Designing LMPA-Based Smart Materials for Soft Robotics Applications

This doctoral research, Designing LMPA (Low Melting Point Alloy) Based Smart Materials for Soft Robotics Applications, includes the following topics: (1) Introduction; (2) Robust Bicontinuous Metal-Elastomer Foam Composites with Highly Tunable Mechanical Stiffness; (3) Actively Morphing Drone Wing Design Enabled by Smart Materials for Green Unmanned Aerial Vehicles; (4) Dynamically Tunable Friction via Subsurface Stiffness Modulation; (5) LMPA Wool Sponge Based Smart Materials with Tunable Electrical Conductivity and Tunable Mechanical Stiffness for Soft Robotics; and (6) Contributions and Future Work.Soft robots are developed to interact safely with environments. Smart composites with tunable properties have found use in many soft robotics applications including robotic manipulators, locomotors, and haptics. The purpose of this work is to develop new smart materials with tunable properties (most importantly, mechanical stiffness) upon external stimuli, and integrate these novel smart materials in relevant soft robots. Stiffness tunable composites developed in previous studies have many drawbacks. For example, there is not enough stiffness change, or they are not robust enough. Here, we explore soft robotic mechanisms integrating stiffness tunable materials and innovate smart materials as needed to develop better versions of such soft robotic mechanisms. First, we develop a bicontinuous metal-elastomer foam composites with highly tunable mechanical stiffness. Second, we design and fabricate an actively morphing drone wing enabled by this smart composite, which is used as smart joints in the drone wing. Third, we explore composite pad-like structures with dynamically tunable friction achieved via subsurface stiffness modulation (SSM). We demonstrate that when these composite structures are properly integrated into soft crawling robots, the differences in friction of the two ends of these robots through SSM can be used to generate translational locomotion for untethered crawling robots. Also, we further develop a new class of smart composite based on LMPA wool sponge with tunable electrical conductivity and tunable stiffness for soft robotics applications. The implications of these studies on novel smart materials design are also discussed

Design and Development of Instrumented Remote Centre Compliance

In the field of robotics and automatic assembly tooling, it is often necessary to provide some compliance when fitting two parts together or when engaging a tool with a complementarily shaped aperture. This need arises because of the tolerances in gripping and positioning capability of a robot arm and the dimensional tolerances of the members being positioned. The use of excessive force to engage two imperfectly aligned members can lead to damage to the members or assembly tooling. A remote centre compliance (RCC) is a device that can provide a compliance center projected outward from the device. Remote compliance centers decouple lateral and angular motion. A RCC device can be used in assembly to ease the insertion force. When a project compliance center is near the insertion point of a peg-in-hole type assembly, the peg translates into the hole when it strikes the outside lead-in chamfer without rotating. This translation without rotation prevents the jamming and galling seen from compliance devices that have a compliance center far away from the insertion point. The proposed work aims at designing and developing an intelligent RCC device which helps the parts assemble even if there are misalignments of known limits and is capable of capturing useful information for the assembly process

Block 2 SRM conceptual design studies. Volume 1, Book 1: Conceptual design package

The conceptual design studies of a Block 2 Solid Rocket Motor (SRM) require the elimination of asbestos-filled insulation and was open to alternate designs, such as case changes, different propellants, modified burn rate - to improve reliability and performance. Limitations were placed on SRM changes such that the outside geometry should not impact the physical interfaces with other Space Shuttle elements and should have minimum changes to the aerodynamic and dynamic characteristics of the Space Shuttle vehicle. Previous Space Shuttle SRM experience was assessed and new design concepts combined to define a valid approach to assured flight success and economic operation of the STS. Trade studies, preliminary designs, analyses, plans, and cost estimates are documented

