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Ricardo Daniel Costa Campos Hexapod Locomotion Universidade do Minho Escola de Engenharia Ricardo Daniel Costa Campos Hexapod Locomotion: a Nonlinear Dynamical Systems Approach Hexapod Locomotion: Hexapod a Nonlinear Dynamical Systems Approach Ricardo Daniel Costa Campos Setembro de 2010 UMinho | 2010 Universidade do Minho Escola de Engenharia Ricardo Daniel Costa Campos Hexapod Locomotion: a Nonlinear Dynamical Systems Approach Tese de Mestrado Ciclo de Estudos Integrados Conducentes ao Grau de Mestre em Engenharia Electrónica Industrial e Computadores Trabalho efectuado sob a orientação da Professora Doutora Cristina Santos Setembro de 2010 Abstract Over recent years the technological progress has been growing interest in the study of legged robots, taking a leading role in the development and improvement of these type of machines. Walking machines have distinct advantages over wheeled robots, mainly, uneven terrains navigation, capacity to overcome obstacles as well as better balance and stability on unstructured or inclined terrains. However, the generation of robust locomotion on these articulated robots, is still a difficult problem to solve, in particular due to high number of degrees of freedom that compose a legged robot and have to be controlled. In this work we focus our research on hexapod machines using their inherent capacity of walking in a wide variety of terrains which is one of their most important features. The aims of this work are design and implement a bio-inspired controller architecture able to generate a stable and robust locomotion in hexapod robots functionally divided in three layers. The proposed architecture is able to generate different hexapodal gaits, switch between the most common gaits and correct the posture of the robot in several different situations where the robot balance is affected. Motor patterns are generated by coupled Central Pattern Generators (CPGs), formulated as nonlinear oscillators. We proposed a CPG network that enables the stable locomotion of the robot and switching between their different gaits. These patterns are modulated by a drive signal, changing the oscillators frequency, amplitude and the coupling parameters among the oscillators, proportionally to the drive signal strength. Locomotion initiation, stopping and smooth gait switching are achieved by changing the drive signal. The velocity is changed accordingly and a natural hexapod locomotion is gen- erated. In this contribution was also developed a posture controller for hexapod robots using the dynamical systems approach. Results were performed in simulation and a simulation model of the Chiara hexapod robot was developed. Results demonstrate the capability of the controller both to locomotion generation and smooth gait transition. The postural controller is also tested in different situations in which the hexapod robot is expected to maintain balance. The presented results prove its reliability and robustness. Keywords:Walking robot; locomotion; central pattern generator; dynamical systems; bio control; mobile robots; nonlinear control systems; robot dynamics; robot programming. i Resumo Nos ´ultimos anos o progresso tecnol´ogico tem feito crescer o interesse no estudo de robˆos com pernas, tendo um papel importante no desenvolvimento e na melhoria deste tipo de m´aquinas. M´aquinas com pernas tˆem vantagens distintas sobre os robˆos de rodas, prin- cipalmente, navegac¸˜ao em terrenos irregulares, capacidade de atravessar obst´aculos, bem como melhor equil´ıbrio e estabilidade em terrenos inclinados ou n˜ao-estruturados. No en- tanto, a gerac¸˜ao de locomoc¸˜ao robusta nestes robˆos articulados, ´eainda um problema dif´ıcil de resolver, em particular devido ao elevado n´umero de graus de liberdade que comp˜oem um robˆocom pernas e que tˆem de ser controlados. Neste trabalho focamos a nossa investigac¸˜ao em m´aquinas hexapodes usando a sua iner- ente capacidade de andar numa ampla variedade de terrenos, a qual ´euma das suas mais importantes caracter´ısticas. Os objectivos deste trabalho s˜ao projectar e implementar a ar- quitectura para um controlador bio-inspirado capaz de gerar uma locomoc¸˜ao robusta e est´avel em robˆos hexapodes, funcionalmente dividida em trˆes camadas. A arquitectura proposta ´e capaz de gerar diferentes tipos de movimentos dos hexapodes, transitar entre os seus tipos de movimentos mais comuns e corrigir a postura do robˆoem v´arias situac¸˜oes diferentes onde o equil´ıbrio do robˆo´eafectado. Os padr˜oes motores s˜ao gerados por Geradores de Padr˜ao Central (CPGs), formulados como osciladores n˜ao-lineares. Propusemos uma rede CPG que permite a locomoc¸˜ao est´avel do robˆoe a transic¸˜ao entre os seus diferentes movimentos. Estes padr˜oes s˜ao modulados por um sinal modulat´orio, alterando a