In silico case studies of compliant robots: AMARSI deliverable 3.3

In the deliverable 3.2 we presented how the morphological computing ap- proach can significantly facilitate the control strategy in several scenarios, e.g. quadruped locomotion, bipedal locomotion and reaching. In particular, the Kitty experimental platform is an example of the use of morphological computation to allow quadruped locomotion. In this deliverable we continue with the simulation studies on the application of the different morphological computation strategies to control a robotic system

A Bio-inspired architecture for adaptive quadruped locomotion over irregular terrain

Tese de doutoramento Programa Doutoral em Engenharia Electrónica e de ComputadoresThis thesis presents a tentative advancement on walking control of small quadruped and humanoid position controlled robots, addressing the problem of walk generation by combining dynamical systems approach to motor control, insights from neuroethology research on vertebrate motor control and computational neuroscience. Legged locomotion is a complex dynamical process, despite the seemingly easy and natural behavior of the constantly present proficiency of legged animals. Research on locomotion and motor control in vertebrate animals from the last decades has brought to the attention of roboticists, the potential of the nature’s solutions to robot applications. Recent knowledge on the organization of complex motor generation and on mechanics and dynamics of locomotion has been successfully exploited to pursue agile robot locomotion. The work presented on this manuscript is part of an effort on the pursuit in devising a general, model free solution, for the generation of robust and adaptable walking behaviors. It strives to devise a practical solution applicable to real robots, such as the Sony’s quadruped AIBO and Robotis’ DARwIn- OP humanoid. The discussed solutions are inspired on the functional description of the vertebrate neural systems, especially on the concept of Central Pattern Generators (CPGs), their structure and organization, components and sensorimotor interactions. They use a dynamical systems approach for the implementation of the controller, especially on the use of nonlinear oscillators and exploitation of their properties. The main topics of this thesis are divided into three parts. The first part concerns quadruped locomotion, extending a previous CPG solution using nonlinear oscillators, and discussing an organization on three hierarchical levels of abstraction, sharing the purpose and knowledge of other works. It proposes a CPG solution which generates the walking motion for the whole-leg, which is then organized in a network for the production of quadrupedal gaits. The devised solution is able to produce goal-oriented locomotion and navigation as directed through highlevel commands from local planning methods. In this part, active balance on a standing quadruped is also addressed, proposing a method based on dynamical systems approach, exploring the integration of parallel postural mechanisms from several sensory modalities. The solutions are all successfully tested on the quadruped AIBO robot. In the second part, is addressed bipedal walking for humanoid robots. A CPG solution for biped walking based on the concept of motion primitives is proposed, loosely based on the idea of synergistic organization of vertebrate motor control. A set of motion primitives is shown to produce the basis of simple biped walking, and generalizable to goal-oriented walking. Using the proposed CPG, the inclusion of feedback mechanisms is investigated, for modulation and adaptation of walking, through phase transition control according to foot load information. The proposed solution is validated on the humanoid DARwIn-OP, and its application is evaluated within a whole-body control framework. The third part sidesteps a little from the other two topics. It discusses the CPG as having an alternative role to direct motor generation in locomotion, serving instead as a processor of sensory information for a feedback based motor generation. In this work a reflex based walking controller is devised for the compliant quadruped Oncilla robot, to serve as purely feedback based walking generation. The capabilities of the reflex network are shown in simulations, followed by a brief discussion on its limitations, and how they could be improved by the inclusion of a CPG.Esta tese apresenta uma tentativa de avanço no controlo de locomoção para pequenos robôs quadrúpedes e bipedes controlados por posição, endereçando o problema de geração motora através da combinação da abordagem de sistemas dinâmicos para o controlo motor, e perspectivas de investigação neuroetologia no controlo motor vertebrado e neurociência computacional. Andar é um processo dinâmico e complexo, apesar de parecer um comportamento fácil e natural devido à presença constante de animais proficientes em locomoção terrestre. Investigação na área da locomoção e controlo motor em animais vertebrados nas últimas decadas, trouxe à atenção dos roboticistas o potencial das soluções encontradas pela natureza aplicadas a aplicações robóticas. Conhecimento recente relativo à geração de comportamentos motores complexos e da mecânica da locomoção tem sido explorada com sucesso na procura de locomoção ágil na robótica. O trabalho apresentado neste documento é parte de um esforço no desenho de uma solução geral, e independente de modelos, para a geração robusta e adaptável de comportamentos locomotores. O foco é desenhar uma solução prática, aplicável a robôs reais, tal como o quadrúpede Sony AIBO e o humanóide DARwIn-OP. As soluções discutidas são inspiradas na descrição funcional do sistema nervoso vertebrado, especialmente no conceito de Central Pattern Generators (CPGs), a sua estrutura e organização, componentes e interacção sensorimotora. Estas soluções são implementadas usando uma abordagem em sistemas dinâmicos, focandos o uso de osciladores não lineares e a explorando as suas propriedades. Os tópicos principais desta tese estão divididos em três partes. A primeira parte explora o tema de locomoção quadrúpede, expandindo soluções prévias de CPGs usando osciladores não lineares, e discutindo uma organização em três níveis de abstracção, partilhando as ideias de outros trabalhos. Propõe uma solução de CPG que gera os movimentos locomotores para uma perna, que é depois organizado numa rede, para a produção de marcha quadrúpede. A solução concebida é capaz de produzir locomoção e navegação, comandada através de comandos de alto nível, produzidos por métodos de planeamento local. Nesta parte também endereçado o problema da manutenção do equilíbrio num robô quadrúpede parado, propondo um método baseado na abordagem em sistemas dinâmicos, explorando a integração de mecanismos posturais em paralelo, provenientes de várias modalidades sensoriais. As soluções são todas testadas com sucesso no robô quadrupede AIBO. Na segunda parte é endereçado o problema de locomoção bípede. É proposto um CPG baseado no conceito de motion primitives, baseadas na ideia de uma organização sinergética do controlo motor vertebrado. Um conjunto de motion primitives é usado para produzir a base de uma locomoção bípede simples e generalizável para navegação. Esta proposta de CPG é usada para de seguida se investigar a inclusão de mecanismos de feedback para modulação e adaptação da marcha, através do controlo de transições entre fases, de acordo com a informação de carga dos pés. A solução proposta é validada no robô humanóide DARwIn-OP, e a sua aplicação no contexto do framework de whole-body control é também avaliada. A terceira parte desvia um pouco dos outros dois tópicos. Discute o CPG como tendo um papel alternativo ao controlo motor directo, servindo em vez como um processador de informação sensorial para um mecanismo de locomoção puramente em feedback. Neste trabalho é desenhado um controlador baseado em reflexos para a geração da marcha de um quadrúpede compliant. As suas capacidades são demonstradas em simulação, seguidas por uma breve discussão nas suas limitações, e como estas podem ser ultrapassadas pela inclusão de um CPG.The presented work was possible thanks to the support by the Portuguese Science and Technology Foundation through the PhD grant SFRH/BD/62047/2009

