Climbing and Walking Robots

With the advancement of technology, new exciting approaches enable us to render mobile robotic systems more versatile, robust and cost-efficient. Some researchers combine climbing and walking techniques with a modular approach, a reconfigurable approach, or a swarm approach to realize novel prototypes as flexible mobile robotic platforms featuring all necessary locomotion capabilities. The purpose of this book is to provide an overview of the latest wide-range achievements in climbing and walking robotic technology to researchers, scientists, and engineers throughout the world. Different aspects including control simulation, locomotion realization, methodology, and system integration are presented from the scientific and from the technical point of view. This book consists of two main parts, one dealing with walking robots, the second with climbing robots. The content is also grouped by theoretical research and applicative realization. Every chapter offers a considerable amount of interesting and useful information

MUSME 2011 4 th International Symposium on Multibody Systems and Mechatronics

El libro de actas recoge las aportaciones de los autores a través de los correspondientes artículos a la Dinámica de Sistemas Multicuerpo y la Mecatrónica (Musme). Estas disciplinas se han convertido en una importante herramienta para diseñar máquinas, analizar prototipos virtuales y realizar análisis CAD sobre complejos sistemas mecánicos articulados multicuerpo. La dinámica de sistemas multicuerpo comprende un gran número de aspectos que incluyen la mecánica, dinámica estructural, matemáticas aplicadas, métodos de control, ciencia de los ordenadores y mecatrónica. Los artículos recogidos en el libro de actas están relacionados con alguno de los siguientes tópicos del congreso: Análisis y síntesis de mecanismos ; Diseño de algoritmos para sistemas mecatrónicos ; Procedimientos de simulación y resultados ; Prototipos y rendimiento ; Robots y micromáquinas ; Validaciones experimentales ; Teoría de simulación mecatrónica ; Sistemas mecatrónicos ; Control de sistemas mecatrónicosUniversitat Politècnica de València (2011). MUSME 2011 4 th International Symposium on Multibody Systems and Mechatronics. Editorial Universitat Politècnica de València. http://hdl.handle.net/10251/13224Archivo delegad

Using evolutionary artificial neural networks to design hierarchical animat nervous systems.

The research presented in this thesis examines the area of control systems for robots or animats (animal-like robots). Existing systems have problems in that they require a great deal of manual design or are limited to performing jobs of a single type. For these reasons, a better solution is desired. The system studied here is an Artificial Nervous System (ANS) which is biologically inspired; it is arranged as a hierarchy of layers containing modules operating in parallel. The ANS model has been developed to be flexible, scalable, extensible and modular. The ANS can be implemented using any suitable technology, for many different environments. The implementation focused on the two lowest layers (the reflex and action layers) of the ANS, which are concerned with control and rhythmic movement. Both layers were realised as Artificial Neural Networks (ANN) which were created using Evolutionary Algorithms (EAs). The task of the reflex layer was to control the position of an actuator (such as linear actuators or D.C. motors). The action layer performed the task of Central Pattern Generators (CPG), which produce rhythmic patterns of activity. In particular, different biped and quadruped gait patterns were created. An original neural model was specifically developed for assisting in the creation of these time-based patterns. It is shown in the thesis that Artificial Reflexes and CPGs can be configured successfully using this technique. The Artificial Reflexes were better at generalising across different actuators, without changes, than traditional controllers. Gaits such as pace, trot, gallop and pronk were successfully created using the CPGs. Experiments were conducted to determine whether modularity in the networks had an impact. It has been demonstrated that the degree of modularization in the network influences its evolvability, with more modular networks evolving more efficiently

