淬透性曲线应用系统软件

利用VISUAL BASICA6．0在计算机上建立了常用钢种淬透性曲线，并利用淬透性曲线和建立的数据库自动完成相关的作图和计算。     

MOTOMAN-UP系列机器人离线编程系统

采用VISUAL C 6.0及OpenGL技术开发了MOTOMAN-UP系列弧焊机器人离线编程系统.建立了MOTOMAN-UP系列机器人D-H坐标系及连杆参数表,编写了运动学逆解模块;针对典型马鞍形工件的特点,规划出焊枪的运动路径与姿态,且按比例同步显示工件;集成了机器人通信模块MOTOCOM32和运动学仿真模块ROTSY并同步导入马鞍形工件,不仅能单步生成作业指令,且可自动生成作业程序.通过对焊接过程进行离线仿真试验及传输作业实焊,验证该系统是切实可行的.     

运用VISUAL FOXPRO编程技术开发电厂检修物资管理系统

分析了计算机技术在发电厂物资管理工作中实际应用情况及存在的问题，并有针对性地提出了运用VISUAL FOXPRO面向对象编程技术，编制开发出适合电厂自身检修物资管理工作的应用软件。介绍了系统开发的技术背景、开发工作的流程、系统的主要功能和结构等，阐明了基层单位利用自身力量开发适用软件的积极意义，对进一步搞好电厂各方面管理工作有一定的启示作用。     

集装箱操作系统的设计与实现

本文通过对集装箱操作系统(CTOS)主要功能模块的介绍,结合实际开发过程当中的实现方法,对集装箱操作系统的设计与实现进行了探讨,同时对其未来的发展趋势做一下展望。     

高扭曲向列液晶盒工作特性研究

利用VISUAL LCD对高扭曲向列液晶盒的透过率-电压特性、对比度-视角特性、透过率-视角特性及动态响应特性进行了模拟。详细分析了液晶盒参数、液晶材料参数、外加电压对液晶显示器特性曲线的影响,并重点介绍了影响对比度、视角、动态响应特性的因素及如何提高响应速度使其满足视频图像显示的需要;研究发现该常白型显示模式基本无色散,并具有较大的视角、良好的透过率和对比度特性,适用于高品质显示。     

Sensor-based probabilistic roadmaps: experiments with an eye-in-hand system

We present a real implemented eye-in-hand test-bed system for sensor-based collision-free motion planning for articulated robot arms. The system consists of a PUMA 560 with a triangulation-based area-scan laser range finder (the eye) mounted on its wrist. The framework for our planning approach is inspired by recent motion planning research for the classical model-based case (known environment) and incrementally builds a roadmap that represents the connectivity of the free configuration space, as the robot senses the physical environment. We present some experimental results with our sensor-based planner running on this real test-bed. The robot is started in completely unknown and cluttered environments. Typically, the planner is able to reach (planning as it senses) the goal configuration in about 7-25 scans (depending on the scene complexity), while avoiding collisions with the obstacles throughout.     

First results in omni-directional visual servoing

In this paper, we describe a visual servoing system developed as a human-robot interface to drive a mobile robot toward any chosen target. An omni-directional camera is used to get the 360° of field of view and an efficient tracking technique is developed to track the target. The use of the omni-directional geometry eliminates many of the problems common in visual tracking and makes the use of visual servoing a practical alternative for robot-human interaction. The experiments demonstrate that it is an effective and robust way to guide a robot. In particular, the experiments show robustness of the tracker to loss of template, vehicle motion, and change in scale and orientation.     

A Robust Solution to the Stereo-Vision-Based Simultaneous Localization and Mapping Problem with Steady and Moving Landmarks

The problem of visual simultaneous localization and mapping (SLAM) is examined in this paper using recently developed ideas and algorithms from modern robust control and estimation theory. A nonlinear model for a stereo-vision-based sensor is derived that leads to nonlinear measurements of the landmark coordinates along with optical flow-based measurements of the relative robot–landmark velocity. Using a novel analytical measurement transformation, the nonlinear SLAM problem is converted into the linear domain and solved using a robust linear filter. Actually, the linear filter is guaranteed stable and the SLAM state estimation error is bounded within an ellipsoidal set. A mathematically rigorous stability proof is given that holds true even when the landmarks move in accordance with an unknown control input. No similar results are available for the commonly employed extended Kalman filter, which is known to exhibit divergence and inconsistency characteristics in practice. A number of illustrative examples are given using both simulated and real vision data that further validate the proposed method.     

Inevitable collision states — a step towards safer robots?

An inevitable collision state for a robotic system can be defined as a state for which, no matter what the future trajectory followed by the system is, a collision with an obstacle eventually occurs. An inevitable collision state takes into account the dynamics of both the system and the obstacles, fixed or moving. The main contribution of this paper is to lay down and explore this novel concept (and the companion concept of inevitable collision obstacle). Formal definitions of the inevitable collision states and obstacles are given. Properties fundamental for their characterization are established. This concept is very general, and can be useful both for navigation and motion planning purposes (for its own safety, a robotic system should never find itself in an inevitable collision state). To illustrate the interest of this concept, it is applied to a problem of safe motion planning for a robotic system subject to sensing constraints in a partially known environment (i.e. that may contain unexpected obstacles). In safe motion planning, the issue is to compute motions for which it is guaranteed that, no matter what happens at execution time, the robotic system never finds itself in a situation where there is no way for it to avoid collision with an unexpected obstacle.     

Self-organization of Dynamic Object Features Based on Bidirectional Training

This paper presents a method to self-organize object features that describe object dynamics using bidirectional training. The model is composed of a dynamics learning module and a feature extraction module. Recurrent Neural Network with Parametric Bias (RNNPB) is utilized for the dynamics learning module, learning and self-organizing the sequences of robot and object motions. A hierarchical neural network is linked to the input of RNNPB as the feature extraction module for self-organizing object features that describe the object motions. The two modules are simultaneously trained through bidirectional training using image and motion sequences acquired from the robot's active sensing with objects. Experiments are performed with the robot's pushing motion with a variety of objects to generate sliding, falling over, bouncing and rolling motions. The results have shown that the model is capable of self-organizing object dynamics based on the self-organized features.