Modelling Walking Behaviors Based on CPGs: A Simplified Bio-inspired Architecture

In this article, we use a recurrent neural network including four-cell core architecture to model the walking gait and implement it with the simulated and physical NAO robot. Meanwhile, inspired by the biological CPG models, we propose a simplified CPG model which comprises motorneurons, interneurons, sensor neurons and the simplified spinal cord. Within this model, the CPGs do not directly output trajectories to the servo motors. Instead, they only work to maintain the phase relation among ipsilateral and contralateral limbs. The final output is dependent on the integration of CPG signals, outputs of interneurons, motor neurons and sensor neurons (sensory feedback).

[1]  A.J. Ijspeert,et al.  Passive compliant quadruped robot using Central Pattern Generators for locomotion control , 2008, 2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.

[2]  Linda B. Smith,et al.  A Dynamic Systems Approach to the Development of Cognition and Action , 2007, Journal of Cognitive Neuroscience.

[3]  John Hallam,et al.  From Animals to Animats 10 , 2008 .

[4]  Shin Ishii,et al.  Reinforcement learning for a biped robot based on a CPG-actor-critic method , 2007, Neural Networks.

[5]  D. McCrea,et al.  Modelling spinal circuitry involved in locomotor pattern generation: insights from deletions during fictive locomotion , 2006, The Journal of physiology.

[6]  Ludovic Righetti,et al.  Design Methodologies for Central Pattern Generators: An Application to Crawling Humanoids , 2006, Robotics: Science and Systems.

[7]  Tom Ziemke,et al.  Humanoids that crawl: Comparing gait performance of iCub and NAO using a CPG architecture , 2011, 2011 IEEE International Conference on Computer Science and Automation Engineering.

[8]  Tom Ziemke,et al.  Modelling early infant walking: Testing a generic CPG architecture on the NAO humanoid , 2011, 2011 IEEE International Conference on Development and Learning (ICDL).

[9]  Gordon Cheng,et al.  A Study of Adaptive Locomotive Behaviors of a Biped Robot: Patterns Generation and Classification , 2010, SAB.

[10]  S. Grillner,et al.  Neuronal Control of Locomotion 'From Mollusc to Man ' , 1999 .

[11]  Florentin Wörgötter,et al.  Fast Biped Walking with a Sensor-driven Neuronal Controller and Real-time Online Learning , 2006, Int. J. Robotics Res..

[12]  C. Liu,et al.  Biped Robot Walking using Central Pattern Generator and Genetic Algorithm , 2010 .

[13]  S. Grillner,et al.  Neuronal Control of LocomotionFrom Mollusc to Man , 1999 .

[14]  Auke Jan Ijspeert,et al.  Central pattern generators for locomotion control in animals and robots: A review , 2008, Neural Networks.

[15]  Patrick Henaff,et al.  On the Role of Sensory Feedbacks in Rowat–Selverston CPG to Improve Robot Legged Locomotion , 2010, Front. Neurorobot..

[16]  M. Latash.  Neurophysiological basis of movement , 1998 .

[17]  Brian Hopkins,et al.  Modelling the early development of bipedal locomotion: A multidisciplinary approach , 1995 .