AER and dynamic systems co-simulation over Simulink with Xilinx System Generator

Address-Event Representation (AER) is a neuromorphic communication protocol for transferring information of spiking neurons implemented into VLSI chips. These neuro-inspired implementations have been used to design sensor chips (retina, cochleas), processing chips (convolutions, filters) and learning chips, what makes possible the development of complex, multilayer, multichip neuromorphic systems. In biology one of the last steps of the processing is to move a muscle, to apply the results of these complex neuromorphic processing to the real world. One interesting question is to be able to transform, or translate, the AER information into robot movements, like for example, moving a DC motor. This paper presents several ways to translate AER spikes into DC motor power, and to control a DC motor speed, based on Pulse Frequency Modulation. These methods have been simulated into Simulink with Xilinx System Generator, and tested into the AER-Robot platform.Junta de Andalucía P06-TIC-01417Ministerio de Educación y Ciencia TEC2006-11730-C03-0

Integrating sensors and actuators for robotic assembly

This thesis addresses the problem of integrating sensors and actuators for closed-loop control of a robotic assembly cell. In addition to the problems of interfacing the physical components of the work-cell, the difficulties of representing sensory feedback at a high level within the robot control program are investigated. A new level of robot programming, called sensor-level programming, is introduced. In this, the movements of the actuators are not given explicitly, but rather are inferred by the programming system to achieve new sensor conditions given by the programmer.Control of each sensor and actuator is distributed through a master-slave hierarchy, with each sensor and actuator having its own slave controller. A protocol for information interchange between each controller and the master is defined. If possible, the control of the kinematics of a robot arm is achieved through the manufacturer's existing control system. Under these circumstances, the actuator slave would be acting as aninterface between the generic command codes issued from the central controller, and the syntax of the corresponding control instructions required by the commercial system.Sensor information is preprocessed in the sensor slaves and a set of high-level descriptors, called attributes, are sent to the central controller. Closed-loop control is achieved on the basis of these attributes.The processing of sensor information which is corrupted by noise is investigated. Sources of sensor noise are identified and new algorithms are developed to quantify the noise based on information obtained from the closed-loop servoing. Once the relative magnitudes of the system andmeasurement noise have been estimated, a Kalman filter is used to weight the sensor information and hence reduce the credibility given to noisy sensors; in the limit ignoring the information completely. The improvements in system performance by processing the sensor information in this way are demonstrated.The sensor-level representation and automatic error processing are embedded in a software control system, which can be used to interface commercial systems as well as purpose-built devices. An'industrial research project associated with the lay-up of carbon-fibre provides anexample of its operation.A list of publications resulting from the work in this thesis is given in Appendix E

Neuro-inspired system for real-time vision sensor tilt correction

Neuromorphic engineering tries to mimic biological information processing. Address-Event-Representation (AER) is an asynchronous protocol for transferring the information of spiking neuro-inspired systems. Currently AER systems are able sense visual and auditory stimulus, to process information, to learn, to control robots, etc. In this paper we present an AER based layer able to correct in real time the tilt of an AER vision sensor, using a high speed algorithmic mapping layer. A codesign platform (the AER-Robot platform), with a Xilinx Spartan 3 FPGA and an 8051 USB microcontroller, has been used to implement the system. Testing it with the help of the USBAERmini2 board and the jAER software.Junta de Andalucía P06-TIC-01417Ministerio de Educación y Ciencia TEC2006-11730-C03-02Ministerio de Ciencia e Innovación TEC2009-10639-C04-0

Design and Development of a Hydrogel-based Soft Sensor for Multi-Axis Force Control

As soft robotic systems become increasingly complex, there is a need to develop sensory systems which can provide rich state information to the robot for feedback control. Multi-axis force sensing and control is one of the less explored problems in this domain. There are numerous challenges in the development of a multi-axis soft sensor: from the design and fabrication to the data processing and modelling. This work presents the design and development of a novel multi-axis soft sensor using a gelatin-based ionic hydrogel and 3D printing technology. A learning-based modelling approach coupled with sensor redundancy is developed to model the environmentally dependent soft sensors. Numerous real-time experiments are conducted to test the performance of the sensor and its applicability in closed-loop control tasks at 20 Hz. Our results indicate that the soft sensor can predict force values and orientation angle within 4% and 7% of their total range, respectively

SOFTWARE PROBLEMS OF AN EXPERIMENTAL ROBOT CONTROLLER BASED ON QNX REAL-TIME OPERATING SYSTEMS

At the Department of Automation and Applied Informatics an experimental robot control system has been developed. The purpose of this research is to study modern robot control algorithms and their realization in a real environment. The project focuses on the problems of multiprocessor systems including the task distribution and communication. Another field of this research is to integrate a six-component force-torque sensor into the robot control system and making use of this information in new robot control algorithms. Another purpose of this study is to examine the software problems of an IBM PC-based multiprocessor system controlling a NOKIA-PUMA 560 humanoid robot arm. The features and system services of the new QNX Neutrino operating system is presented in comparison with the previously used QNX v4. The main areas of the version upgrade will be shown focusing on the interprocess communication questions. The processing components of this multiprocessor robot control system with its external interfaces will be discussed later and some further system level development possibilities will be outlined. This final part of the study gives the summary of the architectural and communication requirements of a hybrid position and force control system in the above environment