펙인홀 작업을 위한 다자유도 그리퍼 및 각도 에러 측정 시스템의 설계

학위논문 (박사)-- 서울대학교 대학원 공과대학 기계항공공학부, 2017. 8. 김종원.펙인홀(Peg-In-Hole) 작업은 로봇을 활용한 조립작업 중 가장 기초적인 작업이라고 할 수 있다. 조그마한 위치 에러에도 끼임 현상(Jamming 또는 Wedging)이 발생하고 이는 부품 삽입 중에 파손을 유발할 수 있기 때문에, 조립 대상물간의 위치 및 방향에 대한 정렬이 성공적인 펙인홀 작업을 위해서는 무엇보다 중요하다. 이러한 펙인홀 작업을 위해서는 지금까지 많은 연구가 진행되어 왔으며, 대상물간의 정렬 방식에 따라서 수동적 또는 능동적 방법으로 구분된다. RCC(Remote Center Compliance)로 대표되는 수동적인 정렬방법은 컴플라이언스와 대상 부품의 특정 모양을 이용하는 반면에, 능동적인 정렬방법은 비전이나 조립 시 발생하는 반력 정보를 이용하여 대상물간의 정렬을 수행한다. 수동적 정렬 방법은 특별한 측정이나 노력 없이 사용될 수 있다는 장점을 가지고 있지만, 부품의 챔버(Chamfer) 사이즈나 펙의 길이 등에 따라서 사용 가능 여부가 결정되어 적용이 제한적이다. 비전의 활용을 통한 정렬도 또한 적용이 제한적인데, 그 이유는 카메라의 설치 위치 및 주변 환경에 따른 측정 정확도의 민감성 때문이다. 본 학위 논문에서는 효과적인 펙인홀 작업을 수행하기 위하여 다자유도의 그리퍼, 각도 에러 측정기 및 측정된 힘 정보를 군집화하여 대상물간의 위치 에러를 측정할 수 있는 알고리즘이 제안되었다. 이를 위하여 하단의 주요 세가지 핵심 기능이 시스템 설계에 구현되었으며, 사각 형상의 펙인홀 작업을 통해 증명되었다. 위치 에러 보정 작업 시 미세 조정 작업을 위하여, 4 자유도를 지닌 두 개의 손가락으로 구성된 그리퍼가 설계되었으며, 손가락 끝 단에는 6축 힘 센서가 내재되어 반력 측정을 가능하게 하였다. 로봇의 손목에 설치된 힘 센서와 로봇 팔의 자유도를 사용하여 작업을 수행하는 일반적인 방법과는 달리, 설계된 다자유도 그리퍼를 활용하여 펙을 조작 가능하게 하였다. 또한, 펙의 양 측면에서 발생된 반력 정보들을 펙의 위치 정보와 함께 저장하여 위치에러 도출에 활용 가능하도록 하였다. 2 자유도의 직교 로봇과 레이저 거리 센서로 구성된 견실한 각도 측정기(Scanner)가 펙과 홀 사이간의 각도 에러 보정을 위하여 설계 및 구현되었다. 펙과 홀 사이간의 접촉 조건에 따라서 모멘트 반력의 발생 유무가 결정되는데, 힘 정보를 바탕으로 한 빠르고 신뢰성 있는 에러 추정을 위해서는 각도 에러 측정을 통한 보정을 필요로 한다. 사각형상의 펙 인 홀 작업의 경우에는, 펙과 홀 사이간의 엣지 및 지지 면의 수에 따라서 총 5가지의 경우로 접촉 조건이 분류가 되는데, 모멘트는 그 중에서 한가지의 경우에만 발생하게 된다. 각도 에러 보정을 통하여, 접촉 조건은 2가지로 줄어들게 되며, 이를 통하여 에러 보정 시간을 줄이는 것이 가능하다. 펙과 홀 사이간의 위치 에러를 추출하기 위하여, 모멘트 반력 정보와 펙의 위치 정보로 구성된 데이터 세트에 군집화 알고리즘을 적용하였다. 각도 에러 보정 후에도, 모멘트가 발생하지 않는 경우가 남게 되며 이러한 혼합된 데이터 세트에서도 위치 에러를 추출할 수 있는 인공지능을 필요로 한다. 이를 위하여, 기계 학습에서 사용되는 두 가지의 대표적인 알고리즘, K 평균 알고리즘과 가우시안 혼합 모델 알고리즘을 다양한 측정 데이터 세트들에 적용하였다. 에러 추출 시 알고리즘의 정확도와 견실함을 확인 하기 위하여 같은 조건에서 측정되거나 다른 속도에서 측정된 세 개의 데이터 세트가 위치 에러 추출을 위하여 사용되었다. K 평균 알고리즘의 경우, 추출된 위치 에러의 정확도와 각각의 데이터 세트에서 추출된 위치 에러 값들의 편차는 각각 0.29mm, 0.14mm 이내이지만, 가우시안 혼합 모델 알고리즘의 경우에는 각각 0.44mm, 0.43mm를 보이고 있다. K 평균 알고리즘은 위치 에러 추출에서 안정적인 정확도와 견실함을 가지며, 가우시안 혼합 모델 알고리즘은 위하여 제한조건을 지닌 파라미터 사용을 필요로 하는 것을 확인할 수 있다. 센서로부터의 정보에 의지하지 않고, 긴 나선형 궤적만을 이용하여 에러 보정을 수행하는 블라인드 서치(Blind Search)와 비교할 때, 제안된 측정기와 위치 추출 알고리즘은 짧고 편차가 없는 에러 보정 시간의 장점을 가지고 있다. 주어진 검색 영역을 수직 수평으로 움직이는 짧은 XY 궤적을 사용하여 에러 보정 시간을 단축 가능하게 하고, 각도 에러 보정을 통하여 접촉 조건 경우의 수를 줄이면서 에러 보정을 위한 시간에 편차가 없도록 하였다.Peg-In-Hole is the one of basic tasks for robotic assembly. For successful Peg-In-Hole, the position and orientation alignment between mating parts is very important because small error can induce jamming and wedging which generates excessive force leading to damages on mating parts during insertion. A lot of researches for Peg-In-Hole task have been underway and it can be categorized into passive and active approaches. The passive approach represented by Remote Center Compliance uses the compliance and shape of mating parts for alignment, whereas the active approach uses measurement from vision, force or both of them. Passive approach has strength in which alignment can be done passively without any other measurements but applications are limited because it depends on the shape of mating parts like chamfer size and length of peg. Utilization of vision is also limited because of sensitivity in accuracy which is affected significantly by camera location and surrounding environment. In this dissertation, a dexterous gripper with an angular error measuring instrument and reliable position error estimation algorithm by clustering the force dataset is proposed for Peg-In-Hole task. Three main key features stated below are implemented in the system design and tested with square Peg-In-Hole experiments. The dexterous gripper which consists of 4 DOF(Degree Of Freedom) two fingers embedded with 6 axis force sensors at the fingertip is designed for micro manipulation during error recovery. Unlike the usual method in which force sensor is mounted on the robot wrist and peg is manipulated by robot arm, the designed dexterous gripper is used for both of grasping and manipulating peg. Reaction force generated on both side of peg is also measured at fingertip and recorded with peg position for error estimation. Robust angle measuring instrument, Scanner, consisted of 2DOF manipulator and laser distance sensor