Locomotion gait optimization for a quadruped robot

This article describes the development of a gait optimization system that allows a fast but stable robot quadruped crawl gait. We focus in the development of a quadruped robot walking gait locomotion that combine bio-inspired Central Patterns Generators (CPGs) and Genetic Algorithms (GA). The CPGs are modelled as autonomous differential equations, that generate the necessary limb movement to perform the walking gait, and the Genetic Algorithm perform the search of the CPGs parameters. This approach allows to explicitly specify parameters such as amplitude, offset and frequency of movement and to smoothly modulate the generated trajectories according to changes in these parameters. It is therefore easy to combine the CPG with an optimization method. A genetic algorithm determines the best set of parameters that generates the limbs movements. We intend to obtain a walking gait locomotion that minimizes the vibration and maximizes the wide stability margin and the forward velocity. The experimental results, performed on a simulated Aibo robot, demonstrated that our approach allows low vibration with a high velocity and wide stability margin for a quadruped walking gait locomotion

Multi-objective parameter CPG optimization for gait generation of a quadruped robot considering behavioral diversity

This paper presents a gait multi-objective optimization system that combines bio-inspired Central Patterns Generators (CPGs) and a multi-objective evolutionary algorithm. CPGs are modeled as autonomous differential equations, that generate the necessary limb movement to perform the required walking gait. In order to optimize the walking gait, four conflicting objectives are considered, simultaneously: minimize the body vibration, maximize the velocity, maximize the wide stability margin and maximize the behavioral diversity. The results of NSGA-II for this multi-objective problem are discussed. The effect of the inclusion of a behavioral diversity objective in the system is also studied in terms of the walking gait achieved. The experimental results show the effectiveness of this multi-objective approach. The several walking gait solutions obtained correspond to different trade-off between the objectives.This work is funded by FEDER Funding supported by the Operational Program Competitive Factors - COMPETE and National Funding supported by the FCT - Portuguese Science Foundation through project PTDC/EEACRO/ 100655/2008. Thanks to Dr. St ? ephane Doncieux from the Institut des Systmes Intelligents et de Robotique (ISIR) of the Pierre and Marie Curie University (UPMC

Learning to Walk with Model Assisted Evolution Strategies

Many algorithms in robotics contain parameterized models. The setting of the parameters in general has a strong impact on the quality of the model. Finding a parameter set which optimizes the quality of the model typically is a challenging task, especially if the structure of the problem is unknown and can not be specified mathematically, i.e. the only way to ge

A review of gait optimization based on evolutionary computation

Gait generation is very important as it directly affects the quality of locomotion of legged robots. As this is an optimization problem with constraints, it readily lends itself to Evolutionary Computation methods and solutions. This paper reviews the techniques used in evolution-based gait optimization, including why Evolutionary Computation techniques should be used, how fitness functions should be composed, and the selection of genetic operators and control parameters. This paper also addresses further possible improvements in the efficiency and quality of evolutionary gait optimization, some problems that have not yet been resolved and the perspectives for related future research

