从有缆遥控水下机器人到自治水下机器人

文章给出了水下机器人的定义,依据定义进行了分类,简要回顾了败类 重要水下机器人的进展,指出了无人无缆自治水下机器人（AUVs)是当今水下机器人研究与开发的热点,介绍了最近20年沈阳自动化研究所与国内外有关单位合作,在水下机器人领域从无人有缆遥控水下机器人（ROVs)到AUVs的研究开发工作,它从一个侧面反映了我国在这一领域的进展情况。     

智能水下机器人声视觉跟踪系统研究

提出了一个新的水下声视觉图像预处理、分割和目标跟踪的处理系统框架.采用该系统框架,设计了一个基于前视声纳的智能水下机器人(AUV)声视觉目标探测跟踪系统,并描述了该系统的软、硬件体系结构.针对水下声视觉图像特点,分析了声纳图像的预处理方法,探讨了图像中特征信息的选取,构造了基于不变矩的仿射变换不变量,提出了基于组合特征...     

水下蛇形机器人的滑翔运动性能研究

结合水下滑翔机在海洋中的较强续航能力,以及蛇形机器人在水中的良好机动性能,研制了一种具有两者特性的新型水下滑翔蛇形机器人,它具有水下滑翔机续航时间长、航行距离远,以及水下蛇形机器人机动性强、运动灵活的运动特性。对该水下滑翔蛇形机器人的滑翔运动性能进行了试验研究。首先对水下滑翔蛇形机器人的运动原理及关节结构进行了设计分析,其次对机器人的硬件及控制系统进行了结构分析,而且根据动量定理和动量矩定理,对机器人的滑翔运动方程进行了推导,并化简到垂直平面。最后对平衡状态进行了仿真分析,对机器人的运动能力进行了试验验证。试验结果验证了水下滑翔蛇形机器人机构的有效性。     

基于遗传算法的家用保安机器人路径规划方法

将领域知识与遗传算法相结合,提出了一种针对家用保安机器人的路径规划方法.该算法采用改进的栅格化方法来描述家庭环境,重新定义了路径适应度函数的评价方法,并设计有效的路径遗传算子.仿真结果表明了该算法的正确性和有效性.利用该算法实现了在实际家庭环境下保安机器人的路径规划与动态避障.     

基于避障区域的足球机器人路径规划方法

提出了一种基于避障区域的机器人运动路径的规划方法,并通过仿真实验验证了这种方法的有效性。仿真结果表明,该方法很好地实现了机器人避障,而且与其他方法相比有如下优点：（1）通过划分避障区域,极大地减少了计算量;（2）采用解三角形的方法判断机器人是否处于避障区内,方法简单有效;（3）通过定义两个集合和在其上的两种运算来构造网格,方法简单可行。     

用于水下微机器人驱动的智能执行材料的制备和驱动特性研究

智能材料具有感知和执行功能，近年来受到广泛研究。在微机器人领域智能材料作为微驱动器，有着广泛的应用前景。本实验制备了一种铁磁性智能执行材料．并研究了该材料在磁场下的形变特性。采用该材料作微执行器制作出了水下微机器人模型。实验表明，该模型在交变磁场的作用下．微执行器将做高频率划动．使水下微机器人模型能够在水中产生运动。这种外场驱动方法和材料在医学领域有着良好的应用前景。     

室内地面清洁机器人路径规划

采用栅格法建立环境地图模型,利用沿边走的路径规划算法进行室内地面清洁机器人无障碍与避障路径规划与仿真试验.结果表明,在静态结构化环境中,清洁机器人能够沿内螺旋式“回”字型路径完成清扫任务,并成功避开障碍物和边界,自动定位和转向,清洁完毕机器人能够自动返回到初始位置.这说明沿边走的内螺旋式“回”字型路径规划方式是可行的.     