Visual Servoing in Robotics

Visual servoing is a well-known approach to guide robots using visual information. Image processing, robotics, and control theory are combined in order to control the motion of a robot depending on the visual information extracted from the images captured by one or several cameras. With respect to vision issues, a number of issues are currently being addressed by ongoing research, such as the use of different types of image features (or different types of cameras such as RGBD cameras), image processing at high velocity, and convergence properties. As shown in this book, the use of new control schemes allows the system to behave more robustly, efficiently, or compliantly, with fewer delays. Related issues such as optimal and robust approaches, direct control, path tracking, or sensor fusion are also addressed. Additionally, we can currently find visual servoing systems being applied in a number of different domains. This book considers various aspects of visual servoing systems, such as the design of new strategies for their application to parallel robots, mobile manipulators, teleoperation, and the application of this type of control system in new areas

Quantum Robot: Structure, Algorithms and Applications

A kind of brand-new robot, quantum robot, is proposed through fusing quantum theory with robot technology. Quantum robot is essentially a complex quantum system and it is generally composed of three fundamental parts: MQCU (multi quantum computing units), quantum controller/actuator, and information acquisition units. Corresponding to the system structure, several learning control algorithms including quantum searching algorithm and quantum reinforcement learning are presented for quantum robot. The theoretic results show that quantum robot can reduce the complexity of O(N^2) in traditional robot to O(N^(3/2)) using quantum searching algorithm, and the simulation results demonstrate that quantum robot is also superior to traditional robot in efficient learning by novel quantum reinforcement learning algorithm. Considering the advantages of quantum robot, its some potential important applications are also analyzed and prospected.Comment: 19 pages, 4 figures, 2 table

From Vision Sensor to Actuators, Spike Based Robot Control through Address-Event-Representation

One field of the neuroscience is the neuroinformatic whose aim is to develop auto-reconfigurable systems that mimic the human body and brain. In this paper we present a neuro-inspired spike based mobile robot. From commercial cheap vision sensors converted into spike information, through spike filtering for object recognition, to spike based motor control models. A two wheel mobile robot powered by DC motors can be autonomously controlled to follow a line drown in the floor. This spike system has been developed around the well-known Address-Event-Representation mechanism to communicate the different neuro-inspired layers of the system. RTC lab has developed all the components presented in this work, from the vision sensor, to the robot platform and the FPGA based platforms for AER processing.Ministerio de Ciencia e Innovación TEC2006-11730-C03-02Junta de Andalucía P06-TIC-0141

An AER-Based Actuator Interface for Controlling an Anthropomorphic Robotic Hand

Bio-Inspired and Neuro-Inspired systems or circuits are a relatively novel approaches to solve real problems by mimicking the biology in its efficient solutions. Robotic also tries to mimic the biology and more particularly the human body structure and efficiency of the muscles, bones, articulations, etc. Address-Event-Representation (AER) is a communication protocol for transferring asynchronous events between VLSI chips, originally developed for neuro-inspired processing systems (for example, image processing). Such systems may consist of a complicated hierarchical structure with many chips that transmit data among them in real time, while performing some processing (for example, convolutions). The information transmitted is a sequence of spikes coded using high speed digital buses. These multi-layer and multi-chip AER systems perform actually not only image processing, but also audio processing, filtering, learning, locomotion, etc. This paper present an AER interface for controlling an anthropomorphic robotic hand with a neuro-inspired system.Unión Europea IST-2001-34124 (CAVIAR)Ministerio de Ciencia y Tecnología TIC-2003-08164-C03-0

AER Neuro-Inspired interface to Anthropomorphic Robotic Hand

Address-Event-Representation (AER) is a communication protocol for transferring asynchronous events between VLSI chips, originally developed for neuro-inspired processing systems (for example, image processing). Such systems may consist of a complicated hierarchical structure with many chips that transmit data among them in real time, while performing some processing (for example, convolutions). The information transmitted is a sequence of spikes coded using high speed digital buses. These multi-layer and multi-chip AER systems perform actually not only image processing, but also audio processing, filtering, learning, locomotion, etc. This paper present an AER interface for controlling an anthropomorphic robotic hand with a neuro-inspired system.Unión Europea IST-2001-34124 (CAVIAR)Ministerio de Ciencia y Tecnología TIC-2003-08164-C03-02Ministerio de Ciencia y Tecnología TIC2000-0406-P4- 0