가변 토폴로지 트러스 로봇의 안정적인 주행 알고리즘 개발

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 기계공학과, 2020. 8. 김종원.Variable Topology Truss (VTT) is truss structured modular robot that can self-reconfigure its topology and geometric configuration, which can be usefully applied to rescuing work in disaster site. In this thesis, design of VTT is introduced and stable rolling locomotion algorithm for VTT is proposed. To achieve self-reconfiguration feature, VTT are composed specially designed members and nodes. VTTs members consist of Spiral Zippers which are novel linear actuators that has high extension ratio, light weight and high strength. VTTs nodes consist of Passive Member-Ends and Master Member-Ends. Passive Member-Ends are linkage type spherical joint with large angle range that can accommodate many members. Master Member-Ends are spherical manipulators that built in Sphere and it move member to change topology of VTT. Rolling locomotion of VTT is achieved by controlling the center of mass by geometric reconfiguration. However, the locomotion planning is complex problem, because VTT is parallel mechanism with high degree of freedom and many constraints, which makes it difficult to predict and avoid constraints for feasible planning. Thus, it needs stable algorithm that can find locomotion trajectory even in complicated and large environment. In addition, since VTT has many sophisticated components, the algorithm must prevent VTT being damaged from ground by tumbling. To meet the requirements, proposed locomotion algorithm is composed of 3 steps; support polygon planning, center of mass planning and node position planning. In support polygon planning, support polygon path is planned by newly proposed random search algorithm, Polygon-Based Random Tree (PRT). In center of mass planning, trajectory of desired projected center of mass is planned by maximizing stability feature. Planned support polygon path and center of mass trajectory guide VTT to have good-conditioned shape which configuration is far from constraints and makes locomotion planning success even in complex and large environment. In node position planning, Non-Impact Rolling locomotion algorithm was developed to plan position of VTTs nodes that prevent damage from the ground while following planned support polygon path and center of mass trajectory. The algorithm was verified by two case study. In case study 1, locomotion planning and simulation was performed considering actual constraints of VTT. To avoid collision between VTT and obstacle, safety space was defined and considered in support polygon planning. The result shows that VTT successfully reaches the goal while avoiding obstacles and satisfying constraints. In case study 2, locomotion planning and simulation was performed in the environment having wide space and narrow passage. Nominal length of VTT was set to be large in wide space to move efficiently, and set to be small in narrow passage to pass through it. The result shows that VTT successfully reaches the goal while changing its nominal length in different terrain.