Design and Evaluation of Pediatric Gait Rehabilitation Robots

Gait therapy methodologies were studied and analyzed for their potential for pediatric patients. Using data from heel, metatarsal, and toe trajectories, a nominal gait trajectory was determined using Fourier transforms for each foot point. These average trajectories were used as a basis of evaluating each gait therapy mechanism. An existing gait therapy device (called ICARE) previously designed by researchers, including engineers at the University of Nebraska-Lincoln, was redesigned to accommodate pediatric patients. Unlike many existing designs, the pediatric ICARE did not over- or under-constrain the patient’s leg, allowing for repeated, comfortable, easily-adjusted gait motions. This design was assessed under clinical testing and deemed to be acceptable. A gait rehabilitation device was designed to interface with both pediatric and adult patients and more closely replicate the gait-like metatarsal trajectory compared to an elliptical machine. To accomplish this task, the nominal gait path was adjusted to accommodate for rotation about the toe, which generated a new trajectory that was tangent to itself at the midpoint of the stride. Using knowledge of the bio-mechanics of the foot, the gait path was analyzed for its applicability to the general population. Several trajectory-replication methods were evaluated, and the crank-slider mechanism was chosen for its superior performance and ability to mimic the gait path adequately. Adjustments were made to the gait path to further optimize its realization through the crank-slider mechanism. Two prototypes were constructed according to the slider-crank mechanism to replicate the gait path identified. The first prototype, while more accurately tracing the gait path, showed difficulty in power transmission and excessive cam forces. This prototype was ultimately rejected. The second prototype was significantly more robust. However, it lacked several key aspects of the original design that were important to matching the design goals. Ultimately, the second prototype was recommended for further work in gait-replication research. Advisor: Carl A. Nelso

Design and Evaluation of Pediatric Gait Rehabilitation Robots

Gait therapy methodologies were studied and analyzed for their potential for pediatric patients. Using data from heel, metatarsal, and toe trajectories, a nominal gait trajectory was determined using Fourier transforms for each foot point. These average trajectories were used as a basis of evaluating each gait therapy mechanism. An existing gait therapy device (called ICARE) previously designed by researchers, including engineers at the University of Nebraska-Lincoln, was redesigned to accommodate pediatric patients. Unlike many existing designs, the pediatric ICARE did not over- or under-constrain the patient’s leg, allowing for repeated, comfortable, easily-adjusted gait motions. This design was assessed under clinical testing and deemed to be acceptable. A gait rehabilitation device was designed to interface with both pediatric and adult patients and more closely replicate the gait-like metatarsal trajectory compared to an elliptical machine. To accomplish this task, the nominal gait path was adjusted to accommodate for rotation about the toe, which generated a new trajectory that was tangent to itself at the midpoint of the stride. Using knowledge of the bio-mechanics of the foot, the gait path was analyzed for its applicability to the general population. Several trajectory-replication methods were evaluated, and the crank-slider mechanism was chosen for its superior performance and ability to mimic the gait path adequately. Adjustments were made to the gait path to further optimize its realization through the crank-slider mechanism. Two prototypes were constructed according to the slider-crank mechanism to replicate the gait path identified. The first prototype, while more accurately tracing the gait path, showed difficulty in power transmission and excessive cam forces. This prototype was ultimately rejected. The second prototype was significantly more robust. However, it lacked several key aspects of the original design that were important to matching the design goals. Ultimately, the second prototype was recommended for further work in gait-replication research. Advisor: Carl A. Nelso

Otimização muscle-in-the-loop em tempo real para reabilitação física com um exosqueleto ativo: uma mudança de paradigma

