Biologically Inspired Neural Controllers for Motor Control in a Quadruped Robot
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6 - Volume 6
Measuring the gap between FPGAs and ASICs
Proceedings of the 2006 ACM/SIGDA 14th international symposium on Field programmable gate arrays
2005 Special Issue: On-chip visual perception of motion: A bio-inspired connectionist model on FPGA
Neural Networks - 2005 Special issue: IJCNN 2005
Biological Cybernetics - Special Issue: Dynamic Principles
Embedded processors and systems: Architectural issues and solutions for emerging applications
Journal of Embedded Computing - Embeded Processors and Systems: Architectural Issues and Solutions for Emerging Applications
An Energy-Efficient Processor Architecture for Embedded Systems
IEEE Computer Architecture Letters
Implementation of Central Pattern Generator in an FPGA-Based Embedded System
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part II
Neuromorphic walking gait control
IEEE Transactions on Neural Networks
Analyzing the Scaling of Connectivity in Neuromorphic Hardware and in Models of Neural Networks
IEEE Transactions on Neural Networks
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Neuromorphic engineering is a discipline devoted to the design and development of computational hardware that mimics the characteristics and capabilities of neuro-biological systems. In recent years, neuromorphic hardware systems have been implemented using a hybrid approach incorporating digital hardware so as to provide flexibility and scalability at the cost of power efficiency and some biological realism. This paper proposes an FPGA-based neuromorphic-like embedded system on a chip to generate locomotion patterns of periodic rhythmic movements inspired by Central Pattern Generators (CPGs). The proposed implementation follows a top-down approach where modularity and hierarchy are two desirable features. The locomotion controller is based on CPG models to produce rhythmic locomotion patterns or gaits for legged robots such as quadrupeds and hexapods. The architecture is configurable and scalable for robots with either different morphologies or different degrees of freedom (DOFs). Experiments performed on a real robot are presented and discussed. The obtained results demonstrate that the CPG-based controller provides the necessary flexibility to generate different rhythmic patterns at run-time suitable for adaptable locomotion.