆฌ๊ฐ€ ๋ฒ„ํผ ๊ฑฐ๋ฆฌ๋ณด๋‹ค ์ž‘์€ ๊ฒฝ์šฐ, ์ฆ‰ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ๊ฐ€ ๋ชจ๋ฐ”์ผ ๋กœ๋ด‡์˜ ๋ฒ„ํผ ์˜์—ญ ๋‚ด๋ถ€์— ์žˆ๋Š” ๊ฒฝ์šฐ ์ œ์•ˆ๋œ ์ „๋žต์€ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ๋ฅผ ๋ฒ„ํผ ์˜์—ญ ๋ฐ–์œผ๋กœ ๋‚ด๋ณด๋‚ด๊ธฐ ์œ„ํ•ด ๋ชจ๋ฐ”์ผ ๋กœ๋ด‡์˜ ์›€์ง์ž„์„ ์ƒ์„ฑํ•ฉ๋‹ˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ๋Š” ๋ฏธ๋ฆฌ ์ •์˜๋œ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ์˜ ์›€์ง์ž„์„ ์ˆ˜์ •ํ•˜์ง€ ์•Š๊ณ ๋„ ๋ชจ๋ฐ”์ผ ๋กœ๋ด‡๊ณผ์˜ ์ž๊ฐ€ ์ถฉ๋Œ์„ ํ”ผํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋ชจ๋ฐ”์ผ ๋กœ๋ด‡์˜ ์›€์ง์ž„์€ ๊ฐ€์ƒ์˜ ํž˜์„ ๊ฐ€ํ•จ์œผ๋กœ์จ ์ƒ์„ฑ๋ฉ๋‹ˆ๋‹ค. ํŠนํžˆ, ํž˜์˜ ๋ฐฉํ–ฅ์€ ์ฐจ๋™ ๊ตฌ๋™ ์ด๋™ ๋กœ๋ด‡์˜ ๋น„ํ™€๋กœ๋…ธ๋ฏน ์ œ์•ฝ ๋ฐ ์กฐ์ž‘๊ธฐ์˜ ๋„๋‹ฌ ๊ฐ€๋Šฅ์„ฑ์„ ๊ณ ๋ คํ•˜์—ฌ ๊ฒฐ์ •๋ฉ๋‹ˆ๋‹ค. ์ œ์•ˆ๋œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ 7์ž์œ ๋„ ๋กœ๋ด‡ํŒ”์„ ๊ฐ€์ง„ ์ฐจ๋™ ๊ตฌ๋™ ๋ชจ๋ฐ”์ผ ๋กœ๋ด‡์— ์ ์šฉํ•˜์—ฌ ๋‹ค์–‘ํ•œ ์‹คํ—˜ ์‹œ๋‚˜๋ฆฌ์˜ค์—์„œ ์ž…์ฆ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.A mobile manipulator is a manipulator mounted on a mobile robot. Compared to a fixed-base manipulator, the mobile manipulator can perform various and complex tasks because the mobility is offered by the mobile robot. However, combining two different systems causes several features to be considered when generating the whole-body motion of the mobile manipulator. The features include redundancy, inertia difference, and non-holonomic constraint. The purpose of this thesis is to propose the whole-body motion generation strategy of the mobile manipulator for considering kinematic and dynamic constraints. First, a planning framework is proposed that computes a path for the whole-body configuration of the mobile manipulator to navigate from the initial position, traverse through the door, and arrive at the target position. The framework handles the kinematic constraint imposed by the closed-chain between the robot and door. The proposed framework obtains the path of the whole-body configuration in two steps. First, the path for the pose of the mobile robot and the path for the door angle are computed by using the graph search algorithm. In graph search, an integer variable called area indicator is introduced as an element of state, which indicates where the robot is located relative to the door. Especially, the area indicator expresses a process of door traversal. In the second step, the configuration of the manipulator is computed by the inverse kinematics (IK) solver from the path of the mobile robot and door angle. The proposed framework has a distinct advantage over the existing methods that manually determine several parameters such as which direction to approach the door and the angle of the door required for passage. The effectiveness of the proposed framework was validated through experiments with a nonholonomic mobile manipulator. Second, a whole-body controller is presented based on the optimization method that can consider both equality and inequality constraints. The method computes the optimal solution of the weighted hierarchical optimization problem. The method is developed to resolve the redundancy of robots with a large number of Degrees of Freedom (DOFs), such as a mobile manipulator or a humanoid, so that they can execute multiple tasks with differently weighted joint motion for each task priority. The proposed method incorporates the weighting matrix into the first-order optimality condition of the optimization problem and leverages an active-set method to handle equality and inequality constraints. In addition, it is computationally efficient because the solution is calculated in a weighted joint space with symmetric null-space projection matrices for propagating recursively to a low priority task. Consequently, robots that utilize the proposed controller effectively show whole-body motions handling prioritized tasks with differently weighted joint spaces. The effectiveness of the proposed controller was validated through experiments with a nonholonomic mobile manipulator as well as a humanoid. Lastly, as one of dynamic constraints for the mobile manipulator, a reactive self-collision avoidance algorithm is developed. The proposed method mainly focuses on self-collision between a