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    ์•ˆ์ „ํ•œ ์žฌ๊ตฌ์„ฑ ๋กœ๋ด‡ ์‹œ์Šคํ…œ: ์„ค๊ณ„, ํ”„๋กœ๊ทธ๋ž˜๋ฐ ๋ฐ ๋ฐ˜์‘ํ˜• ๊ฒฝ๋กœ๊ณ„ํš

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€, 2020. 8. ๋ฐ•์ข…์šฐ.The next generation of robots are being asked to work in close proximity to humans. At the same time, the robot should have the ability to change its topology to flexibly cope with various tasks. To satisfy these two requirements, we propose a novel modular reconfi gurable robot and accompanying software architecture, together with real-time motion planning algorithms to allow for safe operation in unstructured dynamic environments with humans. Two of the key innovations behind our modular manipulator design are a genderless connector and multi-dof modules. By making the modules connectable regardless of the input/output directions, a genderless connector increases the number of possible connections. The developed genderless connector can transmit as much load as necessary to an industrial robot. In designing two-dof modules, an offset between two joints is imposed to improve the overall integration and the safety of the modules. To cope with the complexity in modeling due to the genderless connector and multi-dof modules, a programming architecture for modular robots is proposed. The key feature of the proposed architecture is that it efficiently represents connections of multi-dof modules only with connections between modules, while existing architectures should explicitly represent all connections between links and joints. The data structure of the proposed architecture contains properties of tree-structured multi-dof modules with intra-module relations. Using the data structure and connection relations between modules, kinematic/dynamic parameters of connected modules can be obtained through forward recursion. For safe operation of modular robots, real-time robust collision avoidance algorithms for kinematic singularities are proposed. The main idea behind the algorithms is generating control inputs that increase the directional manipulability of the robot to the object direction by reducing directional safety measures. While existing directional safety measures show undesirable behaviors in the vicinity of the kinematic singularities, the proposed geometric safety measure generates stable control inputs in the entire joint space. By adding the preparatory input from the geometric safety measure to the repulsive input, a hierarchical collision avoidance algorithm that is robust to kinematic singularity is implemented. To mathematically guarantee the safety of the robot, another collision avoidance algorithm using the invariance control framework with velocity-dependent safety constraints is proposed. When the object approached the robot from a singular direction, the safety constraints are not satis ed in the initial state of the robot and the safety cannot be guaranteed using the invariance control. By proposing a control algorithm that quickly decreases the preparatory constraints below thresholds, the robot re-enters the constraint set and avoids collisions using the invariance control framework. The modularity and safety of the developed reconfi gurable robot is validated using a set of simulations and hardware experiments. The kinematic/dynamic model of the assembled robot is obtained in real-time and used to accurately control the robot. Due to the safe design of modules with o sets and the high-level safety functions with collision avoidance algorithms, the developed recon figurable robot has a broader safe workspace and wider ranger of safe operation speed than those of cooperative robots.