A novel system architecture for real-time low-level vision

A novel system architecture that exploits the spatial locality in memory access that is found in most low-level vision algorithms is presented. A real-time feature selection system is used to exemplify the underlying ideas, and an implementation based on commercially available Field Programmable Gate Arrays (FPGA’s) and synchronous SRAM memory devices is proposed. The peak memory access rate of a system based on this architecture is estimated at 2.88 G-Bytes/s, which represents a four to five times improvement with respect to existing reconfigurable computers

A versatile and reconfigurable microassembly workstation

In this paper, a versatile and reconfigurable microassembly workstation designed and realized as a research tool for investigation of the problems in microassembly and micromanipulation processes and recent developments on mechanical and control structure of the system with respect to the previous workstation are presented. These developments include: (i) addition of a manipulator system to realize more complicated assembly and manipulation tasks, (ii) addition of extra DOF for the vision system and sample holder stages in order to make the system more versatile (iii) a new optical microscope as the vision system in order to visualize the microworld and determine the position and orientation of micro components to be assembled or manipulated, (iv) a modular control system hardware which allows handling more DOF. In addition several experiments using the workstation are presented in different modes of operation like tele-operated, semiautomated and fully automated by means of visual based schemes

A generic implementation framework for stereo matching algorithms

Traditional area-based matching techniques make use of similarity metrics such as the Sum of Absolute Differences(SAD), Sum of Squared Differences (SSD) and Normalised Cross Correlation (NCC). Non-parametric matching algorithms such as the rank and census rely on the relative ordering of pixel values rather than the pixels themselves as a similarity measure. Both traditional area-based and non-parametric stereo matching techniques have an algorithmic structure which is amenable to fast hardware realisation. This investigation undertakes a performance assessment of these two families of algorithms for robustness to radiometric distortion and random noise. A generic implementation framework is presented for the stereo matching problem and the relative hardware requirements for the various metrics investigated

Telepresence and Space Station Freedom workstation operations

The Space Station Freedom workstation system is a distributed network of computer based workstations that provides the man-machine interfaces for controlling space station systems. This includes control of external manipulator, robotic and free flyer devices by crewmembers in the space station's pressurized shirt-sleeve environment. These remotely controlled devices help minimize the requirement for costly crew extravehicular activity (EVA) time for such tasks as station assembly and payload support. Direct window views may be used for controlling some of the systems, but many activities will be remote or require levels of detail not possible by direct observation. Since controlling remote devices becomes more difficult when direct views are inadequate or unavailable, many performance enhancing techniques have been considered for representing information about remote activities to the operator. Described here are the telepresence techniques under consideration to support operations and training. This includes video enhancements (e.g., graphic and text overlays and stereo viewing), machine vision systems, remote activity animation, and force reflection representation

FPGA-based High-Performance Collision Detection: An Enabling Technique for Image-Guided Robotic Surgery

Collision detection, which refers to the computational problem of finding the relative placement or con-figuration of two or more objects, is an essential component of many applications in computer graphics and robotics. In image-guided robotic surgery, real-time collision detection is critical for preserving healthy anatomical structures during the surgical procedure. However, the computational complexity of the problem usually results in algorithms that operate at low speed. In this paper, we present a fast and accurate algorithm for collision detection between Oriented-Bounding-Boxes (OBBs) that is suitable for real-time implementation. Our proposed Sweep and Prune algorithm can perform a preliminary filtering to reduce the number of objects that need to be tested by the classical Separating Axis Test algorithm, while the OBB pairs of interest are preserved. These OBB pairs are re-checked by the Separating Axis Test algorithm to obtain accurate overlapping status between them. To accelerate the execution, our Sweep and Prune algorithm is tailor-made for the proposed method. Meanwhile, a high performance scalable hardware architecture is proposed by analyzing the intrinsic parallelism of our algorithm, and is implemented on FPGA platform. Results show that our hardware design on the FPGA platform can achieve around 8X higher running speed than the software design on a CPU platform. As a result, the proposed algorithm can achieve a collision frame rate of 1 KHz, and fulfill the requirement for the medical surgery scenario of Robot Assisted Laparoscopy.published_or_final_versio