is also designed and implemented for detecting the angular error between peg and hole. Depending on the contact condition, its decided whether moment is generated or not, thus angular error compensation is necessary for fast and reliable error estimation based on the force data. In case of square Peg-In-Hole, the contact condition can be classified into 5 cases depending on the number of edge and supporting area between peg and hole and moment is generated in only one case. With the angular error compensation, the number of contact condition can be diminished to 2 cases thus shortened recovery time can be accomplished. To extract the position error between peg and hole, error estimation with clustering algorithm is applied to the measured dataset of moment and peg position. Even after angular error compensation, there still exists the condition which generates no reaction moment, thus artificial intelligence which can extract the position error among mixed dataset is required. Two representative algorithms, K means algorithms and Gaussian Mixture Model algorithm, commonly used in machine learning for clustering dataset are applied to various datasets constructed with position and moment for estimating position error. Two datasets, one constructed with the three datasets measured at same condition and the other constructed with three datasets measured with different velocity are used to check accuracy and robustness in error estimation from both of algorithm. The accuracy of estimated position error and deviation among estimated error in each dataset from K means algorithm is within 0.29mm and 0.14mm whereas both of that from Gaussian Mixture Model algorithm is within 0.44mm and 0.43mm. K means algorithm shows stable accuracy and robustness on position error estimation whereas the Gaussian Mixture Model algorithm needs to use constrained parameter for both of them. Comparing with blind search which uses no information from sensors and long spiral trajectory for error recovery, the proposed measurement system and algorithms have advantages in terms of recovery time and no variation of it. Short XY trajectory which moves horizontally and vertically in given search area can be used and error recovery time have no variation regardless of position error by diminishing the number of contact conditions through angular error compensation.Chapter 1. Introduction 1 1.1. Robotic Assembly and Peg-In-Hole Task 1 1.2. Previous Research Works 2 1.2.1. Passive approaches 3 1.2.2. Active approaches 5 1.3. Purpose and Contribution of Research 9 Chapter 2. Contact Condition Analysis 12 2.1. Classification of Contact Condition 12 2.1.1. Connected Component Labeling 12 2.1.2. Binary image generation procedure 13 2.1.3. Analysis results for contact condition 14 2.2. Force and Moment depending on Contact Condition 17 Chapter 3. Design Synthesis of Gripper and Scanner 21 3.1. Overall Design Overview 21 3.2. Design and Mechanism of Finger 23 3.2.1. Advantages of parallel mechanism 23 3.2.2. Mechanism description of finger 28 3.2.3. Kinematics of finger 31 3.3 Design and Mechanism of Scanner 33 3.3.1. Mechanism description 33 3.3.2. FEM analysis for deflection compensation 34 Chapter 4. Error Recovery Algorithms 40 4.1. Clustering for Error Estimation 40 4.1.1. K means algorithm 41 4.1.2. Gaussian Mixture Model algorithm 42 4.2. Procedure for Error Recovery 44 4.3. Comparison of Error Recovery Algorithms 45 4.3.1. Comparison of trajectory in blind and XY search 45 4.3.2. Comparison of trajectory for position error recovery 46 4.3.3. Comparison of trajectory for angular error recovery 49 4.3.4. Comparison of variation in recovery time 50 Chapter 5. Experimental Results 52 5.1. Angular Error Measurement of Scanner 52 5.1.1. Verification of scanner accuracy and repeatability 52 5.1.2. Measurement and alignment of angular error 56 5.2. Reaction Moment Measurement at Fingertip 58 5.2.1. Measurement of moment data 58 5.2.2. Description of measurement condition 59 5.2.3. Clustering results from K means algorithm 61 5.2.4. Clustering results from Gaussian Mixture Model Algorithm 64 5.2.5 Comparison of clustering result 69 Chapter 6. Conclusion 71 Bibliography 74 Abstract in Korean 78Docto

