A FPGA-Based Neuromorphic Locomotion System for Multi-Legged Robots

作者：Israel Guerra Hernandez Erick; Espinal Andres; Batres Mendoza Patricia; Hugo Garcia Capulin Carlos; Romero Troncoso Rene De J; Rostro Gonzalez Horacio^*

来源：IEEE Access, 2017, 5: 8301-8312.

DOI：10.1109/ACCESS.2017.2696985

• FPGA
• spiking neural networks
• neuromorphic engineering
• legged robots
• grammatical evolution
• Victor-Purpura distance

The paper develops a neuromorphic system on a Spartan 6 field programmable gate array (FPGA) board to generate locomotion patterns (gaits) for three different legged robots (biped, quadruped, and hexapod). The neuromorphic system consists of a reconfigurable FPGA-based architecture for a 3G artificial neural network (spiking neural network), which acts as a Central Pattern Generator (CPG). The locomotion patterns, are then generated by the CPG through a general neural architecture, which parameters are offline estimated by means of grammatical evolution and Victor-Purpura distance-based fitness function. The neuromorphic system is fully validated on real biped, quadruped, and hexapod robots.

• 出版日期2017