Arturo Morgado-Estevez

Neuro-Inspired Spike-Based Motion: From Dynamic Vision Sensor to Robot Motor Open-Loop Control through Spike-VITE

In this paper we present a complete spike-based architecture: from a Dynamic Vision Sensor (retina) to a stereo head robotic platform. The aim of this research is to reproduce intended movements performed by humans taking into account as many features as possible from the biological point of view. This paper fills the gap between current spike silicon sensors and robotic actuators by applying a spike processing strategy to the data flows in real time. The architecture is divided into layers: the retina, visual information processing, the trajectory generator layer which uses a neuroinspired algorithm (SVITE) that can be replicated into as many times as DoF the robot has; and finally the actuation layer to supply the spikes to the robot (using PFM). All the layers do their tasks in a spike-processing mode, and they communicate each other through the neuro-inspired AER protocol. The open-loop controller is implemented on FPGA using AER interfaces developed by RTC Lab. Experimental results reveal the viability of this spike-based controller. Two main advantages are: low hardware resources (2% of a Xilinx Spartan 6) and power requirements (3.4 W) to control a robot with a high number of DoF (up to 100 for a Xilinx Spartan 6). It also evidences the suitable use of AER as a communication protocol between processing and actuation.

Towards AER VITE: Building spike gate signal

Neuromorphic engineers aim to mimic the precise and efficient mechanisms of the nervous system to process information using spikes from sensors to actuators. There are many available works that sense and process information in a spike-based way. But there are still several gaps in the actuation and motor control field in a spike-based way. Spike-based Proportional-Integrative-Derivative controllers (PID) are present in the literature. On the other hand, neuro-inspired control models as VITE (Vector Integration To End point) and FLETE (Factorization of muscle Length and muscle Tension) are also present in the literature. This paper presents another step toward the spike implementation of those neuro-inspired models. We present a spike-based ramp multiplier. VITE algorithm generates the way to achieve a final position targeted by a mobile robotic arm. The block presented is used as a gate for the way involved and it also puts the incoming movement on speed with a variable slope profile. Only spikes for information representation were used and the process is in real time. The software simulation based on Simulink and Xilinx System Generator shows the accurate adjust to the traditional processing for short time periods and the hardware tests confirm and extend the previous simulated results for any time. We have implemented the spikes generator, the ramp multiplier and the low pass filter into the Virtex-5 FPGA and connected this with an USB-AER (Address Event Representation) board to monitor the spikes.

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 11.53spikes/s and 3.86spikes/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.

A FPGA spike-based robot controlled with neuro-inspired VITE

This paper presents a spike-based control system applied to a fixed robotic platform. Our aim is to take a step forward to a future complete spikes processing architecture, from vision to direct motor actuation. This paper covers the processing and actuation layer over an anthropomorphic robot. In this way, the processing layer uses the neuro-inspired VITE algorithm, for reaching a target, based on PFM taking advantage of spike system information: its frequency. Thus, all the blocks of the system are based on spikes. Each layer is implemented within a FPGA board and spikes communication is codified under the AER protocol. The results show an accurate behavior of the robotic platform with 6-bit resolution for a 130o range per joint, and an automatic speed control of the algorithm. Up to 96 motor controllers could be integrated in the same FPGA, allowing the positioning and object grasping by more complex anthropomorphic robots.

Towards a cloud-based automated surveillance system using wireless technologies

Cloud Computing can bring multiple benefits for Smart Cities. It permits the easy creation of centralized knowledge bases, thus straightforwardly enabling that multiple embedded systems (such as sensor or control devices) can have a collaborative, shared intelligence. In addition to this, thanks to its vast computing power, complex tasks can be done over low-spec devices just by offloading computation to the cloud, with the additional advantage of saving energy. In this work, cloud’s capabilities are exploited to implement and test a cloud-based surveillance system. Using a shared, 3D symbolic world model, different devices have a complete knowledge of all the elements, people and intruders in a certain open area or inside a building. The implementation of a volumetric, 3D, object-oriented, cloud-based world model (including semantic information) is novel as far as we know. Very simple devices (orange Pi) can send RGBD streams (using kinect cameras) to the cloud, where all the processing is distributed and done thanks to its inherent scalability. A proof-of-concept experiment is done in this paper in a testing lab with multiple cameras connected to the cloud with 802.11ac wireless technology. Our results show that this kind of surveillance system is possible currently, and that trends indicate that it can be improved at a short term to produce high performance vigilance system using low-speed devices. In addition, this proof-of-concept claims that many interesting opportunities and challenges arise, for example, when mobile watch robots and fixed cameras would act as a team for carrying out complex collaborative surveillance strategies.