frequˆencia, amplitude dos os- ciladores e os parˆametros de acoplamento entre os osciladores, proporcionalmente ao valor do sinal modulat´orio. O iniciar, parar da locomoc¸˜ao e a transic¸˜ao suave de movimento s˜ao alcanc¸ados mudando o sinal modulat´orio. A velocidade ´ealterada em conformidade, e uma locomoc¸˜ao natural do hexapode ´egerada. Nesta contribuic¸˜ao foi tamb´em desenvolvido um controlador de postura para robˆos hexapodes usando uma abordagem de sistemas dinˆamicos. Os resultados s˜ao realizados em simulac¸˜ao e foi desenvolvido um modelo de simulac¸˜ao do robˆohexapode Chiara. Os resultados demonstram a capacidade do controlador tanto para gerac¸˜ao de locomoc¸˜ao como para transic¸˜ao suave de movimento. O controlador postural ´e tamb´em testado em diferentes situac¸˜oes nas quais se espera que o robˆohexapode mantenha o equil´ıbrio. Os resultados apresentados provam a sua fiabilidade e robustez. ii Contents 1 Introduction 1 1.1 Motivation................................... 1 1.2 Objectives................................... 2 1.3 StructureoftheThesis .. .. .. .. .. .. .. .. 4 1.4 Publications.................................. 5 2 Biological Hexapod Locomotion 6 2.1 InvertebrateNervousSystems . .. 7 2.1.1 TheCentralNervousSystem. 9 2.2 CentralPatternGenerators . .. 13 2.2.1 Central Pattern Generators in Invertebrate Systems . ........ 14 2.3 ProposedArchitecture .. .. .. .. .. .. .. .. 16 2.3.1 ControllerRequirements . 17 3 State of the Art 20 3.1 LeggedRobots ................................ 20 3.2 HexapodRobots................................ 22 3.3 ControlModelsofHexapodLocomotion. ... 40 3.3.1 CentralPatternGenerationApproaches . ... 40 3.3.2 FiniteStatebasedApproaches . 43 3.3.3 CoordinationbasedApproaches . 43 3.4 GaitTransition ................................ 44 3.5 PostureControl ................................ 46 4 Development of Chiara Robot using Webots Simulator 49 4.1 ChiaraRobot ................................. 49 iii iv CONTENTS 4.1.1 Features................................ 50 4.1.2 Motors ................................ 52 4.1.3 Sensors ................................ 53 4.2 ShapeSimplificationusingSolidworks . ..... 54 4.3 WebotsModeloftheHexapodRobot. 55 4.3.1 ServoNode.............................. 57 4.3.2 PhysicsNode............................. 60 4.3.3 TouchSensorNode .......................... 61 5 Hexapod Locomotion Generation 63 5.1 GaitDescription................................ 63 5.2 LocomotorModel............................... 66 5.3 CPGs ..................................... 68 5.4 Interlimbcoordination . 75 5.5 GaitGenerationExperiments . .. 76 5.5.1 MetachronalGait........................... 76 5.5.2 RippleGait .............................. 79 5.5.3 TripodGait .............................. 81 6 Gait Transition 84 6.1 GaitTransitionMechanism . 84 6.2 Initiating/stoppinglocomotion . ..... 84 6.3 Dutyfactormodulation . 85 6.4 Gaitphasesmodulation. 85 6.5 Experiments.................................. 85 7 Posture Control 94 7.1 LateralPostureControl . 94 7.2 Experiments.................................. 97 8 Conclusions 107 8.1 ResultsDiscussion .............................. 108 8.2 FutureWork.................................. 109 List of Figures 2.1 Brain(from[1]). ............................... 9 2.2 VentralNerveCord(from[1]). .. 9 2.3 Commissure(from[1]).. 10 2.4 Intersegmental Connectives (from [1]). ....... 10 2.5 Protocerebrum(from[1]). 10 2.6 Deutocerebrum(from[1]). 11 2.7 Tritocerebrum(from[1]).. .. 11 2.8 SubesophagealGanglion(from[1]). .... 12 2.9 Circumesophageal Connectives (from [1]). ....... 12 2.10 ThoracicGanglia(from[1]). ... 12 2.11 AbdominalGanglia(from[1]). ... 13 2.12 Left: Functional division of the motor controller structures in the nervous system of invertebrate. Right: Proposed locomotor controller architecture. 16 3.1 RobotI(from[2]). .............................. 23 3.2 RobotII(from[2]). .............................. 24 3.3 Biobot(from[3])................................ 24 3.4 TarryIandTarryII(from[4]). .. 24 3.5 Hamlet(from[5]). .............................. 25 3.6 RHex(from[6]). ............................... 25 3.7 RobotIII(from[2]). ............................. 25 3.8 LauronIII(from[7]). ............................. 26 3.9 GenghisII(from[8]).............................. 26 3.10 TUMWalkingMachine(from[4]).. .. 26 3.11 GregorI(from[9]). .............................. 27 v vi LIST OF FIGURES 3.12 Chiara(from[10]). .............................. 27 3.13 Lynxmotion(from[11]). 28 3.14 Arthron(from[12]).. 28 3.15 HexCrawler(from[13]). 28 3.16 a) BILL-Ant-p robot (from [14]). b) Acromyrmex versicolor (from [14]). 29 3.17 a) Periplaneta americana (from [15]). b) Sprawlita (from[15]). 30 3.18 Whegs. a) Whegs I (from [16]). b) Whegs II (from [16]). .......
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