Inter-spikes-intervals exponential and gamma distributions study of neuron firing rate for SVITE motor control model on FPGA

This paper presents a statistical study on a neuro-inspired spike-based implementation of the Vector-Integration-To-End-Point motor controller (SVITE) and compares its deterministic neuron-model stream of spikes with a proposed modification that converts the model, and thus the controller, in a Poisson like spike stream distribution. A set of hardware pseudo-random numbers generators, based on a Linear Feedback Shift Register (LFSR), have been introduced in the neuron-model so that they reach a closer biological neuron behavior. To validate the new neuron-model behavior a comparison between the Inter-Spikes-Interval empirical data and the Exponential and Gamma distributions has been carried out using the Kolmogorov–Smirnoff test. An in-hardware validation of the controller has been performed in a Spartan6 FPGA to drive directly with spikes DC motors from robotics to study the behavior and viability of the modified controller with random components. The results show that the original deterministic spikes distribution of the controller blocks can be swapped with Poisson distributions using 30-bit LFSRs. The comparative between the usable controlling signals such as the trajectory and the speed profile using a deterministic and the new controller show a standard deviation of 11.53 spikes/s and 3.86 spikes/s respectively. These rates do not affect our system because, within Pulse Frequency Modulation, in order to drive the motors, time length can be fixed to spread the spikes. Tuning this value, the slow rates could be filtered by the motor. Therefore, this SVITE neuro-inspired controller can be integrated within complex neuromorphic architectures with Poisson-like neurons

Event-based control system on FPGA applied to the pencil balancer robotic platform

An event-based motor controller design is presented. The system is designed to solve the classic inverted pendulum problem by using a robotic platform and a totally neuro-inspired event-based mechanism. Specifically, DVS retinas provide feedback and an FPGA implements control. The robotic platform used is the so called ’pencil balancer’. The retinas provide visual information to the FPGA that processes it and obtains the center of mass of the pencil. Once this center of mass is averaged over time, it is used joint with the cart position provided by a flat potentiometer bar to compute the angle of the pencil from the vertical. The angle is delivered to an eventbased Proportional-Derivative (PD) controller that drives the DC motor using Pulse Frequency Modulation (PFM) to accomplish the control objective. The results show an accurate, real-time and efficient controller design

ED-BioRob: A Neuromorphic Robotic Arm With FPGA-Based Infrastructure for Bio-Inspired Spiking Motor Controllers

Compared to classic robotics, biological nervous systems respond to stimuli in a fast and efficient way regarding the body motor actions. Decision making, once the sensory information arrives to the brain, is in the order of ms, while the whole process from sensing to movement requires tens of ms. Classic robotic systems usually require complex computational abilities. Key differences between biological systems and robotic machines lie 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 currents or ionic pulses (spikes). When neurons are arranged in networks, they allow not only for the processing of sensory information, but also for 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 closed-loop control model, called spike-based PID controller (sPID), was 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 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

A Survey on FPGA-Based Sensor Systems: Towards Intelligent and Reconfigurable Low-Power Sensors for Computer Vision, Control and Signal Processing

The current trend in the evolution of sensor systems seeks ways to provide more accuracy and resolution, while at the same time decreasing the size and power consumption. The use of Field Programmable Gate Arrays (FPGAs) provides specific reprogrammable hardware technology that can be properly exploited to obtain a reconfigurable sensor system. This adaptation capability enables the implementation of complex applications using the partial reconfigurability at a very low-power consumption. For highly demanding tasks FPGAs have been favored due to the high efficiency provided by their architectural flexibility (parallelism, on-chip memory, etc.), reconfigurability and superb performance in the development of algorithms. FPGAs have improved the performance of sensor systems and have triggered a clear increase in their use in new fields of application. A new generation of smarter, reconfigurable and lower power consumption sensors is being developed in Spain based on FPGAs. In this paper, a review of these developments is presented, describing as well the FPGA technologies employed by the different research groups and providing an overview of future research within this field.The research leading to these results has received funding from the Spanish Government and European FEDER funds (DPI2012-32390), the Valencia Regional Government (PROMETEO/2013/085) and the University of Alicante (GRE12-17)

Sensors and Technologies in Spain: State-of-the-Art

The aim of this special issue was to provide a comprehensive view on the state-of-the-art sensor technology in Spain. Different problems cause the appearance and development of new sensor technologies and vice versa, the emergence of new sensors facilitates the solution of existing real problems. [...

Proceedings of the 19th Sound and Music Computing Conference

Proceedings of the 19th Sound and Music Computing Conference - June 5-12, 2022 - Saint-Étienne (France). https://smc22.grame.f