Controlling swimming and crawling in a fish robot using a central pattern generator

Online trajectory generation for robots with multiple degrees of freedom is still a difficult and unsolved problem, in particular for non-steady state locomotion, that is, when the robot has to move in a complex environment with continuous variations of the speed, direction, and type of locomotor behavior. In this article we address the problem of controlling the non-steady state swimming and crawling of a novel fish robot. For this, we have designed a control architecture based on a central pattern generator (CPG) implemented as a system of coupled nonlinear oscillators. The CPG, like its biological counterpart, can produce coordinated patterns of rhythmic activity while being modulated by simple control parameters. To test our controller, we designed BoxyBot, a simple fish robot with three actuated fins capable of swimming in water and crawling on firm ground. Using the CPG model, the robot is capable of performing and switching between a variety of different locomotor behaviors such as swimming forwards, swimming backwards, turning, rolling, moving upwards/downwards, and crawling. These behaviors are triggered and modulated by sensory input provided by light, water, and touch sensors. Results are presented demonstrating the agility of the robot and interesting properties of a CPG-based control approach such as stability of the rhythmic patterns due to limit cycle behavior, and the production of smooth trajectories despite abrupt changes of control parameters. The robot is currently used in a temporary 20-month long exhibition at the EPFL. We present the hardware setup that was designed for the exhibition, and the type of interactions with the control system that allow visitors to influence the behavior of the robot. The exhibition is useful to test the robustness of the robot for long term use, and to demonstrate the suitability of the CPG-based approach for interactive control with a human in the loop. This article is an extended version of an article presented at BioRob2006 the first IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