Spike-based VITE control with dynamic vision sensor applied to an arm robot

Spike-based motor control is very important in the field of robotics and also for the neuromorphic engineering community to bridge the gap between sensing / processing devices and motor control without losing the spike philosophy that enhances speed response and reduces power consumption. This paper shows an accurate neuro-inspired spike-based system composed of a DVS retina, a visual processing system that detects and tracks objects, and a SVITE motor control, where everything follows the spike-based philosophy. The control system is a spike version of the neuroinspired open loop VITE control algorithm implemented in a couple of FPGA boards: the first one runs the algorithm and the second one drives the motors with spikes. The robotic platform is a low cost arm with four degrees of freedom.

SVITE: A Spike-Based VITE Neuro-Inspired Robot Controller

This paper presents an implementation of a neuro-inspired algorithm called VITE (Vector Integration To End Point) in FPGA in the spikes domain. VITE aims to generate a non-planned trajectory for reaching tasks in robots. The algorithm has been adapted to work completely in the spike domain under Simulink simulations. The FPGA implementation consists in 4 VITE in parallel for controlling a 4-degree-of-freedom stereo-vision robot. This work represents the main layer of a complex spike-based architecture for robot neuro-inspired reaching tasks in FPGAs. It has been implemented in two Xilinx FPGA families: Virtex-5 and Spartan-6. Resources consumption comparative between both devices is presented. Results obtained for Spartan device could allow controlling complex robotic structures with up to 96 degrees of freedom per FPGA, providing, in parallel, high speed connectivity with other neuromorphic systems sending movement references. An exponential and gamma distribution test over the inter spike interval has been performed to proof the approach to the neural code proposed.

Performance study of software AER-based convolutions on a parallel supercomputer

This paper is based on the simulation of a convolution model for bioinspired neuromorphic systems using the Address-Event-Representation (AER) philosophy and implemented in the supercomputer CRS of the University of Cadiz (UCA). In this work we improve the runtime of the simulation, by dividing an image into smaller parts before AER convolution and running each operation in a node of the cluster. This research involves a test cases design in which the optimal parameters are set to run the AER convolution in parallel processors. These cases consist on running the convolution taking an image divided in different number of parts, applying to each part a Sobel filter for edge detection, and based on the AER-TOOL simulator. Execution times are compared for all cases and the optimal configuration of the system is discussed. In general, CRS obtain better performances when the image is divided than for the whole image.

Low-Cost Servomotor Driver for PFM Control

Servomotors have already been around for some decades and they are extremely popular among roboticists due to their simple control technique, reliability and low-cost. They are usually controlled by using Pulse Width Modulation (PWM) and this paper aims to keep the idea of simplicity and low-cost, while introducing a new control technique: Pulse Frequency Modulation (PFM). The objective of this paper is to focus on our development of a low-cost servomotor controller which will allow the research community to use them with PFM. A low-cost commercial servomotor is used as the base system for the development: a small PCB that fits inside the case and allocates all the electronic components to control the motor has been designed to replace the original. The potentiometer is retained as the feedback sensor and a microcontroller is responsible for controlling the position of the motor. The paper compares the performance of a PWM and a PFM controlled servomotor. The comparison shows that the servomotor with our controller achieves a faster mechanism for switching targets and a lower latency. This controller can be used with neuromorphic systems to remove the conversion from events to PWM.

Towards Automated Welding in Big Shipbuilding Assisted by Programed Robotic Arm Using a Measuring Arm

This paper presents an automated robotic welding system adapted for shipbuilding in large shipyards. This solution has been devised in the shipyard of Navantia located in the south of Spain, in the context of ROBOT FASE II R&D project. It also presents the human teams that have developed this welding system. The article explains the 3 parts that make up the welding system. The location of the robotic welding arm of the Fanuc brand is detailed in the first part. In addition, the gantry and spatial coordinate axes are described and indicated where the robotic arm is housed. The second part contains the system capture of the coordinates in the space for the reading of the singular points to be soldered. These points are measured by a portable measuring arm. The last part is composed of the system of communication between the different parts throughout the computer. The computer is responsible for synchronizing the measuring arm and the robotic welding arm by translating the points to be soldered.