Intelligent Approaches in Locomotion - A Review <s> Central pattern generators and oscillators <s> Most rhythmic behaviors such as respiration, locomotion, and feeding are under the control of networks of neurons in the central nervous system known as central pattern generators (CPGs). The respiratory rhythm of the pond snail Lymnaea stagnalis is a relatively simple, CPG-based behavior for which the underlying neural elements have been identified. A three-neuron network capable of generating the respiratory rhythm of this air-breathing mollusk has been reconstructed in culture. The intrinsic and network properties of this neural ensemble have been studied, and the mechanism of postinhibitory rebound excitation was found to be important for the rhythm generation. This in vitro model system enables a better understanding of the neural basis of rhythm generation. <s> BIB001 </s> Intelligent Approaches in Locomotion - A Review <s> Central pattern generators and oscillators <s> Central pattern generators are neuronal circuits that when activated can produce rhythmic motor patterns such as walking, breathing, flying, and swimming in the absence of sensory or descending inputs that carry specific timing information. General principles of the organization of these circuits and their control by higher brain centers have come from the study of smaller circuits found in invertebrates. Recent work on vertebrates highlights the importance of neuromodulatory control pathways in enabling spinal cord and brain stem circuits to generate meaningful motor patterns. Because rhythmic motor patterns are easily quantified and studied, central pattern generators will provide important testing grounds for understanding the effects of numerous genetic mutations on behavior. Moreover, further understanding of the modulation of spinal cord circuitry used in rhythmic behaviors should facilitate the development of new treatments to enhance recovery after spinal cord damage. <s> BIB002 </s> Intelligent Approaches in Locomotion - A Review <s> Central pattern generators and oscillators <s> This paper presents theoretical results of the neural control mechanism existed in the spinal cord, central pattern generator (CPG), which has the ability to provide rhythmic movement patterns for the invertebrate and vertebrate. It is known that although CPG is verified by biological methods, it still lacks a complete theoretical investigation. The theoretical analysis about CPG from engineering perspective such as parameter selection and conditions of stable oscillation will strengthen the foundation of CPG theory, and it will significantly enhance the effective application of CPG into motor control systems. <s> BIB003 </s> Intelligent Approaches in Locomotion - A Review <s> Central pattern generators and oscillators <s> The problem of controlling locomotion is an area in which neuroscience and robotics can fruitfully interact. In this article, I will review research carried out on locomotor central pattern generators (CPGs), i.e. neural circuits capable of producing coordinated patterns of high-dimensional rhythmic output signals while receiving only simple, low-dimensional, input signals. The review will first cover neurobiological observations concerning locomotor CPGs and their numerical modelling, with a special focus on vertebrates. It will then cover how CPG models implemented as neural networks or systems of coupled oscillators can be used in robotics for controlling the locomotion of articulated robots. The review also presents how robots can be used as scientific tools to obtain a better understanding of the functioning of biological CPGs. Finally, various methods for designing CPGs to control specific modes of locomotion will be briefly reviewed. In this process, I will discuss different types of CPG models, the pros and cons of using CPGs with robots, and the pros and cons of using robots as scientific tools. Open research topics both in biology and in robotics will also be discussed. <s> BIB004 </s> Intelligent Approaches in Locomotion - A Review <s> Central pattern generators and oscillators <s> Compared with wheeled mobile robots, legged robots can easily step over obstacles and walk through rugged ground. They have more flexible bodies and therefore, can deal with complex environment. Nevertheless, some other issues make the locomotion control of legged robots a much complicated task, such as the redundant degree of freedoms and balance keeping. From literatures, locomotion control has been solved mainly based on programming mechanism. To use this method, walking trajectories for each leg and the gaits have to be designed, and the adaptability to an unknown environment cannot be guaranteed. From another aspect, studying and simulating animals’ walking mechanism for engineering application is an efficient way to break the bottleneck of locomotion control for legged robots. This has attracted more and more attentions. Inspired by central pattern generator (CPG), a control method has been proved to be a successful attempt within this scope. In this paper, we will review the biological mechanism, the existence evidences, and the network properties of CPG. From the engineering perspective, we will introduce the engineering simulation of CPG, the property analysis, and the research progress of CPG inspired control method in locomotion control of legged robots. Then, in our research, we will further discuss on existing problems, hot issues, and future research directions in this field. <s> BIB005
In motor skills science there was a debate over whether locomotion is reflex based or is generated internally. Experiments in the second half of the 20th century demonstrated that internal generation had to be a significant part of locomotion  . This was proved by severing sensory neural pathways in animal subjects and observing that they could still perform locomotion. In more recent times, dissections have enabled a reverse engineering of the neural networks that control this innate locomotion. Those networks that have been discovered exist in spinal regions and have therefore been called 'central pattern generators', or CPGs BIB002 - BIB001 . A biological CPG can be defined as a neural network that produces rhythmic pattern outputs without the need for patterned input. However, a distinction should be made between CPG neural networks and more traditional NNs, which are discussed in section 4. In reviewing the engineering use of CPGs, we have determined that it is better to see CPGs as systems of oscillators, rather than as neural networks. In biological systems, the primary unit of rhythm is built around a pair of inhibitory/excitatory neurons that produce oscillations. A detailed examination of a biological CPG from an engineering perspective was conducted in BIB003 but, for most applications, the neuron pair is approximated with a pair of differential equations. The review of CPGs here focuses on application to robotic control and generalises the concept to oscillator models. For other perspectives, including historical and biological contexts, see the reviews in BIB005 , BIB004 . Some approaches, that are referred to as CPGs, do not even explicitly use pairs of differentials equations, but rather use oscillators with more transparent sinusoidal forms, as discussed in the next section.