Open motion control architecture for humanoid robots

This Ph.D. thesis contributes to the development of control architecture for robots. It provides a complex study of a control systems design and makes a proposal for generalized open motion control architecture for humanoid robots. Generally speaking, the development of humanoid robots is a very complex engineering and scientific task that requires new approaches in mechanical design, electronics, software engineering and control. First of all, taking into account all these considerations, this thesis tries to answer the question of why we need the development of such robots. Further, it provides a study of the evolution of humanoid robots, as well as an analysis of modern trends. A complex study of motion, that for humanoid robots, means first of all the biped locomotion is addressed. Requirements for the design of open motion control architecture are posed. This work stresses the motion control algorithms for humanoid robots. The implementation of only servo control for some types of robots (especially for walking systems) is not sufficient. Even having stable motion pattern and well tuned joint control, a humanoid robot can fall down while walking. Therefore, these robots need the implementation of another, upper control loop which will provide the stabilization of their motion. This Ph.D. thesis proposes the study of a joint motion control problem and a new solution to walking stability problem for humanoids. A new original walking stabilization controller based on decoupled double inverted pendulum dynamical model is developed. This Ph.D. thesis proposes novel motion control software and hardware architecture for humanoid robots. The main advantage of this architecture is that it was designed by an open systems approach allowing the development of high-quality humanoid robotics platforms that are technologically up-to-date. The Rh-1 prototype of the humanoid robot was constructed and used as a test platform for implementing the concepts described in this Ph.D. thesis. Also, the implementation of walking stabilization control algorithms was made with OpenHRP platform and HRP-2 humanoid robot. The simulations and walking experiments showed favourable results not only in forward walking but also in turning and backwards walking gaits. It proved the applicability and reliability of designed open motion control architecture for humanoid robots. Finally, it should be noted that this Ph.D. thesis considers the motion control system of a humanoid robot as a whole, stresses the entire concept-design-implementation chain and develops basic guidelines for the design of open motion control architecture that can be easily implemented in other biped platforms

The Mechanics and Control of Undulatory Robotic Locomotion

In this dissertation, we examine a formulation of problems of undulatory robotic locomotion within the context of mechanical systems with nonholonomic constraints and symmetries. Using tools from geometric mechanics, we study the underlying structure found in general problems of locomotion. In doing so, we decompose locomotion into two basic components: internal shape changes and net changes in position and orientation. This decomposition has a natural mathematical interpretation in which the relationship between shape changes and locomotion can be described using a connection on a trivial principal fiber bundle. We begin by reviewing the processes of Lagrangian reduction and reconstruction for unconstrained mechanical systems with Lie group symmetries, and present new formulations of this process which are easily adapted to accommodate external constraints. Additionally, important physical quantities such as the mechanical connection and reduced mass-inertia matrix can be trivially determined using this formulation. The presence of symmetries then allows us to reduce the necessary calculations to simple matrix manipulations. The addition of constraints significantly complicates the reduction process; however, we show that for invariant constraints, a meaningful connection can be synthesized by defining a generalized momentum representing the momentum of the system in directions allowed by the constraints. We then prove that the generalized momentum and its governing equation possess certain invariances which allows for a reduction process similar to that found in the unconstrained case. The form of the reduced equations highlights the synthesized connection and the matrix quantities used to calculate these equations. The use of connections naturally leads to methods for testing controllability and aids in developing intuition regarding the generation of various locomotive gaits. We present accessibility and controllability tests based on taking derivatives of the connection, and relate these tests to taking Lie brackets of the input vector fields. The theory is illustrated using several examples, in particular the examples of the snakeboard and Hirose snake robot. We interpret each of these examples in light of the theory developed in this thesis, and examine the generation of locomotive gaits using sinusoidal inputs and their relationship to the controllability tests based on Lie brackets