Assisting human locomotion with a wearable robotic orthosis is still quite challenging, largely due to the complexity of the neuromusculoskeletal system, the time-varying dynamics that accompany motor adaptation, and the uniqueness of every individual’s response to the assistance given by the robot. To this day, these devices have not met their well-known promise yet, mostly due to the fact that they are not perfectly suitable for the rehabilitation of neuropathologic patients. One of the main challenges hampering this goal still relies on the interface and co-dependency between the human and the machine. Nowadays, most commercial exoskeletons replay pre-defined gait patterns, whereas research exoskeletons are switching to controllers based on optimized torque profiles. In most cases, the dynamics of the human musculoskeletal system are still ignored and do not take into account the optimal conditions for inducing a positive modulation of neuromuscular activity. This is because both rehabilitation strategies are still emphasized on the macro level of the whole joint instead of focusing on the muscles’ dynamics and activity, which are the actual anatomical elements that may need to be rehabilitated. Strategies to keep the human in the loop of the exoskeleton’s control laws in real-time may help to overcome these challenges. The main purpose of the present dissertation is to make a paradigm shift in the approach on how the assistance that is given to a subject by an exoskeleton is modelled and controlled during physical rehabilitation. Therefore, in the scope of the present work, it was intended to design, concede, implement, and validate a real-time muscle-in-the-loop optimization model to find the best assistive support ratio that would induce optimal rehabilitation conditions to a specific group of impaired muscles while having a minimum impact on the other healthy muscles. The developed optimization model was implemented in the form of a plugin and was integrated on a neuromechanical model-based interface for driving a bilateral ankle exoskeleton. Experimental pilot tests evaluated the feasibility and effectiveness of the model. Results of the most significant pilots achieved EMG reductions up to 61 ± 3 % in Soleus and 41 ± 10 % in Gastrocnemius Lateralis. Moreover, results also demonstrated the efficiency of the optimization’s specific reduction on rehabilitation by looking into the muscular fatigue after each experiment. Finally, two parallel preliminary studies emerged from the pilots, which looked at muscle adaptation, after a new assistive condition had been applied, over time and at the effect of the lateral positioning of the exoskeleton’s actuators on the leg muscles.Auxiliar a locomoção humana com uma ortose robótica ainda é bastante desafiante, em grande parte devido à complexidade do sistema neuromusculoesquelético, à dinâmica variável no tempo que acompanha a adaptação motora e à singularidade da resposta de cada indivíduo à assistência dada pelo robô. Até hoje, está por cumprir a promessa inicial destes dispositivos, principalmente devido ao facto de não serem perfeitamente adequados para a reabilitação de pacientes neuropatológicos. Um dos principais desafios que dificultam esse objetivo foca-se ainda na interface e na co-dependência entre o ser humano e a máquina. Hoje em dia, a maioria dos exoesqueletos comerciais reproduz padrões de marcha predefinidos, enquanto que os exoesqueletos em investigação estão só agora a mudar para controladores com base em perfis de binário otimizados. Na maioria dos casos, a dinâmica do sistema musculoesquelético humano ainda é ignorada e não tem em consideração as condições ideais para induzir uma modulação positiva da atividade neuromuscular. Isso ocorre porque ambas as estratégias de reabilitação ainda são enfatizadas no nível macro de toda a articulação, em vez de se concentrar na dinâmica e atividade dos músculos, que são os elementos anatómicos que realmente precisam de ser reabilitados. Estratégias para manter o ser humano em loop nos comandos que controlam o exoesqueleto em tempo real podem ajudar a superar estes desafios. O principal objetivo desta dissertação é fazer uma mudança de paradigma na abordagem em como a assistência que é dada a um sujeito por um exosqueleto é modelada e controlada durante a reabilitação física. Portanto, no contexto do presente trabalho, pretendeu-se projetar, conceder, implementar e validar um modelo de otimização muscle-in-the-loop em tempo real para encontrar a melhor relação de suporte capaz de induzir as condições ideais de reabilitação para um grupo específico de músculos fragilizados, tendo um impacto mínimo nos outros músculos saudáveis. O modelo de otimização desenvolvido foi implementado na forma de um plugin e foi integrado numa interface baseada num modelo neuromecânico para o controlo de um exoesqueleto bilateral de tornozelo. Testes experimentais piloto avaliaram a viabilidade e a eficácia do modelo. Os resultados dos testes mais significativos demonstraram reduções de EMG de até 61 ± 3 % no Soleus e 41 ± 10 % no Gastrocnemius Lateral. Adicionalmente, os resultados demonstraram também a eficiência em reabilitação da redução específica no EMG devido à otimização tendo em conta a fadiga muscular após cada teste. Finalmente, dois estudos preliminares paralelos emergiram dos testes piloto, que analisaram a adaptação muscular após uma nova condição assistiva ter sido definida ao longo do tempo e o efeito do posicionamento lateral dos atuadores do exoesqueleto nos músculos da perna.Mestrado em Engenharia Biomédic

Preface

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