manipulator and the mobile robot. We introduce the concept of a distance buffer border (DBB), which is a 3D curved surface enclosing a buffer region of the mobile robot. The region has the thickness equal to buffer distance. When the distance between the manipulator and mobile robot is less than the buffer distance, i.e. the manipulator lies inside the buffer region of the mobile robot, the proposed strategy is to move the mobile robot away from the manipulator in order for the manipulator to be placed outside the border of the region, the DBB. The strategy is achieved by exerting force on the mobile robot. Therefore, the manipulator can avoid self-collision with the mobile robot without modifying the predefined motion of the manipulator in a world Cartesian coordinate frame. In particular, the direction of the force is determined by considering the non-holonomic constraint of the differentially driven mobile robot. Additionally, the reachability of the manipulator is considered to arrive at a configuration in which the manipulator can be more maneuverable. To realize the desired force and resulting torque, an avoidance task is constructed by converting them into the accelerations of the mobile robot and smoothly inserted with a top priority into the controller. The proposed algorithm was implemented on a differentially driven mobile robot with a 7-DOFs robotic arm and its performance was demonstrated in various experimental scenarios.1 INTRODUCTION 1 1.1 Motivation 1 1.2 Contributions of thesis 2 1.3 Overview of thesis 3 2 WHOLE-BODY MOTION PLANNER : APPLICATION TO NAVIGATION INCLUDING DOOR TRAVERSAL 5 2.1 Background & related works 7 2.2 Proposed framework 9 2.2.1 Computing path for mobile robot and door angle - S1 10 2.2.1.1 State 10 2.2.1.2 Action 13 2.2.1.3 Cost 15 2.2.1.4 Search 18 2.2.2 Computing path for arm configuration - S2 20 2.3 Results 21 2.3.1 Application to pull and push-type door 21 2.3.2 Experiment in cluttered environment 22 2.3.3 Experiment with different robot platform 23 2.3.4 Comparison with separate planning by existing works 24 2.3.5 Experiment with real robot 29 2.4 Conclusion 29 3 WHOLE-BODY CONTROLLER : WEIGHTED HIERARCHICAL QUADRATIC PROGRAMMING 31 3.1 Related works 32 3.2 Problem statement 34 3.2.1 Pseudo-inverse with weighted least-squares norm for each task 35 3.2.2 Problem statement 37 3.3 WHQP with equality constraints 37 3.4 WHQP with inequality constraints 45 3.5 Experimental results 48 3.5.1 Simulation experiment with nonholonomic mobile manipulator 48 3.5.1.1 Scenario description 48 3.5.1.2 Task and weighting matrix description 49 3.5.1.3 Results 51 3.5.2 Real experiment with nonholonomic mobile manipulator 53 3.5.2.1 Scenario description 53 3.5.2.2 Task and weighting matrix description 53 3.5.2.3 Results 54 3.5.3 Real experiment with humanoid 55 3.5.3.1 Scenario description 55 3.5.3.2 Task and weighting matrix description 55 3.5.3.3 Results 57 3.6 Discussions and implementation details 57 3.6.1 Computation cost 57 3.6.2 Composite weighting matrix in same hierarchy 59 3.6.3 Nullity of WHQP 59 3.7 Conclusion 59 4 WHOLE-BODY CONSTRAINT : SELF-COLLISION AVOIDANCE 61 4.1 Background & related Works 64 4.2 Distance buffer border and its score computation 65 4.2.1 Identification of potentially colliding link pairs 66 4.2.2 Distance buffer border 67 4.2.3 Evaluation of distance buffer border 69 4.2.3.1 Singularity of the differentially driven mobile robot 69 4.2.3.2 Reachability of the manipulator 72 4.2.3.3 Score of the DBB 74 4.3 Self-collision avoidance algorithm 75 4.3.1 Generation of the acceleration for the mobile robot 76 4.3.2 Generation of the repulsive acceleration for the other link pair 82 4.3.3 Construction of an acceleration-based task for self-collision avoidance 83 4.3.4 Insertion of the task in HQP-based controller 83 4.4 Experimental results 86 4.4.1 System overview 87 4.4.2 Experimental results 87 4.4.2.1 Self-collision avoidance while tracking the predefined trajectory 87 4.4.2.2 Self-collision avoidance while manually guiding the end-effector 89 4.4.2.3 Extension to obstacle avoidance when opening the refrigerator 91 4.4.3 Discussion 94 4.5 Conclusion 95 5 CONCLUSIONS 97 Abstract (In Korean) 113 Acknowlegement 116๋ฐ•