분산된 로터로 구동되는 비행 스켈레톤 시스템의 디자인 상태추정 및 제어

학위논문(박사)--서울대학교 대학원 :공과대학 기계항공공학부,2020. 2. 이동준.In this thesis, we present key theoretical components for realizing flying aerial skeleton system called LASDRA (large-size aerial skeleton with distributed rotor actuation). Aerial skeletons are articulated aerial robots actuated by distributed rotors including both ground connected type and flying type. These systems have recently attracted interest and are being actively researched in several research groups, with the expectation of applying those for aerial manipulation in distant/narrow places, or for the performance with entertaining purpose such as drone shows. Among the aerial skeleton systems, LASDRA system, proposed by our group has some significant advantages over the other skeleton systems that it is capable of free SE(3) motion by omni-directional wrench generation of each link, and also the system can be operated with wide range of configuration because of the 3DOF (degrees of freedom) inter-link rotation enabled by cable connection among the link modules. To realize this LASDRA system, following three components are crucial: 1) a link module that can produce omni-directional force and torque and enough feasible wrench space; 2) pose and posture estimation algorithm for an articulated system with high degrees of freedom; and 3) a motion generation framework that can provide seemingly natural motion while being able to generate desired motion (e.g., linear and angular velocity) for the entire body. The main contributions of this thesis is theoretically developing these three components, and verifying these through outdoor flight experiment with a real LASDRA system. First of all, a link module for the LASDRA system is designed with proposed constrained optimization problem, maximizing the guaranteed feasible force and torque for any direction while also incorporating some constraints (e.g., avoiding inter-rotor air-flow interference) to directly obtain feasible solution. Also, an issue of ESC-induced (electronic speed control) singularity is first introduced in the literature which is inevitably caused by bi-directional thrust generation with sensorless actuators, and handled with a novel control allocation called selective mapping. Then for the state estimation of the entire LASDRA system, constrained Kalman filter based estimation algorithm is proposed that can provide estimation result satisfying kinematic constraint of the system, also along with a semi-distributed version of the algorithm to endow with system scalability. Lastly, CPG-based motion generation framework is presented that can generate natural biomimetic motion, and by exploiting the inverse CPG model obtained with machine learning method, it becomes possible to generate certain desired motion while still making CPG generated natural motion.본 논문에서는 비행 스켈레톤 시스템 LASDRA (large-size aerial skeleton with distributed rotor actuation) 의 구현을 위해 요구되는 핵심 기법들을 제안하며, 이를 실제 LASDRA 시스템의 실외 비행을 통해 검증한다. 제안된 기법은 1) 전방향으로 힘과 토크를 낼 수 있고 충분한 가용 렌치공간을 가진 링크 모듈, 2) 높은 자유도의 다관절구조 시스템을 위한 위치 및 자세 추정 알고리즘, 3) 자연스러운 움직임을 내는 동시에 전체 시스템이 속도, 각속도 등 원하는 움직임을 내도록 할 수 있는 모션 생성 프레임워크로 구성된다. 본 논문에서는 우선 링크 모듈의 디자인을 위해 전방향으로 보장되는 힘과 토크의 크기를 최대화하는 구속 최적화를 사용하고, 실제 적용가능한 해를 얻기 위해 몇가지 구속조건(로터 간 공기 흐름 간섭의 회피 등)을 고려한다. 또한 센서가 없는 액츄에이터로 양방향 추력을 내는 것에서 야기되는 ESC 유발 특이점 (ESC-induced singularity) 이라는 문제를 처음으로 소개하고, 이를 해결하기 위해 선택적 맵핑 (selective mapping) 이라는 기법을 제시한다. 전체 LASDRA 시스템의 상태추정을 위해 시스템의 기구학적 구속조건을 만족하는 결과를 얻을 수 있도록 구속 칼만 필터 기반의 상태추정 기법을 제시하고, 시스템 확장성을 고려하여 반 분산 (semi-distributed) 개념의 알고리즘을 함께 제시한다. 마지막으로 본 논문에서는 자연스러운 움직임의 생성을 위하여 CPG 기반의 모션 생성 프레임워크를 제안하며, 기계 학습 방법을 통해 CPG 역연산 모델을 얻음으로써 전체 시스템이 원하는 움직임을 낼 수 있도록 한다.1 Introduction 1 1.1 Motivation and Background 1 1.2 Research Problems and Approach 3 1.3 Preview of Contributions 5 2 Omni-Directional Aerial Robot 7 2.1 Introduction 7 2.2 Mechanical Design 12 2.2.1 Design Description 12 2.2.2 Wrench-Maximizing Design Optimization 13 2.3 System Modeling and Control Design 20 2.3.1 System Modeling 20 2.3.2 Pose Trajectory Tracking Control 22 2.3.3 Hybrid Pose/Wrench Control 22 2.3.4 PSPM-Based Teleoperation 24 2.4 Control Allocation with Selective Mapping 27 2.4.1 Infinity-Norm Minimization 27 2.4.2 ESC-Induced Singularity and Selective Mapping 29 2.5 Experiment 38 2.5.1 System Setup 38 2.5.2 Experiment Results 41 2.6 Conclusion 49 3 Pose and Posture Estimation of an Aerial Skeleton System 51 3.1 Introduction 51 3.2 Preliminary 53 3.3 Pose and Posture Estimation 55 3.3.1 Estimation Algorithm via SCKF 55 3.3.2 Semi-Distributed Version of Algorithm 59 3.4 Simulation 62 3.5 Experiment 65 3.5.1 System Setup 65 3.5.2 Experiment of SCKF-Based Estimation Algorithm 66 3.6 Conclusion 69 4 CPG-Based Motion Generation 71 4.1 Introduction 71 4.2 Description of Entire Framework 75 4.2.1 LASDRA System 75 4.2.2 Snake-Like Robot & Pivotboard 77 4.3 CPG Model 79 4.3.1 LASDRA System 79 4.3.2 Snake-Like Robot 80 4.3.3 Pivotboard 83 4.4 Target Pose Calculation with Expected Physics 84 4.5 Inverse Model Learning 86 4.5.1 LASDRA System 86 4.5.2 Snake-Like Robot 89 4.5.3 Pivotboard 90 4.6 CPG Parameter Adaptation 93 4.7 Simulation 94 4.7.1 LASDRA System 94 4.7.2 Snake-Like Robot & Pivotboard 97 4.8 Conclusion 101 5 Outdoor Flight Experiment of the F-LASDRA System 103 5.1 System Setup 103 5.2 Experiment Results 104 6 Conclusion 111 6.1 Summary 111 6.2 Future Works 112Docto