๋‹ค์Œ ์„ธ๋Œ€์˜ ๋กœ๋ด‡์€ ์‚ฌ๋žŒ๊ณผ ๊ฐ€๊นŒ์ด์—์„œ ํ˜‘์—…ํ•  ์ˆ˜ ์žˆ๋Š” ๊ธฐ๋Šฅ์„ ๊ฐ€์ ธ์•ผํ•œ๋‹ค. ๊ทธ์™€ ๋™์‹œ์—, ๋กœ๋ด‡์€ ๋‹ค์–‘ํ•˜๊ฒŒ ๋ณ€ํ•˜๋Š” ์ž‘์—…์— ๋Œ€ํ•ด ์œ ์—ฐํ•˜๊ฒŒ ๋Œ€์ฒ˜ํ•  ์ˆ˜ ์žˆ๋„๋ก ์ž์‹ ์˜ ๊ตฌ์กฐ๋ฅผ ๋ฐ”๊พธ๋Š” ๊ธฐ๋Šฅ์„ ๊ฐ€์ ธ์•ผ ํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ๋‘ ๊ฐ€์ง€ ์š”๊ตฌ์กฐ๊ฑด์„ ๋งŒ์กฑ์‹œํ‚ค๊ธฐ ์œ„ํ•ด, ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ƒˆ๋กœ์šด ๋ชจ๋“ˆ๋ผ ๋กœ๋ด‡ ์‹œ์Šคํ…œ๊ณผ ํ”„๋กœ๊ทธ๋ž˜๋ฐ ์•„ํ‚คํ…์ณ๋ฅผ ์ œ์‹œํ•˜๊ณ , ์‚ฌ๋žŒ์ด ์กด์žฌํ•˜๋Š” ๋™์  ํ™˜๊ฒฝ์—์„œ ์•ˆ์ „ํ•œ ๋กœ๋ด‡์˜ ์šด์šฉ์„ ์œ„ํ•œ ์‹ค์‹œํ•œ ๊ฒฝ๋กœ ๊ณ„ํš ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์‹œํ•œ๋‹ค. ๊ฐœ๋ฐœ๋œ ๋ชจ๋“ˆ๋ผ ๋กœ๋ด‡์˜ ๋‘ ๊ฐ€์ง€ ํ•ต์‹ฌ์ ์ธ ํ˜์‹ ์„ฑ์€ ๋ฌด์„ฑ๋ณ„ ์ปค๋„ฅํ„ฐ์™€ ๋‹ค์ž์œ ๋„ ๋ชจ๋“ˆ์—์„œ ์ฐพ์„ ์ˆ˜ ์žˆ๋‹ค. ์ž…๋ ฅ/์ถœ๋ ฅ ๋ฐฉํ–ฅ์— ์ƒ๊ด€ ์—†์ด ๋ชจ๋“ˆ์ด ์—ฐ๊ฒฐ๋  ์ˆ˜ ์žˆ๋„๋ก ํ•จ์œผ๋กœ์จ, ๋ฌด์„ฑ๋ณ„ ์ปค๋„ฅํ„ฐ๋Š” ๊ฒฐํ•ฉ ๊ฐ€๋Šฅํ•œ ๊ฒฝ์šฐ์˜ ์ˆ˜๋ฅผ ๋Š˜๋ฆด ์ˆ˜ ์žˆ๋‹ค. ๊ฐœ๋ฐœ๋œ ๋ฌด์„ฑ๋ณ„ ์ปค๋„ฅํ„ฐ๋Š” ์‚ฐ์—…์šฉ ๋กœ๋ด‡์—์„œ ์š”๊ตฌ๋˜๋Š” ์ถฉ๋ถ„ํ•œ ๋ถ€ํ•˜๋ฅผ ๊ฒฌ๋”œ ์ˆ˜ ์žˆ๋„๋ก ์„ค๊ณ„๋˜์—ˆ๋‹ค. 2 ์ž์œ ๋„ ๋ชจ๋“ˆ์˜ ์„ค๊ณ„์—์„œ ๋‘ ์ถ• ์‚ฌ์ด์— ์˜คํ”„์…‹์„ ๊ฐ€์ง€๋„๋ก ํ•จ์œผ๋กœ์จ ์ „์ฒด์ ์ธ ์™„์„ฑ๋„ ๋ฐ ์•ˆ์ „๋„๋ฅผ ์ฆ๊ฐ€์‹œ์ผฐ๋‹ค. ๋ฌด์„ฑ๋ณ„ ์ปค๋„ฅํ„ฐ์™€ ๋‹ค์ž์œ ๋„ ๋ชจ๋“ˆ๋กœ ์ธํ•œ ๋ชจ๋ธ๋ง์˜ ๋ณต์žก์„ฑ์— ๋Œ€์‘ํ•˜๊ธฐ ์œ„ํ•ด, ์ผ๋ฐ˜์ ์ธ ๋ชจ๋“ˆ๋ผ ๋กœ๋ด‡์„ ์œ„ํ•œ ์†Œํ”„ํŠธ์›จ์–ด ์•„ํ‚คํ…์ณ๋ฅผ ์ œ์•ˆํ•˜์˜€๋‹ค. ๊ธฐ์กด ๋ชจ๋“ˆ๋ผ ๋กœ๋ด‡์˜ ์—ฐ๊ฒฐ์„ ๋‚˜ํƒ€๋‚ด๋Š” ๋ฐฉ๋ฒ•์ด ๋ชจ๋“  ๋งํฌ์™€ ์กฐ์ธํŠธ ์‚ฌ์ด์˜ ์—ฐ๊ฒฐ ๊ด€๊ณ„๋ฅผ ๋ณ„๋„๋กœ ๋‚˜ํƒ€๋‚ด์•ผํ•˜๋Š” ๊ฒƒ๊ณผ ๋‹ค๋ฅด๊ฒŒ, ์ œ์•ˆ๋œ ์•„ํ‚คํ…์ณ๋Š” ๋ชจ๋“ˆ๋“ค ์‚ฌ์ด์˜ ์—ฐ๊ฒฐ๊ด€๊ณ„๋งŒ์„ ๋‚˜ํƒ€๋ƒ„์œผ๋กœ์จ ํšจ์œจ์ ์ธ ๋‹ค์ž์œ ๋„ ๋ชจ๋“ˆ์˜ ์—ฐ๊ฒฐ๊ด€๊ณ„๋ฅผ ๋‚˜ํƒ€๋‚ผ ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ํŠน์ง•์œผ๋กœ ํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ํŠธ๋ฆฌ ๊ตฌ์กฐ๋ฅผ ๊ฐ€์ง€๋Š” ์ผ๋ฐ˜์ ์ธ ๋‹ค์ž์œ ๋„ ๋ชจ๋“ˆ์˜ ์„ฑ์งˆ์„ ๋‚˜ํƒ€๋‚ด๋Š” ๋ฐ์ดํ„ฐ ๊ตฌ์กฐ๋ฅผ ์ •์˜ํ•˜์˜€๋‹ค. ๋ชจ๋“ˆ๋“ค ์‚ฌ์ด์˜ ์—ฐ๊ฒฐ๊ด€๊ณ„ ๋ฐ ๋ฐ์ดํ„ฐ ๊ตฌ์กฐ๋ฅผ ์ด์šฉํ•˜์—ฌ, ์ •ํ™•ํ•œ ๊ธฐ๊ตฌํ•™/๋™์—ญํ•™ ๋ชจ๋ธ ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์–ป์–ด๋‚ด๋Š” ์ˆœ๋ฐฉํ–ฅ ์žฌ๊ท€ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ตฌํ˜„ํ•˜์˜€๋‹ค. ๋ชจ๋“ˆ๋ผ ๋กœ๋ด‡์˜ ์•ˆ์ „ํ•œ ์šด์šฉ์„ ์œ„ํ•ด, ๊ธฐ๊ตฌํ•™์  ํŠน์ด์ ์— ๊ฐ•๊ฑดํ•œ ์‹ค์‹œ๊ฐ„ ์ถฉ๋ŒํšŒํ”ผ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ๋ฐฉํ–ฅ์„ฑ ์•ˆ์ „๋„๋ฅผ ์ค„์ด๋Š” ๋ฐฉํ–ฅ์˜ ์ œ์–ด ์ž…๋ ฅ์„ ์ƒ์„ฑํ•˜์—ฌ ๋ฌผ์ฒด ๋ฐฉํ–ฅ์œผ๋กœ์˜ ๋กœ๋ด‡ ๋ฐฉํ–ฅ์„ฑ ๋งค๋‹ˆํ“ฐ๋Ÿฌ๋นŒ๋ฆฌํ‹ฐ๋ฅผ ์ฆ๊ฐ€์‹œํ‚ค๋Š” ๊ฒƒ์ด ์ œ์•ˆํ•œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ํ•ต์‹ฌ์ด๋‹ค. ๊ธฐ์กด์˜ ๋ฐฉํ–ฅ์„ฑ ์•ˆ์ „๋„๊ฐ€ ๊ธฐ๊ตฌํ•™์  ํŠน์ด์  ๊ทผ์ฒ˜์—์„œ ์›ํ•˜์ง€ ์•Š๋Š” ์„ฑ์งˆ์„ ๊ฐ€์ง€๋Š” ๊ฒƒ๊ณผ๋Š” ๋ฐ˜๋Œ€๋กœ, ์ œ์•ˆํ•œ ๊ธฐํ•˜ํ•™์  ์•ˆ์ „๋„๋Š” ์ „์ฒด ์กฐ์ธํŠธ ๊ณต๊ฐ„์—์„œ ์•ˆ์ •์ ์ธ ์ œ์–ด ์ž…๋ ฅ์„ ์ƒ์„ฑํ•œ๋‹ค. ์ด ๊ธฐํ•˜ํ•™์  ์•ˆ์ „๋„๋ฅผ ์ด์šฉํ•˜์—ฌ, ๊ธฐ๊ตฌํ•™์  ํŠน์ด์ ์— ๊ฐ•๊ฑดํ•œ ๊ณ„์ธต์  ์ถฉ๋ŒํšŒํ”ผ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ตฌํ˜„ํ•˜์˜€๋‹ค. ์ˆ˜ํ•™์ ์œผ๋กœ ๋กœ๋ด‡์˜ ์•ˆ์ „๋„๋ฅผ ๋ณด์žฅํ•˜๊ธฐ ์œ„ํ•ด, ์ƒ๋Œ€์†๋„์— ์ข…์†์ ์ธ ์•ˆ์ „ ์ œ์•ฝ์กฐ๊ฑด์„ ๊ฐ€์ง€๋Š” ๋ถˆ๋ณ€ ์ œ์–ด ํ”„๋ ˆ์ž„์›Œํฌ์„ ์ด์šฉํ•˜์—ฌ ๋˜ ํ•˜๋‚˜์˜ ์ถฉ๋Œ ํšŒํ”ผ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ๋ฌผ์ฒด๊ฐ€ ํŠน์ด์  ๋ฐฉํ–ฅ์œผ๋กœ๋ถ€ํ„ฐ ๋กœ๋ด‡์— ์ ‘๊ทผํ•  ๋•Œ, ๋กœ๋ด‡์˜ ์ดˆ๊ธฐ ์ƒํƒœ์—์„œ ์•ˆ์ „ ์ œ์•ฝ์กฐ๊ฑด์„ ๋งŒ์กฑ์‹œํ‚ค์ง€ ๋ชปํ•˜๊ฒŒ ๋˜์–ด ๋ถˆ๋ณ€์ œ์–ด๋ฅผ ์ ์šฉํ•  ์ˆ˜ ์—†๊ฒŒ ๋œ๋‹ค. ์ค€๋น„ ์ œ์•ฝ์กฐ๊ฑด์„ ๋น ๋ฅด๊ฒŒ ์ž„๊ณ„์  ์•„๋ž˜๋กœ ๊ฐ์†Œ์‹œํ‚ค๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ ์šฉํ•จ์œผ๋กœ์จ, ๋กœ๋ด‡์€ ์ œ์•ฝ์กฐ๊ฑด ์ง‘ํ•ฉ์— ๋‹ค์‹œ ๋“ค์–ด๊ฐ€๊ณ  ๋ถˆ๋ณ€ ์ œ์–ด ๋ฐฉ๋ฒ•์„ ์ด์šฉํ•˜์—ฌ ์ถฉ๋Œ์„ ํšŒํ”ผํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋œ๋‹ค. ๊ฐœ๋ฐœ๋œ ์žฌ๊ตฌ์„ฑ ๋กœ๋ด‡์˜ ๋ชจ๋“ˆ๋ผ๋ฆฌํ‹ฐ์™€ ์•ˆ์ „๋„๋Š” ์ผ๋ จ์˜ ์‹œ๋ฎฌ๋ ˆ์ด์…˜๊ณผ ํ•˜๋“œ์›จ์–ด ์‹คํ—˜์„ ํ†ตํ•ด ๊ฒ€์ฆ๋˜์—ˆ๋‹ค. ์‹ค์‹œ๊ฐ„์œผ๋กœ ์กฐ๋ฆฝ๋œ ๋กœ๋ด‡์˜ ๊ธฐ๊ตฌํ•™/๋™์—ญํ•™ ๋ชจ๋ธ์„ ์–ป์–ด๋‚ด ์ •๋ฐ€ ์ œ์–ด์— ์‚ฌ์šฉํ•˜์˜€๋‹ค. ์•ˆ์ „ํ•œ ๋ชจ๋“ˆ ๋””์ž์ธ๊ณผ ์ถฉ๋Œ ํšŒํ”ผ ๋“ฑ์˜ ๊ณ ์ฐจ์› ์•ˆ์ „ ๊ธฐ๋Šฅ์„ ํ†ตํ•˜์—ฌ, ๊ฐœ๋ฐœ๋œ ์žฌ๊ตฌ์„ฑ ๋กœ๋ด‡์€ ๊ธฐ์กด ํ˜‘๋™๋กœ๋ด‡๋ณด๋‹ค ๋„“์€ ์•ˆ์ „ํ•œ ์ž‘์—…๊ณต๊ฐ„๊ณผ ์ž‘์—…์†๋„๋ฅผ ๊ฐ€์ง„๋‹ค.1 Introduction 1 1.1 Modularity and Recon gurability 1 1.2 Safe Interaction 4 1.3 Contributions of This Thesis 9 1.3.1 A Recon gurable Modular Robot System with Bidirectional Modules 9 1.3.2 A Modular Robot Software Programming Architecture 10 1.3.3 Anticipatory Collision Avoidance Planning 11 1.4 Organization of This Thesis 14 2 Design and Prototyping of the ModMan 17 2.1 Genderless Connector 18 2.2 Modules for ModMan 21 2.2.1 Joint Modules 21 2.2.2 Link and Gripper Modules 25 2.3 Experiments 26 2.3.1 System Setup 26 2.3.2 Repeatability Comparison with Non-recon gurable Robot Manipulators 28 2.3.3 E ect of the O set in Two-dof Modules 30 2.4 Conclusion 32 3 A Programming Architecture for Modular Recon gurable Robots 33 3.1 Data Structure for Multi-dof Joint Modules 34 3.2 Automatic Kinematic Modeling 37 3.3 Automatic Dynamic Modeling 40 3.4 Flexibility in Manipulator 42 3.5 Experiments 45 3.5.1 System Setup 46 3.5.2 Recon gurability 46 3.5.3 Pick-and-Place with Vision Sensors 48 3.6 Conclusion 49 4 A Preparatory Safety Measure for Robust Collision Avoidance 51 4.1 Preliminaries on Manipulability and Safety 52 4.2 Analysis on Reected Mass 56 4.3 Manipulability Control on S+(1;m) 60 4.3.1 Geometry of the Group of Positive Semi-de nite Matrices 60 4.3.2 Rank-One Manipulability Control 63 4.4 Collision Avoidance with Preparatory Action 65 4.4.1 Repulsive and Preparatory Potential Functions 65 4.4.2 Hierarchical Control and Task Relaxation 67 4.5 Experiments 70 4.5.1 Manipulability Control 71 4.5.2 Collision Avoidance 75 4.6 Conclusion 82 5 Collision Avoidance with Velocity-Dependent Constraints 85 5.1 Input-Output Linearization 87 5.2 Invariance Control 89 5.3 Velocity-Dependent Constraints for Robot Safety 90 5.3.1 Velocity-Dependent Repulsive Constraints 90 5.3.2 Preparatory Constraints 92 5.3.3 Corrective Control for Dangerous Initial State 93 5.4 Experiment 95 5.5 Conclusion 98 6 Conclusion 101 6.1 Overview of This Thesis 101 6.2 Future Work 104 Appendix A Appendix 107 A.1 Preliminaries on Graph Theory 107 A.2 Lie-Theoretic Formulations of Robot Kinematics and Dynamics 108 A.3 Derivatives of Eigenvectors and Eigenvalues 110 A.4 Proof of Proposition Proposition 4.1 111 A.5 Proof of Triangle Inequality When p = 1 114 A.6 Detailed Conditions for a Danger Field 115 Bibliography 117 Abstract 127Docto