    Development of a doorframe-typed swinging seedling pick-up device for automatic field transplantation

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    A doorframe-typed swing seedling pick-up device for automatic field transplanters was developed and evaluated in a laboratory. The device, consisting of a path manipulator and two grippers, can move the pins slowly to extract seedlings from the tray cells and return quickly to the pick-up point for the next extraction. The path manipulator was constructed with the creative design of type-โ…ก mechanism combination in series. It consists of an oscillating guide linkage mechanism and a grooved globoidal cam mechanism. The gripper is a pincette-type mechanism using the pick-up pins to penetrate into the root mass for seedling extraction. The dynamic analysis of the designed seedling pick-up device was simulated with ADAMS software. Being the first prototype, various performance tests under local production conditions were conducted to find out the optimal machine operation parameters and transplant production conditions. As the gripper with multiple fine pins was moved by the swing pick-up device, it can effectively complete the transplanting work cycle of extracting, transferring, and discharging a seedling. The laboratory evaluation showed that the pick-up device equipped with two grippers can extract 80 seedlings/min with a 90% success and a 3% failure in discharging seedlings, using 42-day-old tomato plantlets. The quality of extracting seedlings was satisfactory

    Vitreo-retinal eye surgery robot : sustainable precision

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    Vitreo-retinal eye surgery encompasses the surgical procedures performed on the vitreous humor and the retina. A procedure typically consists of the removal of the vitreous humor, the peeling of a membrane and/or the repair of a retinal detachment. Vitreo-retinal surgery is performed minimal invasively. Small needle shaped instruments are inserted into the eye. Instruments are manipulated by hand in four degrees of freedom about the insertion point. Two rotations move the instrument tip laterally, in addition to a translation in axial instrument direction and a rotation about its longitudinal axis. The manipulation of the instrument tip, e.g. a gripping motion can be considered as a fifth degree of freedom. While performing vitreo-retinal surgery manually, the surgeon faces various challenges. Typically, delicate micrometer range thick tissue is operated, for which steady hand movements and high accuracy instrument manipulation are required. Lateral instrument movements are inverted by the pivoting insertion point and scaled depending on the instrument insertion depth. A maximum of two instruments can be used simultaneously. There is nearly no perception of surgical forces, since most forces are below the human detection limit. Therefore, the surgeon relies only on visual feedback, obtained via a microscope or endoscope. Both vision systems force the surgeon to work in a static and non ergonomic body posture. Although the surgeonโ€™s proficiency improves throughout his career, hand tremor will become a problem at higher age. Robotically assisted surgery with a master-slave system can assist the surgeon in these challenges. The slave system performs the actual surgery, by means of instrument manipulators which handle the instruments. The surgeon remains in control of the instruments by operating haptic interfaces via a master. Using electronic hardware and control software, the master and slave are connected. Amongst others, advantages as tremor filtering, up-scaled force feedback, down-scaled motions and stabilized instrument positioning will enhance dexterity on surgical tasks. Furthermore, providing the surgeon an ergonomic body posture will prolong the surgeonโ€™s career. This thesis focuses on the design and realization of a high precision slave system for eye surgery. The master-slave system uses a table mounted design, where the system is compact, lightweight, easy to setup and equipped to perform a complete intervention. The slave system consists of two main parts: the instrument manipulators and their passive support system. Requirements are derived from manual eye surgery, conversations with medical specialists and analysis of the human anatomy and vitreo-retinal interventions. The passive support system provides a stiff connection between the instrument manipulator, patient and surgical table. Given the human anatomical diversity, presurgical adjustments can be made to allow the instrument manipulators to be positioned