Abstract
Central pattern generators (CPGs) are neural circuits found in vertebrate and invertebrate animals that produce oscillatory patterns for rhythmic motor behaviors. When applied to robotics, they are often used as building blocks for the generation of walking controllers. From a mathematical viewpoint, CPGs are dynamical systems exhibiting limit cycle behaviors, which offer several advantages when applied to the locomotion of robots. One of their main advantages is that they can be dynamically coupled to the mechanical system, which can enforce the synchronization of the CPG network with the body and the environment, through mechanical entrainment using resonance tuning or through explicit learning of the frequency components and the phases of an external signal. Moreover, they permit easy modulation of the gait speed and incorporation of gait transition mechanisms. The recovery from perturbations is also inherently encoded in the system, and the need for an accurate model of the robot is often not required. Finally, if the CPG controller is implemented in a distributed fashion, e.g., on several microcontrollers, it allows simplified reconfiguration or adaptation of the robot to a missing or a nonfunctional part.
After an historical overview of CPG-based models in the first section of the chapter (Sect. 1), we describe different conceptual models in Sect. 2 and review important methodological considerations in the implementation of a CPG controller for robotic applications in Sect. 3. Finally, in Sect. 4, we review some applications of CPGs in robots, with a strong emphasis on the control of humanoid locomotion.
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Dzeladini, F., Ait-Bouziad, N., Ijspeert, A. (2019). CPG-Based Control of Humanoid Robot Locomotion. In: Goswami, A., Vadakkepat, P. (eds) Humanoid Robotics: A Reference. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6046-2_49
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