    Swarm Robotics: An Extensive Research Review

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    Heterogeneous Self-Reconfiguring Robotics: Ph.D. Thesis Proposal

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    Self-reconfiguring robots are modular systems that can change shape, or reconfigure, to match structure to task. They comprise many small, discrete, often identical modules that connect together and that are minimally actuated. Global shape transformation is achieved by composing local motions. Systems with a single module type, known as homogeneous systems, gain fault tolerance, robustness and low production cost from module interchangeability. However, we are interested in heterogeneous systems, which include multiple types of modules such as those with sensors, batteries or wheels. We believe that heterogeneous systems offer the same benefits as homogeneous systems with the added ability to match not only structure to task, but also capability to task. Although significant results have been achieved in understanding homogeneous systems, research in heterogeneous systems is challenging as key algorithmic issues remain unexplored. We propose in this thesis to investigate questions in four main areas: 1) how to classify heterogeneous systems, 2) how to develop efficient heterogeneous reconfiguration algorithms with desired characteristics, 3) how to characterize the complexity of key algorithmic problems, and 4) how to apply these heterogeneous algorithms to perform useful new tasks in simulation and in the physical world. Our goal is to develop an algorithmic basis for heterogeneous systems. This has theoretical significance in that it addresses a major open problem in the field, and practical significance in providing self-reconfiguring robots with increased capabilities

    Autonomous Task-Based Evolutionary Design of Modular Robots

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    In an attempt to solve the problem of finding a set of multiple unique modular robotic designs that can be constructed using a given repertoire of modules to perform a specific task, a novel synthesis framework is introduced based on design optimization concepts and evolutionary algorithms to search for the optimal design. Designing modular robotic systems faces two main challenges: the lack of basic rules of thumb and design bias introduced by human designers. The space of possible designs cannot be easily grasped by human designers especially for new tasks or tasks that are not fully understood by designers. Therefore, evolutionary computation is employed to design modular robots autonomously. Evolutionary algorithms can efficiently handle problems with discrete search spaces and solutions of variable sizes as these algorithms