Design and control of amphibious robots with multiple degrees of freedom

This thesis presents the design and realization of two generations of robot elements that can be assembled together to construct amphibious mobile robots. These elements, designed to be individually waterproof and having their own battery, motor controller, and motor, have been used to actually construct a snake, a boxfish and a salamander robot. Central pattern generator (CPG) models inspired from those found in vertebrates have been used for online trajectory generation on these robots and implemented on their onboard locomotion controllers. CPGs proved to be an interesting way of controlling complex robots, providing a simple interface which hides the complexity of the robot to the end user. Online learning algorithms that can be used to dynamically adapt the locomotion parameters to the environment have been implemented. Finally, this work also shows how robotics can be a useful tool to verify biological hypotheses. For instance, the salamander robot has been used to test a model of CPG for salamander locomotion

Locomoção bípede adaptativa a partir de uma única demonstração usando primitivas de movimento

Doutoramento em Engenharia EletrotécnicaEste trabalho aborda o problema de capacidade de imitação da locomoção humana através da utilização de trajetórias de baixo nível codificadas com primitivas de movimento e utilizá-las para depois generalizar para novas situações, partindo apenas de uma demonstração única. Assim, nesta linha de pensamento, os principais objetivos deste trabalho são dois: o primeiro é analisar, extrair e codificar demonstrações efetuadas por um humano, obtidas por um sistema de captura de movimento de forma a modelar tarefas de locomoção bípede. Contudo, esta transferência não está limitada à simples reprodução desses movimentos, requerendo uma evolução das capacidades para adaptação a novas situações, assim como lidar com perturbações inesperadas. Assim, o segundo objetivo é o desenvolvimento e avaliação de uma estrutura de controlo com capacidade de modelação das ações, de tal forma que a demonstração única apreendida possa ser modificada para o robô se adaptar a diversas situações, tendo em conta a sua dinâmica e o ambiente onde está inserido. A ideia por detrás desta abordagem é resolver o problema da generalização a partir de uma demonstração única, combinando para isso duas estruturas básicas. A primeira consiste num sistema gerador de padrões baseado em primitivas de movimento utilizando sistemas dinâmicos (DS). Esta abordagem de codificação de movimentos possui propriedades desejáveis que a torna ideal para geração de trajetórias, tais como a possibilidade de modificar determinados parâmetros em tempo real, tais como a amplitude ou a frequência do ciclo do movimento e robustez a pequenas perturbações. A segunda estrutura, que está embebida na anterior, é composta por um conjunto de osciladores acoplados em fase que organizam as ações de unidades funcionais de forma coordenada. Mudanças em determinadas condições, como o instante de contacto ou impactos com o solo, levam a modelos com múltiplas fases. Assim, em vez de forçar o movimento do robô a situações pré-determinadas de forma temporal, o gerador de padrões de movimento proposto explora a transição entre diferentes fases que surgem da interação do robô com o ambiente, despoletadas por eventos sensoriais. A abordagem proposta é testada numa estrutura de simulação dinâmica, sendo que várias experiências são efetuadas para avaliar os métodos e o desempenho dos mesmos.This work addresses the problem of learning to imitate human locomotion actions through low-level trajectories encoded with motion primitives and generalizing them to new situations from a single demonstration. In this line of thought, the main objectives of this work are twofold: The first is to analyze, extract and encode human demonstrations taken from motion capture data in order to model biped locomotion tasks. However, transferring motion skills from humans to robots is not limited to the simple reproduction, but requires the evaluation of their ability to adapt to new situations, as well as to deal with unexpected disturbances. Therefore, the second objective is to develop and evaluate a control framework for action shaping such that the single-demonstration can be modulated to varying situations, taking into account the dynamics of the robot and its environment. The idea behind the approach is to address the problem of generalization from a single-demonstration by combining two basic structures. The first structure is a pattern generator system consisting of movement primitives learned and modelled by dynamical systems (DS). This encoding approach possesses desirable properties that make them well-suited for trajectory generation, namely the possibility to change parameters online such as the amplitude and the frequency of the limit cycle and the intrinsic robustness against small perturbations. The second structure, which is embedded in the previous one, consists of coupled phase oscillators that organize actions into functional coordinated units. The changing contact conditions plus the associated impacts with the ground lead to models with multiple phases. Instead of forcing the robot’s motion into a predefined fixed timing, the proposed pattern generator explores transition between phases that emerge from the interaction of the robot system with the environment, triggered by sensor-driven events. The proposed approach is tested in a dynamics simulation framework and several experiments are conducted to validate the methods and to assess the performance of a humanoid robot

