An artificial life approach to dense stereo disparity

This article presents an adaptive approach to improving the infection algorithm that we have used to solve the dense stereo matching problem. The algorithm presented here incorporates two different epidemic automata along a single execution of the infection algorithm. The new algorithm attempts to provide a general behavior of guessing the best correspondence between a pair of images. Our aim is to provide a new strategy inspired by evolutionary computation, which combines the behaviors of both automata into a single correspondence problem. The new algorithm will decide which automata will be used based on the transmission of information and mutation, as well as the attributes, texture, and geometry, of the input images. This article gives details about how the rules used in the infection algorithm are coded. Finally, we show experiments with a real stereo pair, as well as with a standard test bed, to show how the infection algorithm works.     

多目移动机器人实验平台的研究

带有多目视觉系统的移动机器人能在同一时间获取更多关于周围环境的信息,从而可以更好地判断周围环境的情况以及自身的处境。提出一种基于双目立体视觉、全景视觉、低位避障视觉的多目视觉移动机器人实验平台,介绍该系统的硬件结构、电机驱动系统、软件结构,重点分析视觉系统的构成与功能。该移动机器人在同一时刻能获得丰富的周围环境信息,从而可以更快地进行自我定位、目标跟踪以及路径规划。     

Stereo-disparity perception for a monochromatic flat slope based on a neural network dynamic model

Stereo-matching is one of the most active research topics in computer vision. In this article, the stereo-correspondence problem for a stereo-image pair on a monochromatic surface is considered. Even if some hints exist, it is not easy to reconstruct the correct 3-D scene from two images because it is an ill-posed problem. We have modified our previous competitive and cooperative neural network model so that we can efficiently perceive a monochromatic surface which is enclosed by two vertical stripes. The modification consists of two factors: (1) combining the parameterized multiple inputs (similarities); (2) extending the cooperative terms of the neural network equation. The effect of the proposed model is examined by experiments with both synthetic and real stereo-image pairs. For the real images, a segmentation method is proposed to deal with the similarity maps. This work was presented, in part, at the Seventh International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

基于PSO/GA的立体视觉测量系统优化布局

探讨一种基于PSO/GA（粒子群优化/遗传算法）混合算法的立体视觉测量系统优化布局方法。以空间点目标的三维重构不确定度最小为目标,构建了立体视觉测量系统优化布局的目标函数。通过实例阐述了使用PSO/GA混合算法求解系统最优布局参数的过程,并且在MATLAB环境下对该方法做了验证。仿真实验结果表明：与传统的粒子群优化算法和遗传算法相比,使用PSO/GA混合算法得到的最佳个体适应度曲线上升速度最快,而且求得的系统最优布局参数使空间点目标的三维重构不确定度最小。     

Real-time stereo matching using memory-efficient Belief Propagation for high-definition 3D telepresence systems

New generations of telecommunications systems will include high-definition 3D video that provides a telepresence feeling. These systems require high-quality depth maps to be generated in a very short time (very low latency, typically about 40 ms). Classical Belief Propagation algorithms (BP) generate high-quality depth maps but they require huge memory bandwidths that limit low-latency implementations of stereo-vision systems with high-definition images.This paper proposes a real-time (latency inferior to 40 ms) high-definition (1280 × 720) stereo matching algorithm using Belief Propagation with good immersive feeling (80 disparity levels). There are two main contributions. The first is an improved BP algorithm with pixel classification that outperforms classical BP while reducing the number of memory accesses. The second is an adaptive message compression technique with a low performance penalty that greatly reduces the memory traffic. The combination of these techniques outperforms classical BP by about 6.0% while reducing the memory traffic by more than 90%.     

Development of a Robotic System which Assists Unmanned Production Based on Cooperation between Off-Line Robots and On-line Robots. Part 3. 1 Development of an Off-Line Robot, Autonomous Navigation, and Detection of Faulty Workpieces in a Vibrating Parts Feeder

Remarkable advances in robotics and intelligent technology have made unmanned production realisable. Based on the off-line robot concept proposed in our first paper, an off-line robot and peripheral devices have been developed for the realisation of unmanned production. The developed robot has a power-wheeled steering (PWS) type mobile platform on which a double-arm manipulator is installed. In order to detect and recognise 3D objects, double CCD cameras are mounted on the top of the robot. Two types of robot end-effectors are developed to handle workpieces and conduct trouble shooting actions. A newly developed production trouble simulator is very useful in simulating and resolving production troubles. A virtual pilot plant for production composed of the off-line robot, two on-line robots, a vibrating bowl feeder, a belt conveyor and a production trouble simulator has been constructed and tests for production simulation have been undertaken. In this paper, autonomous navigation of the developed robot in the virtual pilot plant is investigated. Then a search for faulty parts in a parts feeder using the developed real-time image extraction method is carried out.     

Cooperative multi-robot systems:: A study of vision-based 3-D mapping using information theory

Building cooperatively 3-D maps of unknown environments is one of the application fields of multi-robot systems. This article addresses that problem through a probabilistic approach based on information theory. A distributed cooperative architecture model is formulated whereby robots exhibit cooperation through efficient information sharing. A probabilistic model of a 3-D map and a statistical sensor model are used to update the map upon range measurements, with an explicit representation of uncertainty through the definition of the map’s entropy. Each robot is able to build a 3-D map upon measurements from its own range sensor and is committed to cooperate with other robots by sharing useful measurements. An entropy-based measure of information utility is used to define a cooperation strategy for sharing useful information, without overwhelming communication resources with redundant or unnecessary information. Each robot reduces the map’s uncertainty by exploring maximum information viewpoints, by using its current map to drive its sensor to frontier regions having maximum entropy gradient. The proposed framework is validated through experiments with mobile robots equipped with stereo-vision sensors.     

立体视觉测量中的摄像机优化布局

通过合理布置摄像机的安装方位,可迸一步提高立体视觉测量系统的测量精度.将遗传算法应用于求解摄像机优化布局的问题,以摄像机安装方位参数为优化变量,并将摄像机优化布局的目标确定为:寻求最佳的摄像机安装方位参数,使空间点目标的三维重构不确定度最小.采用三维重构不确定度两阶估计方法,即同时考虑摄像机标定和空间点目标三维重构过程中的不确定度传递问题.在Matlab环境下,利用GATBX遗传算法工具箱对该方法进行验证.仿真实验结果表明:经过50代遗传迭代后,可得到优化变量的最优解.