offer feasible robustness to local minima in the search space; and they can be parallelized easily to reducing system runtime. Moreover, they do not have to make assumptions about the solution form. This dissertation proposes a novel autonomous system for task-based modular robotic design based on evolutionary algorithms to search for the optimal design. The introduced system offers a flexible synthesis algorithm that can accommodate to different task-based design needs and can be applied to different modular shapes to produce homogenous modular robots. The proposed system uses a new representation for modular robotic assembly configuration based on graph theory and Assembly Incidence Matrix (AIM), in order to enable efficient and extendible task-based design of modular robots that can take input modules of different geometries and Degrees Of Freedom (DOFs). Robotic simulation is a powerful tool for saving time and money when designing robots as it provides an accurate method of assessing robotic adequacy to accomplish a specific task. Furthermore, it is difficult to predict robotic performance without simulation. Thus, simulation is used in this research to evaluate the robotic designs by measuring the fitness of the evolved robots, while incorporating the environmental features and robotic hardware constraints. Results are illustrated for a number of benchmark problems. The results presented a significant advance in robotic design automation state of the art

    TOWARDS A NOVEL RESILIENT ROBOTIC SYSTEM

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    Resilient robotic systems are a kind of robotic system that is able to recover their original function after partial damage of the system. This is achieved by making changes on the partially damaged robot. In this dissertation study, a general robot, which makes sense by including active joints, passive joints, passive links, and passive adjustable links, was proposed in order to explore its resilience. Note that such a robot is also called an under-actuated robot. This dissertation presents the following studies. First, a novel architecture of robots was proposed, which is characterized as under-actuated robot. The architecture enables three types of recovery strategy, namely (1) change of the robot behavior, (2) change of the robot state, and (3) change of the robot configuration. Second, a novel docking system was developed, which allows for the realization of real-time assembly and disassembly and passive joint and adjustable passive link, and this thus enables the realization of the proposed architecture. Third, an example prototype system was built to experiment the effectiveness of the proposed architecture and to demonstrate the resilient behavior of the robot. Fourth, a novel method for robot configuration synthesis was developed, which is based on the genetic algorithm (GA), to determine the goal configuration of a partially damaged robot, at which the robot can still perform its original function. The novelty of the method lies in the integration of both discrete variables such as the number of modules, type of modules, and assembly patterns between modules and the continuous