가변 토폴로지 트러스 (Variable Topology Truss, VTT)는 토폴로지와 기하학적 형상의 재구성이 가능한 트러스 구조의 모듈 로봇이다. 본 논문에서는 VTT의 설계 구조를 소개하고 VTT의 안정적인 주행을 알고리즘을 제안한다. VTT는 토폴로지와 기하학적 형상의 재구성을 위해 특수한 구조의 멤버와 노드를 가진다. VTT의 멤버는 높은 압축비, 가벼운 중량, 높은 강도를 가진 신개념 선형 구동기인 스파이럴 지퍼로 구성되어 있다. VTT의 노드는 패시브 멤버 엔드와 마스터 엔드로 구성되어 있다. 패시브 멤버는 링키지 구조의 3 자유도 관절로, 넓은 각도 구동 범위를 가지고 있고 많은 수의 멤버를 연결할 수 있다. 마스터 멤버 엔드는 노드 부의 내장된 구형 매니퓰레이터로, 토폴로지 재구성 시 멤버를 이동시키는데 사용된다. VTT는 기하학적 형상을 변화하여 구르는 움직임을 통해 주행한다. VTT의 주행 알고리즘은 서포트 폴리곤 계획 단계, 무게 중심 계획 단계, 노드 위치 계획 단계로 이루어진다. 서포트 폴리곤 계획 단계에서는 새롭게 제안된 무작위 탐색 (random search) 알고리즘인 Polygon-Based Random Tree (PRT)을 적용해 서포트 폴리곤의 경로를 계획한다. 무게 중심 계획 단계에서는 안정성을 최대화하는 VTT의 무게 중심 궤적을 계획한다. 계획된 서포트 폴리곤 경로와 무게 중심 궤적을 VTT가 제한 조건으로부터 먼 좋은 상태의 형상을 유지하게 하여 복잡한 환경에 대해서도 경로 계획이 실패하지 않고 안정적으로 이루어질 수 있도록 한다. 노드 위치 계획 단계에서는 서포트 폴리곤 경로와 노드 위치의 궤적을 추종하는 노드 위치 궤적을 계획한다. 이 과정에서 비충격 롤링 이동 알고리즘 (Non-Impact Rolling locomotion algorithm)을 적용하여 지면과의 충돌로 인한 충격이 일어나지 않는 궤적을 계획한다. 실제 VTT의 제한 조건을 반영한 모델에 본 알고리즘을 적용하여 시뮬레이션을 수행한 결과, VTT가 모든 제한 조건을 만족하고 장애물을 회피하면서 목표 지점에 도달할 수 있음을 확인하였다.Chapter 1. Introduction 1 1.1 Motivation 1 1.2 Previous Truss Type Modular Robot 4 1.3 Previous Research on VTTs Locomotion 8 1.3.1 Heuristic Based Methods 9 1.3.2 Optimization Based Method 10 1.4 Objectives of Locomotion Algorithm 12 1.5 Contribution of Thesis 13 1.5.1 Introduction to Hardware Design of VTT 13 1.5.2 Stable Rolling Locomotion of VTT 15 Chapter 2. Design of Variable Topology Truss 17 2.1 Member Design 18 2.1.1 Spiral Zipper 20 2.1.2 Tensioner 26 2.2 Node Design 28 2.2.1 Passive Member-End and Sphere 29 2.2.2 Master Member-End 36 2.3 Control System 40 2.4 Node Position Control Experiment 44 Chapter 3. Mathematical Model of Variable Topology Truss 47 3.1 Configuration and Terminology 47 3.2 Inverse Kinematics 50 3.3 Constraints 51 3.4 Stability Criteria 64 Chapter 4. Locomotion Algorithm 66 4.1 Concept of Locomotion Algorithm 67 4.1.1 Method for Successful Planning and Obstacle Avoidance 67 4.1.2 Method to Prevent Damage from the Ground 71 4.1.3 Step of Locomotion Algorithm 72 4.2 Support Polygon Planning 73 4.2.1 Polygon-Based Random Tree (PRT) Algorithm 73 4.2.2 Probabilistic Completeness of PRT Algorithm 79 4.3 Center of Mass Planning 85 4.4 Node Position Planning 86 4.4.1 Concept of Non-Impact Rolling Locomotion 86 4.4.2 Planning Algorithm for Non-Impact Rolling Locomotion 89 4.4.3 Optimization Problem of Moving Phase 94 4.4.4 Optimization Problem of Landing Phase 98 4.4.5 Optimization Problem of Transient Phase 99 Chapter 5. Experimental Verification 100 5.1 Case Study 1: Actual VTT Prototype 101 5.1.1 Simulation Condition 101 5.1.2 Obstacle Avoidance Method 103 5.1.3 Simulation Result 104 5.2 Case Study 2: Environment with Narrow Passage 111 5.2.1 Simulation Condition 111 5.2.2 Support Polygon Planning with Varying Nominal Length 114 5.2.3 Simulation Result 117 Chapter 6. Conclusion 126 Bibliography 129 Abstract in Korean 134Docto

