ED-BioRob: A Neuromorphic Robotic Arm With FPGA-Based Infrastructure for Bio-Inspired Spiking Motor Controllers - Linares-Barranco, Alejandro; Perez-Peña, Fernando; Jimenez-Fernandez, Angel; Chicca, Elisabetta (Frontiers in Neurorobotics, 2020)
Compared to classic robotics, biological nervous systems respond to stimuli in a fast and efficient way regarding to the body motor actions. Decision making, once the sensory information arrives to the brain, requires a few $μ$s while the whole process from sensing to movement requires tens of ms. Classic robotics systems usually require complex computational abilities. Key differences between biological systems and robotic machines reside in the way information is coded and transmitted. A neuron is the “basic” element that constitutes biological nervous systems. Neurons communicate in an event-driven way through small current or ionic pulses (spikes). When neurons are arranged in networks, they allow not only the processing of sensory information, but also the actuation over the muscles in the same spiking manner. This paper presents the application of a classic motor control model (proportional-integral-derivative) developed with the biological spike processing principle, including the motor actuation with time enlarged spikes instead of the classic pulse-width-modulation. This close-loop control model, called spike-PID controller, has been improved and adapted for a dual FPGA-based system to control the four joints of a bioinspired light robot (BioRob X5), called event-driven BioRob (ED-BioRob). The use of spiking signals has allowed the system to achieve a current consumption bellow 1A for the entire 4 DoF working at the same time. Furthermore, the robot joints commands can be received from a population of silicon-neurons running on the Dynap-SE platform. Thus, our proposal aims to bridge the gap between a general purpose processing analog neuromorphic hardware and the spiking actuation of a robotic platform.