Robotics 2010

Without a doubt, robotics has made an incredible progress over the last decades. The vision of developing, designing and creating technical systems that help humans to achieve hard and complex tasks, has intelligently led to an incredible variety of solutions. There are barely technical fields that could exhibit more interdisciplinary interconnections like robotics. This fact is generated by highly complex challenges imposed by robotic systems, especially the requirement on intelligent and autonomous operation. This book tries to give an insight into the evolutionary process that takes place in robotics. It provides articles covering a wide range of this exciting area. The progress of technical challenges and concepts may illuminate the relationship between developments that seem to be completely different at first sight. The robotics remains an exciting scientific and engineering field. The community looks optimistically ahead and also looks forward for the future challenges and new development

Agile Bipedal Locomotion via Hierarchical Control by Incorporating Physical Principles, Learning, and Optimization

Robotic Bipedal locomotion holds the potential for efficient, robust traversal of difficult terrain. The difficulty lies in the dynamics of locomotion which complicate control and motion planning. Bipedal locomotion dynamics are dimensionally large problems, extremely nonlinear, and operate on the limits of actuator capabilities, which limit the performance of generic methods of control. This thesis presents an approach to the problem of agile legged locomotion founded on a first principles understanding of gait dynamics. This approach is built on the perspective that an understanding of locomotion is vital to the successful application of modern control and planning tools. We present 1) a ground-up analysis of legged locomotion as a dynamical phenomenon, 2) approaches that utilize dynamically meaningful reduced order models of locomotion, and 3) applications to the hardware robot Cassie via reinforcement learning

Chaotic exploration and learning of locomotor behaviours

Recent developments in the embodied approach to understanding the generation of adaptive behaviour, suggests that the design of adaptive neural circuits for rhythmic motor patterns should not be done in isolation from an appreciation, and indeed exploitation, of neural-body-environment interactions. Utilising spontaneous mutual entrainment between neural systems and physical bodies provides a useful passage to the regions of phase space which are naturally structured by the neuralbody- environmental interactions. A growing body of work has provided evidence that chaotic dynamics can be useful in allowing embodied systems to spontaneously explore potentially useful motor patterns. However, up until now there has been no general integrated neural system that allows goal-directed, online, realtime exploration and capture of motor patterns without recourse to external monitoring, evaluation or training methods. For the first time, we introduce such a system in the form of a fully dynamic neural system, exploiting intrinsic chaotic dynamics, for the exploration and learning of the possible locomotion patterns of an articulated robot of an arbitrary morphology in an unknown environment. The controller is modelled as a network of neural oscillators which are coupled only through physical embodiment, and goal directed exploration of coordinated motor patterns is achieved by a chaotic search using adaptive bifurcation. The phase space of the indirectly coupled neural-body-environment system contains multiple transient or permanent self-organised dynamics each of which is a candidate for a locomotion behaviour. The adaptive bifurcation enables the system orbit to wander through various phase-coordinated states using its intrinsic chaotic dynamics as a driving force and stabilises the system on to one of the states matching the given goal criteria. In order to improve the sustainability of useful transient patterns, sensory homeostasis has been introduced which results in an increased diversity of motor outputs, thus achieving multi-scale exploration. A rhythmic pattern discovered by this process is memorised and sustained by changing the wiring between initially disconnected oscillators using an adaptive synchronisation method. The dynamical nature of the weak coupling through physical embodiment allows this adaptive weight learning to be easily integrated, thus forming a continuous exploration-learning system. Our result shows that the novel neuro-robotic system is able to create and learn a number of emergent locomotion behaviours for a wide range of body configurations and physical environment, and can re-adapt after sustaining damage. The implications and analyses of these results for investigating the generality and limitations of the proposed system are discussed