Motion Planning for Variable Topology Trusses: Reconfiguration and Locomotion

Truss robots are highly redundant parallel robotic systems that can be applied in a variety of scenarios. The variable topology truss (VTT) is a class of modular truss robots. As self-reconfigurable modular robots, a VTT is composed of many edge modules that can be rearranged into various structures depending on the task. These robots change their shape by not only controlling joint positions as with fixed morphology robots, but also reconfiguring the connectivity between truss members in order to change their topology. The motion planning problem for VTT robots is difficult due to their varying morphology, high dimensionality, the high likelihood for self-collision, and complex motion constraints. In this paper, a new motion planning framework to dramatically alter the structure of a VTT is presented. It can also be used to solve locomotion tasks that are much more efficient compared with previous work. Several test scenarios are used to show its effectiveness. Supplementary materials are available at https://www.modlabupenn.org/vtt-motion-planning/.Comment: 20 pages, 36 figure

Modular Robots Morphology Transformation And Task Execution

Self-reconfigurable modular robots are composed of a small set of modules with uniform docking interfaces. Different from conventional robots that are custom-built and optimized for specific tasks, modular robots are able to adapt to many different activities and handle hardware and software failures by rearranging their components. This reconfiguration capability allows these systems to exist in a variety of morphologies, and the introduced flexibility enables self-reconfigurable modular robots to handle a much wider range of tasks, but also complicates the design, control, and planning. This thesis considers a hierarchy framework to deploy modular robots in the real world: the robot first identifies its current morphology, then reconfigures itself into a new morphology if needed, and finally executes either manipulation or locomotion tasks. A reliable system architecture is necessary to handle a large number of modules. The number of possible morphologies constructed by modules increases exponentially as the number of modules grows, and these morphologies usually have many degrees of freedom with complex constraints. In this thesis, hardware platforms and several control methods and planning algorithms are developed to build this hierarchy framework leading to the system-level deployment of modular robots, including a hybrid modular robot (SMORES-EP) and a modular truss robot (VTT). Graph representations of modular robots are introduced as well as several algorithms for morphology identification. Efficient mobile-stylereconfiguration strategies are explored for hybrid modular robots, and a real-time planner based on optimal control is developed to perform dexterous manipulation tasks. For modular truss robots, configuration space is studied and a hybrid planning framework (sampling-based and search-based) is presented to handle reconfiguration activities. A non-impact rolling locomotion planner is then developed to drive an arbitrary truss robot in an environment

Scalable and Probabilistically Complete Planning for Robotic Spatial Extrusion

There is increasing demand for automated systems that can fabricate 3D structures. Robotic spatial extrusion has become an attractive alternative to traditional layer-based 3D printing due to a manipulator's flexibility to print large, directionally-dependent structures. However, existing extrusion planning algorithms require a substantial amount of human input, do not scale to large instances, and lack theoretical guarantees. In this work, we present a rigorous formalization of robotic spatial extrusion planning and provide several efficient and probabilistically complete planning algorithms. The key planning challenge is, throughout the printing process, satisfying both stiffness constraints that limit the deformation of the structure and geometric constraints that ensure the robot does not collide with the structure. We show that, although these constraints often conflict with each other, a greedy backward state-space search guided by a stiffness-aware heuristic is able to successfully balance both constraints. We empirically compare our methods on a benchmark of over 40 simulated extrusion problems. Finally, we apply our approach to 3 real-world extrusion problems

Computer-Aided Geometry Modeling

Techniques in computer-aided geometry modeling and their application are addressed. Mathematical modeling, solid geometry models, management of geometric data, development of geometry standards, and interactive and graphic procedures are discussed. The applications include aeronautical and aerospace structures design, fluid flow modeling, and gas turbine design

Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments

Proceedings of the NASA Conference on Space Telerobotics, volume 1

The theme of the Conference was man-machine collaboration in space. Topics addressed include: redundant manipulators; man-machine systems; telerobot architecture; remote sensing and planning; navigation; neural networks; fundamental AI research; and reasoning under uncertainty

