A Flexible Image Processing Framework for Vision-based Navigation Using Monocular Image Sensors

On-Orbit Servicing (OOS) encompasses all operations related to servicing satellites and performing other work on-orbit, such as reduction of space debris. Servicing satellites includes repairs, refueling, attitude control and other tasks, which may be needed to put a failed satellite back into working condition. A servicing satellite requires accurate position and orientation (pose) information about the target spacecraft. A large quantity of different sensor families is available to accommodate this need. However, when it comes to minimizing mass, space and power required for a sensor system, mostly monocular imaging sensors perform very well. A disadvantage is- when comparing to LIDAR sensors- that costly computations are needed to process the data of the sensor. The method presented in this paper is addressing these problems by aiming to implement three different design principles; First: keep the computational burden as low as possible. Second: utilize different algorithms and choose among them, depending on the situation, to retrieve the most stable results. Third: Stay modular and flexible. The software is designed primarily for utilization in On-Orbit Servicing tasks, where- for example- a servicer spacecraft approaches an uncooperative client spacecraft, which can not aid in the process in any way as it is assumed to be completely passive. Image processing is used for navigating to the client spacecraft. In this specific scenario, it is vital to obtain accurate distance and bearing information until, in the last few meters, all six degrees of freedom are needed to be known. The smaller the distance between the spacecraft, the more accurate pose estimates are required. The algorithms used here are tested and optimized on a sophisticated Rendezvous and Docking Simulation facility (European Proximity Operations Simulator- EPOS 2.0) in its second-generation form located at the German Space Operations Center (GSOC) in Weßling, Germany. This particular simulation environment is real-time capable and provides an interface to test sensor system hardware in closed loop configuration. The results from these tests are summarized in the paper as well. Finally, an outlook on future work is given, with the intention of providing some long-term goals as the paper is presenting a snapshot of ongoing, by far not yet completed work. Moreover, it serves as an overview of additions which can improve the presented method further

Design and Control of a Flight-Style AUV with Hovering Capability

The small flight-style Delphin AUV is designed to evaluate the performance of a long range survey AUV with the additional capability to hover and manoeuvre at slow speed. Delphin’s hull form is based on a scaled version of Autosub6000, and in addition to the main thruster and control surfaces at the rear of the vehicle, Delphin is equipped with four rim driven tunnel thrusters. In order to reduce the development cycle time, Delphin was designed to use commercial-off-the-shelf (COTS) sensors and thrusters interfaced to a standard PC motherboard running the control software within the MS Windows environment. To further simplify the development, the autonomy system uses the State-Flow Toolbox within the Matlab/Simulink environment. While the autonomy software is running, image processing routines are used for obstacle avoidance and target tracking, within the commercial Scorpion Vision software. This runs as a parallel thread and passes results to Matlab via the TCP/IP communication protocol. The COTS based development approach has proved effective. However, a powerful PC is required to effectively run Matlab and Simulink, and, due to the nature of the Windows environment, it is impossible to run the control in hard real-time. The autonomy system will be recoded to run under the Matlab Windows Real-Time Windows Target in the near future. Experimental results are used to demonstrating the performance and current capabilities of the vehicle are presented

Wireless industrial intelligent controller for a non-linear system

Modern neural network (NN) based control schemes have surmounted many of the limitations found in the traditional control approaches. Nevertheless, these modern control techniques have only recently been introduced for use on high-specification Programmable Logic Controllers (PLCs) and usually at a very high cost in terms of the required software and hardware. This ‗intelligent‘ control in the sector of industrial automation, specifically on standard PLCs thus remains an area of study that is open to further research and development. The research documented in this thesis examined the effectiveness of linear traditional control schemes such as Proportional Integral Derivative (PID), Lead and Lead-Lag control, in comparison to non-linear NN based control schemes when applied on a strongly non-linear platform. To this end, a mechatronic-type balancing system, namely, the Ball-on-Wheel (BOW) system was designed, constructed and modelled. Thereafter various traditional and intelligent controllers were implemented in order to control the system. The BOW platform may be taken to represent any single-input, single-output (SISO) non-linear system in use in the real world. The system makes use of current industrial technology including a standard PLC as the digital computational platform, a servo drive and wireless access for remote control. The results gathered from the research revealed that NN based control schemes (i.e. Pure NN and NN-PID), although comparatively slower in response, have greater advantages over traditional controllers in that they are able to adapt to external system changes as well as system non-linearity through a process of learning. These controllers also reduce the guess work that is usually involved with the traditional control approaches where cumbersome modelling, linearization or manual tuning is required. Furthermore, the research showed that online-learning adaptive traditional controllers such as the NN-PID controller which maintains the best of both the intelligent and traditional controllers may be implemented easily and with minimum expense on standard PLCs

Image Processing Application Development: From Rapid Prototyping to SW/HW Co-simulation and Automated Code Generation

Nowadays, the market-place offers quite powerful and low cost reconfigurable hardware devices and a wide range of software tools which find application in the image processing field. However, most of the image processing application designs and their latter deployment on specific hardware devices is still carried out quite costly by hand. This paper presents a new approach to image processing application development, which tackles the historic question of how filling the gap existing between rapid throwaway software designs and final software/hardware implementations. A new graphical component-based tool has been implemented which allows to comprehensively develop this kind of applications, from functional and architectural prototyping stages to software/hardware co-simulation and final code generation. Building this tool has been possible thanks to the synergy that arises from the integration of several of the pre-existent software and hardware image processing libraries and tools.COSIVA (TIC 2000-1765-C03-02),EFTCOR (DPI2002-11583-E), PMPDI-UPCT-2004Escuela Técnica Superior de Ingeniería de Telecomunicació

Biblioteca para diseño basado en modelos de algoritmos de procesado de imágenes en FPGA

This paper describes a library (XSGImgLib) that includes parameterizable blocks to implement low-level image processing tasks on FPGAs. A modelbased design technique provided by Xilinx System Generator (XSG) has been used to design the blocks, which implement point operation (binarization) and neighborhood operations (linear and non-linear filtering) in grayscale images. The blocks are parameterizable for input/output data precision, window size, normalization strategy, and implementation options (area versus speed optimization). The paper includes the implementation results obtained after fixing these options and exemplifies the combination of several blocks of the library to build a complete design for image segmentation purposes.Este artículo describe una biblioteca de bloques parametrizables (XSGImgLib) para la implementación de tareas de procesado de imágenes en FPGA. Se ha utilizado la técnica de diseño basado en modelos proporcionada por Xilinx System Generator (XSG) para diseñar diferentes bloques de procesado que implementan operaciones puntuales (binarización) y basadas en vecindad (filtros lineales y no-lineales) para imágenes en escala de grises. La parametrización de los bloques permite configurar la precisión de los datos de entrada/salida, el tamaño de la ventana, la estrategia de normalización y distintas opciones de implementación (optimización en área o velocidad). El artículo muestra los resultados de implementación para las diferentes opciones de configuración y ejemplifica la combinación de los bloques de procesado en el desarrollo de un sistema para segmentado de imágenes.Agencia Española de Cooperación Internacional para el Desarrollo PCID/024124/09, PCID/030769/1