Human-Machine Interfaces using Distributed Sensing and Stimulation Systems

As the technology moves towards more natural human-machine interfaces (e.g. bionic limbs, teleoperation, virtual reality), it is necessary to develop a sensory feedback system in order to foster embodiment and achieve better immersion in the control system. Contemporary feedback interfaces presented in research use few sensors and stimulation units to feedback at most two discrete feedback variables (e.g. grasping force and aperture), whereas the human sense of touch relies on a distributed network of mechanoreceptors providing a wide bandwidth of information. To provide this type of feedback, it is necessary to develop a distributed sensing system that could extract a wide range of information during the interaction between the robot and the environment. In addition, a distributed feedback interface is needed to deliver such information to the user. This thesis proposes the development of a distributed sensing system (e-skin) to acquire tactile sensation, a first integration of distributed sensing system on a robotic hand, the development of a sensory feedback system that compromises the distributed sensing system and a distributed stimulation system, and finally the implementation of deep learning methods for the classification of tactile data. It\u2019s core focus addresses the development and testing of a sensory feedback system, based on the latest distributed sensing and stimulation techniques. To this end, the thesis is comprised of two introductory chapters that describe the state of art in the field, the objectives, and the used methodology and contributions; as well as six studies that tackled the development of human-machine interfaces

Design of a small fast steering mirror for airborne and aerospace applications

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2008.Includes bibliographical references (p. 177-181).This thesis presents the analysis and design of a small advanced fast steering mirror (sAFSM) for airborne and aerospace platforms. The sAFSM provides feedback-controlled articulation of two rotational axes for precision optical pointing. The design, useful for both disturbance rejection and high-speed scanning applications, incorporates a flux steering actuator with a ring core magnetic configuration. The novel magnetic concept enables a dramatic size reduction compared with heritage systems. The moving armature is supported with a combination of elastomer sheets and active position control. Local angular and mirror-normal displacement is sensed with integrated capacitive sensors. Analysis content includes specification of performance requirements based on a realistic deep-space laser communication mission, magnetic equivalent circuit and three-dimensional magnetostatic finite element analysis of the actuator, and a 3D structural optimization of the moving armature modal frequencies. The resulting design is one iteration removed from a flight -ready model. The sAFSM hardware is in fabrication, and anticipated performance exceeds 10 krad/s2 angular acceleration, 10 mrad range, and 9 kHz closed-loop bandwidth.by Michael Thomas Boulet.S.M

Advances of Italian Machine Design

This 2028 Special Issue presents recent developments and achievements in the field of Mechanism and Machine Science coming from the Italian community with international collaborations and ranging from theoretical contributions to experimental and practical applications. It contains selected contributions that were accepted for presentation at the Second International Conference of IFToMM Italy, IFIT2018, that has been held in Cassino on 29 and 30 November 2018. This IFIT conference is the second event of a series that was established in 2016 by IFToMM Italy in Vicenza. IFIT was established to bring together researchers, industry professionals and students, from the Italian and the international community in an intimate, collegial and stimulating environment