Geometric representations for conceptual design using evolutionary algorithms

Civil engineering design problems are typically approached using traditional techniques i.e. deterministic algorithms, rather than via stochastic search such as evolutionary algorithms. However evolutionary algorithms are adept at exploring fragmented and complex search spaces, such as those found in design, but do require potential solutions to have a 'representation' amenable to evolutionary operators. Four canonical representations have been proposed including: strings (generally used for parameter based problems), voxels (shape discovery), trees and graphs (skeletal structures). Several authors have proposed design algorithms for the conceptual layout design of commercial office buildings but all are limited to buildings with rectangular floor plans. This thesis presents an evolutionary algorithm based methodology capable of representing buildings with orthogonal boundaries and atria by using a 3-section string with real encoding, which ensures the initialisation and evolutionary operations are not too disruptive on column alignments encoded via the genome. In order to handle orthogonal layouts polygon- partitioning techniques are used to decompose them into rectangular sections, which can be solved individually. However to prevent the layout becoming too discontinuous, an 'adjacency graph' is proposed which ensures column line continuity throughout the building. Dome geometric layout design is difficult, because every joint and member must be located on the external surface and not impinge on the internal void. This thesis describes a string-based representation capable of designing directly in 3D using surface area and enclosed volume as the major search parameters. The representation encodes support and joint positions, which are converted into a dome by constructing its corresponding convex hull. Once constructed the hull's edges become the structural members and its vertices the joints. This avoids many of the problems experienced by the previous approach, which suffers when restrictive constraints such as the requirement to maintain l/8th symmetry are removed. The aim of this thesis is to investigate how some civil engineering design problems, in particular structures, can be represented using evolutionary algorithms (EA) and contains two, independent experimental chapters on building layout design and geometric dome design (an introduction to EAs and design is also provided). Civil engineering design problems are typically approached using traditional techniques i.e. deterministic algorithms, rather than via stochastic search such as EAs. However EAs are adept at exploring fragmented and complex search spaces, such as those found in design, but do require potential solutions to have a 'representation' amenable to evolutionary operators. Four canonical representations have been proposed including: strings (generally used for parameter based problems), voxels (shape discovery), trees and graphs (skeletal structures). Several authors have proposed design algorithms for the conceptual layout design of commercial office buildings but all are limited to buildings with rectangular floor plans. This thesis presents an evolutionary algorithm based methodology capable of representing buildings with orthogonal boundaries and atria by using a 3-section string with real encoding, which ensures the initialisation and evolutionary operations are not too disruptive on column alignments encoded via the genome. In order to handle orthogonal layouts polygon- partitioning techniques are used to decompose them into rectangular sections, which can be solved individually. However to prevent the layout becoming too discontinuous, an 'adjacency graph' is proposed which ensures column line continuity throughout the building. Dome geometric layout design is difficult, because every joint and member must be located on the external surface and not impinge on the internal void. This thesis describes a string-based representation capable of designing directly in 3D using surface area and enclosed volume as the major search parameters. The representation encodes support and joint positions, which are converted into a dome by constructing its corresponding convex hull. Once constructed the hull's edges become the structural members and its vertices the joints. This avoids many of the problems experienced by the previous approach, which suffers th when restrictive constraints such as the requirement to maintain 1/8 symmetry are removed

Path and Motion Planning for Autonomous Mobile 3D Printing

Autonomous robotic construction was envisioned as early as the ‘90s, and yet, con- struction sites today look much alike ones half a century ago. Meanwhile, highly automated and efficient fabrication methods like Additive Manufacturing, or 3D Printing, have seen great success in conventional production. However, existing efforts to transfer printing technology to construction applications mainly rely on manufacturing-like machines and fail to utilise the capabilities of modern robotics. This thesis considers using Mobile Manipulator robots to perform large-scale Additive Manufacturing tasks. Comprised of an articulated arm and a mobile base, Mobile Manipulators, are unique in their simultaneous mobility and agility, which enables printing-in-motion, or Mobile 3D Printing. This is a 3D printing modality, where a robot deposits material along larger-than-self trajectories while in motion. Despite profound potential advantages over existing static manufacturing-like large- scale printers, Mobile 3D printing is underexplored. Therefore, this thesis tack- les Mobile 3D printing-specific challenges and proposes path and motion planning methodologies that allow this printing modality to be realised. The work details the development of Task-Consistent Path Planning that solves the problem of find- ing a valid robot-base path needed to print larger-than-self trajectories. A motion planning and control strategy is then proposed, utilising the robot-base paths found to inform an optimisation-based whole-body motion controller. Several Mobile 3D Printing robot prototypes are built throughout this work, and the overall path and motion planning strategy proposed is holistically evaluated in a series of large-scale 3D printing experiments