Pattern Generation for Rough Terrain Locomotion with Quadrupedal Robots:Morphed Oscillators & Sensory Feedback

Animals are able to locomote on rough terrain without any apparent difficulty, but this does not mean that the locomotor system is simple. The locomotor system is actually a complex multi-input multi-output closed-loop control system. This thesis is dedicated to the design of controllers for rough terrain locomotion, for animal-like quadrupedal robots. We choose the problem of blind rough terrain locomotion as the target of experiments. Blind rough terrain locomotion requires continuous and momentary corrections of leg movements and body posture, and provides a proper testbed to observe the interaction of different mod- ules involved in locomotion control. As for the specific case of this thesis, we have to design rough terrain locomotion controllers that do not depend on the torque-control capability, have limited sensing, and have to be computationally light, all due to the properties of the robotics platform that we use. We propose that a robust locomotion controller, taking into account the aforementioned constraints, is constructed from at least three modules: 1) pattern generators providing the nominal patterns of locomotion; 2) A posture controller continuously adjusting the attitude of the body and keeping the robot upright; and 3) quick reflexes to react to unwanted momentary events like stumbling or an external force impulse. We introduce the framework of morphed oscillators to systematize the design of pattern gen- erators realized as coupled nonlinear oscillators. Morphed oscillators are nonlinear oscillators that can encode arbitrary limit cycle shapes and simultaneously have infinitely large basins of attraction. More importantly, they provide dynamical systems that can assume the role of feedforward locomotion controllers known as Central Pattern Generators (CPGs), and accept discontinuous sensory feedback without the risk of producing discontinuous output. On top of the CPG module, we add a kinematic model-based posture controller inspired by virtual model control (VMC), to control the body attitude. Virtual model control produces forces, and through the application of the Jacobian transpose method, generates torques which are added to the CPG torques. However, because our robots do not have a torque- control capability, we adapt the posture controller by producing task-space velocities instead of forces, thus generating joint-space velocity feedback signals. Since the CPG model used for locomotion generates joint velocities and accepts feedback without the fear of instability or discontinuity, the posture control feedback is easily integrated into the CPG dynamics. More- over, we introduce feedback signals for adjusting the posture by shifting the trunk positions, which directly update the limit cycle shape of the morphed oscillator nodes of the CPG. Reflexes are added, with minimal complexity, to react to momentary events. We implement simple impulse-based feedback mechanisms inspired by animals and successful rough terrain robots to 1) flex the leg if the robot is stumbling (stumbling correction reflex); 2) extend the leg if an expected contact is missing (leg extension reflex); or 3) initiate a lateral stepping sequence in response to a lateral external perturbation. CPG, posture controller, and reflexes are put together in a modular control architecture alongside additional modules that estimate inclination, control speed and direction, maintain timing of feedback signals, etc. [...