over each eye. Most of the support system is integrated within the patientโ€™s headrest. On either the left or right side, two exchangeable manipulator-support arms can be installed onto the support system, depending on the eye being operated upon. The compact, lightweight and easy to install design, allows for a short setup time and quick removal in case of a complication. The slave systemโ€™s surgical reach is optimized to emulate manually performed surgery. For bimanual instrument operation, two instrument manipulators are used. Additional instrument manipulators can be used for non-active tools e.g. an illumination probe or an endoscope. An instrument manipulator allows the same degrees of freedom and a similar reach as manually performed surgery. Instrument forces are measured to supply force feedback to the surgeon via haptic interfaces. The instrument manipulator is designed for high stiffness, is play free and has low friction to allow tissue manipulation with high accuracy. Each instrument manipulator is equipped with an on board instrument change system, by which instruments can be changed in a fast and secure way. A compact design near the instrument allows easy access to the surgical area, leaving room for the microscope and peripheral equipment. The acceptance of a surgical robot for eye surgery mostly relies on equipment safety and reliability. The design of the slave system features various safety measures, e.g. a quick release mechanism for the instrument manipulator and additional locks on the pre-surgical adjustment fixation clamp. Additional safety measures are proposed, like a hard cover over the instrument manipulator and redundant control loops in the controlling FPGA. A method to fixate the patientโ€™s head to the headrest by use of a custom shaped polymer mask is proposed. Two instrument manipulators and their passive support system have been realized so far, and the first experimental results confirm the designed low actuation torque and high precision performance

    A framework for compliant physical interaction : the grasp meets the task

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    Although the grasp-task interplay in our daily life is unquestionable, very little research has addressed this problem in robotics. In order to fill the gap between the grasp and the task, we adopt the most successful approaches to grasp and task specification, and extend them with additional elements that allow to define a grasp-task link. We propose a global sensor-based framework for the specification and robust control of physical interaction tasks, where the grasp and the task are jointly considered on the basis of the task frame formalism and the knowledge-based approach to grasping. A physical interaction task planner is also presented, based on the new concept of task-oriented hand pre-shapes. The planner focuses on manipulation of articulated parts in home environments, and is able to specify automatically all the elements of a physical interaction task required by the proposed framework. Finally, several applications are described, showing the versatility of the proposed approach, and its suitability for the fast implementation of robust physical interaction tasks in very different robotic systems

    Intelligent control of mobile robot with redundant manipulator & stereovision: quantum / soft computing toolkit

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    The task of an intelligent control system design applying soft and quantum computational intelligence technologies discussed. An example of a control object as a mobile robot with redundant robotic manipulator and stereovision introduced. Design of robust knowledge bases is performed using a developed computational intelligence โ€“ quantum / soft computing toolkit (QC/SCOptKBTM). The knowledge base self-organization process of fuzzy homogeneous regulators through the application of end-to-end IT of quantum computing described. The coordination control between the mobile robot and redundant manipulator with stereovision based on soft computing described. The general design methodology of a generalizing control unit based on the physical laws of quantum computing (quantum information-thermodynamic trade-off of control quality distribution and knowledge base self-organization goal) is considered. The modernization of the pattern recognition system based on stereo vision technology presented. The effectiveness of the proposed methodology is demonstrated in comparison with the structures of control systems based on soft computing for unforeseen control situations with sensor system