New designs for bioinspired microstructures with adhesion to rough surfaces

Adhesion to substrates with surface roughness is a research field with many unsolved questions. A more thorough understanding of the underlying principles is important to develop new technologies with potential implications for instance in robotics, industrial automatization and wearable interfaces. Nature is a vast source of inspiration as animals have mastered climbing on various surfaces at high speed with several attachment and detachment events in a short time. In this work, new designs for dry adhesives inspired by natural blueprints are presented. Different strategies were explored to understand and tune adhesion on a range of substrates from smooth glass to polymers with skin-like roughness. Both the material properties and the geometry of the dry adhesives were utilized to improve adhesion strength. Three concepts are presented in this work: (i) composite structures with tunable interface, (ii) soft pressure sensitive adhesive layers, and (iii) funnel-shaped microstructures. This thesis aims for better understanding of the adhesion behavior as a function of several important factors including hold time, substrate material and roughness. The new concepts for bioinspired structures investigated in the present thesis will contribute to the development of performant, reversible adhesives for a variety of applications where surface roughness is involved.Adhäsion an rauen Oberflächen stellt immer noch ein Forschungsfeld mit vielen ungelösten Problemen dar. Um neue Technologien mit Bedeutung für beispielsweise die Robotik, industrielle Automatisierung und körpernahe Sensorik zu entwickeln, bedarf es eines tieferen Verständnisses der zugrunde liegenden Prinzipien. Hier stellt die Natur eine vielfältige Inspirationsquelle dar, da bestimmte Lebewesen in der Lage sind, auf unterschiedlichsten Untergründen zu haften. Im Rahmen dieser Arbeit werden der Natur nachempfundene Modelle und Lösungen zur Haftung vorgestellt. Zum Verständnis der Haftungsmechanismen und zur Optimierung der Hafteigenschaften auf einer Bandbreite von Substraten, von glattem Glas bis hin zu rauen, hautähnlichen Polymeroberflächen, wurden unterschiedliche Herangehensweisen untersucht. Zur Erhöhung der Haftkraft kamen sowohl Variationen in den verwendeten Materialien, als auch in der Geometrie der Haftstrukturen zum Einsatz. Drei Konzepte werden in dieser Arbeit vorgestellt: (i) Kompositstrukturen mit variablen Grenzflächen; (ii) weiche, drucksensitive Schichten und (iii) trichterförmige Mikrostrukturen. Es wird ein besseres Verständnis des Adhäsionsverhaltens in direktem Zusammenhang mit verschiedenen Struktur-, Substrat- und Messparametern angestrebt. Die in dieser Arbeit vorgestellten, neuen Konzepte für bioinspirierte Strukturen sollen zur Entwicklung performanter, reversibler Haftverbindungen für einen breiten Anwendungsbereich auf rauen Oberflächen beitragen.L’adhésion sur des surfaces rugueuses offre beaucoup de questions ouvertes aux chercheurs. Pour développer des technologies pionnières dans les domaines comme la robotique, automatisation industrielle et les capteurs portables, une connaissance plus détaillée des mécanismes gouvernant ce phénomène est nécessaire. La nature est une source d’inspiration vaste avec une multitude d’animaux possédant la capacité d’escalader diverses surfaces à grande vitesse. Cette thèse présente de nouveaux designs d’adhésifs secs inspirés par la nature. Différentes stratégies ont été explorées afin de comprendre et modifier l’adhésion sur des surfaces variées comme le verre poli ou des polymères avec une texture de surface ressemblant celle de la peau. Les propriétés des matériaux et la géométrie des structures ont été utilisées comme paramètres pour maximiser l’adhésion. Cette thèse comprend trois parties : (i) des structures composites avec interface variable, (ii) des films mous sensibles à la pression, et (iii) des structures en forme d’entonnoir. Les paramètres étudiés englobent entre outre le temps d’attente, le matériau du substrat et sa rugosité. Tous les concepts peuvent être raffinés et optimisé envers certaines applications. Les nouveaux concepts de structures inspirés par la nature présentés ci-dedans ont pour but de contribuer au développement d’adhésifs performants et réversibles pour une variété d’applications pour lesquelles la rugosité joue un important rôle.The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 340929 awarded to Eduard Arzt and by the German Research Foundation (Deutsche Forschungsgemeinschaft) through the grant n. HE 7498/1-1 awarded to René Hensel