variables such as the length of modules and initial location of the robot. Fifth, a GA-based method for robot reconfiguration planning and scheduling was developed to actually change the robot from its initial configuration to the goal configuration with a minimum effort (time and energy). Two conclusions can be drawn from the above studies. First, the under-actuated robotic architecture can build a cost effective robot that can achieve the highest degree of resilience. Second, the design of the under-actuated resilient robot with the proposed docking system not only reduces the cost but also overcomes the two common actuator failures: (i) an active joint is unlocked (thus becoming a passive joint) and (ii) an active joint is locked (thus becoming an adjustable link). There are several contributions made by this dissertation to the field of robotics. The first is the finding that an under-actuated robot can be made more resilient. In the field of robotics, the concept of the under-actuated robot is available, but it has not been considered for reconfiguration (in literature, the reconfiguration is mostly about fully actuated robots). The second is the elaboration on the concept of reconfiguration planning, scheduling, and manipulation/control. In the literature of robotics, only the concept of reconfiguration planning is precisely given but not for reconfiguration scheduling. The third is the development of the model along with its algorithm for synthesis of the goal reconfiguration, reconfiguration planning, and scheduling. The application of the proposed under-actuated resilient robot lies in the operations in unknown or dangerous environments, for example, in rescue missions and space explorations. In these applications, replacement or repair of a damaged robot is impossible or cost-prohibited

    Topological representation and analysis method for multi-port and multi-orientation docking modular robots

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    For MSR Robots to successfully configure from one configuration into another, the control system must be able to visualize the current structure of the robot, which cannot be done without appropriate information about each module's docking status. Although the type of information required to visualize the structure of a MSR robot differs with the physical design of the modules, there are essential information that are commonly required, such as docking orientation and identity of neighboring modules. This paper presents a novel multi-port and multi-orientation modular robot, and a representation method that can uniquely represent the geometric structure of a group of connected modules and to analyze the number of "reconfigurable DOF" within the structure. The proposed method uses labeled planar graphs and incidence matrices to describe the docking status of the modules within the structure, which helps to effectively encode the data in computer understandable expressions. In addition to the work in configuration analysis, an innovative mechanism for detecting the orientation of each docking port is also presented.published_or_final_versio
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