    Robust Door Operation with the Toyota Human Support Robot. Robotic perception, manipulation and learning

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    Robots are progressively spreading to urban, social and assistive domains. Service robots operating in domestic environments typically face a variety of objects they have to deal with to fulfill their tasks. Some of these objects are articulated such as cabinet doors and drawers. The ability to deal with such objects is relevant, as for example navigate between rooms or assist humans in their mobility. The exploration of this task rises interesting questions in some of the main robotic threads such as perception, manipulation and learning. In this work a general framework to robustly operate different types of doors with a mobile manipulator robot is proposed. To push the state-of-the-art, a novel algorithm, that fuses a Convolutional Neural Network with point cloud processing for estimating the end-effector grasping pose in real-time for multiple handles simultaneously from single RGB-D images, is proposed. Also, a Bayesian framework that embodies the robot with the ability to learn the kinematic model of the door from observations of its motion, as well as from previous experiences or human demonstrations. Combining this probabilistic approach with state-of-the-art motion planninOutgoin

    Towards automated sample collection and return in extreme underwater environments

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    ยฉ The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Billings, G., Walter, M., Pizarro, O., Johnson-Roberson, M., & Camilli, R. Towards automated sample collection and return in extreme underwater environments. Journal of Field Robotics, 2(1), (2022): 1351โ€“1385, https://doi.org/10.55417/fr.2022045.In this report, we present the system design, operational strategy, and results of coordinated multivehicle field demonstrations of autonomous marine robotic technologies in search-for-life missions within the Pacific shelf margin of Costa Rica and the Santorini-Kolumbo caldera complex, which serve as analogs to environments that may exist in oceans beyond Earth. This report focuses on the automation of remotely operated vehicle (ROV) manipulator operations for targeted biological sample-collection-and-return from the seafloor. In the context of future extraterrestrial exploration missions to ocean worlds, an ROV is an analog to a planetary lander, which must be capable of high-level autonomy. Our field trials involve two underwater vehicles, the SuBastian ROV and the Nereid Under Ice (NUI) hybrid ROV for mixed initiative (i.e., teleoperated or autonomous) missions, both equipped seven-degrees-of-freedom hydraulic manipulators. We describe an adaptable, hardware-independent computer vision architecture that enables high-level automated manipulation. The vision system provides a three-dimensional understanding of the workspace to inform manipulator motion planning in complex unstructured environments. We demonstrate the effectiveness of the vision system and control framework through field trials in increasingly challenging environments, including the automated collection and return of biological samples from within the active undersea volcano Kolumbo. Based on our experiences in the field, we discuss the performance of our system and identify promising directions for future research.This work was funded under a NASA PSTAR grant, number NNX16AL08G, and by the National Science Foundation under grants IIS-1830660 and IIS-1830500. The authors would like to thank the Costa Rican Ministry of Environment and Energy and National System of Conservation Areas for permitting research operations at the Costa Rican shelf margin, and the Schmidt Ocean Institute (including the captain and crew of the R/V Falkor and ROV SuBastian) for their generous support and making the FK181210 expedition safe and highly successful. Additionally, the authors would like to thank the Greek Ministry of Foreign Affairs for permitting the 2019 Kolumbo Expedition to the Kolumbo and Santorini calderas, as well as Prof. Evi Nomikou and Dr. Aggelos Mallios for their expert guidance and tireless contributions to the expedition

    HERO Glove

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    Non-repetitive manipulation tasks that are easy for humans to perform are difficult for autonomous robots to execute. The Haptic Exoskeletal Robot Operator (HERO) Glove is a system designed for users to remotely control robot manipulators whilst providing sensory feedback to the user. This realistic haptic feedback is achieved through the use of toroidal air-filled actuators that stiffen up around the userโ€™s fingers. Tactile sensor data is sent from the robot to the HERO Glove, where it is used to vary the pressure in the toroidal actuators to simulate the sense of touch. Curvature sensors and inertial measurement units are used to capture the gloveโ€™s pose to control the robot
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