无缆水下机器人水声图象处理系统设计

水声图象处理系统是无缆水下机器人的重要智能系统，它以ＴＭＳ３２０Ｃ３０高速数字信号处理器为核心，实时地完成水声图象压缩和水声目标参数计算（包括妨碍航行的障碍识别）等功能，本文给出了该系统软件、硬件的设计以及水池实验结果。     

一种新型包装码垛机器人路径规划方法

目的为了提高码垛机器人的工作效率,减小能量损耗,优化机器人末端抓手的工作轨迹。方法建立机器人路径规划的数学模型,在此基础上对传统的蚁群算法进行改进,将环境中局部的机器人路径信息引入蚁群信息素的初始化和路径选择概率中,提高蚁群算法的收敛速度,并防止算法早熟,避免算法陷入局部最优。结果仿真结果表明,改进后的蚁群算法收敛速度更快,能够在较短时间内规划出最佳路径。结论所提方法能够明显提高码垛机器人最佳路径搜索能力,对于提升机器人运行效率具有重要指导意义。     

Lever Arm Compensation of Autonomous Underwater Vehicle for Fast Transfer Alignment

Transfer alignment is used to initialize SINS (Strapdown Inertial Navigation System) in motion. Lever-arm effect compensation is studied existing in an AUV (Autonomous Underwater Vehicle) before launched from the mother ship. The AUV is equipped with SINS, Doppler Velocity Log, depth sensor and other navigation sensors. The lever arm will cause large error on the transfer alignment between master inertial navigation system and slave inertial navigation system, especially in big ship situations. This paper presents a novel method that can effectively estimate and compensate the flexural lever arm between the main inertial navigation system mounted on the mother ship and the slave inertial navigation system equipped on the AUV. The nonlinear measurement equation of angular rate is derived based on three successive rotations of the body frame of the master inertial navigation system. Nonlinear filter is utilized as the nonlinear estimator for its capability of non-linear approximation. Observability analysis was conducted on the SINS state vector based on singular value decomposition method. State equation of SINS was adopted as the system state equation. Simulation experiments were conducted and results showed that the proposed method can estimate the flexural lever arm more accurately, the precision of transfer alignment was improved and alignment time was shortened accordingly.     

A Hybrid Path Planning Method Based on Articulated Vehicle Model

Due to the unique steering mechanism and driving characteristics of the articulated vehicle, a hybrid path planning method based on the articulated vehicle model is proposed to meet the demand of obstacle avoidance and searching the path back and forth of the articulated vehicle. First, Support Vector Machine (SVM) theory is used to obtain the two-dimensional optimal zero potential curve and the maximum margin, and then, several key points are selected from the optimal zero potential curves by using Longest Accessible Path (LAP) method. Next, the Cubic Bezier (CB) curve is adopted to connect the curve that satisfies the curvature constraint of the articulated vehicle between every two key points. Finally, Back and Forth Rapidly-exploring Random Tree with Course Correction (BFRRT-CC) is designed to connect paths that do not meet articulated vehicle curvature requirements. Simulation results show that the proposed hybrid path planning method can search a feasible path with a 90-degree turn, which meets the demand for obstacle avoidance and articulated vehicle back-and-forth movement.     

基于路径预测的自主车最优跟踪控制

针对自主车,提出了高速公路交通环境下的一种快速路径预测算法.通过引入一个车辆运动学预瞄模型,对自主车未来的行驶位置进行估计.并结合所提路径算法给出的目标道路位置,计算预测误差.设计了基于预测误差的最优反馈控制器用于实现路径跟踪.CarSim+Simulink仿真结果表明:所提最有控制器保证自主车在速度v＜16 m/s时...     

基于遇障速度法足球机器人的路径规划

提出了机器人在动态环境下的路径规划方法。这种方法基于机器人运动速度信息制定的避障策略。通过遇障速度的几何变换产生可达避障速度，从而确定运动路径上潜在的障碍物。同时，还推导了机器人路径搜索树网格算法。足球机器人仿真比赛表明，这种方法适用于动态和静态障碍物的避障。     

一种基于神经网络的移动机器人路径规划算法

针对结构化环境下移动机器人的路径规划问题，提出了一种基于神经网络的路径规划算法。该算法利用神经网络描述环境约束并计算碰撞能量 函数。采用了一种离散化的方法逼近能量的负梯度方向，从而确定路径点集的运动趋向。最后利用计算机仿真分析了该算法的性能和效率。     

Novel Algorithm for Mobile Robot Path Planning in Constrained Environment

This paper presents a development of a novel path planning algorithm, called Generalized Laser simulator (GLS), for solving the mobile robot path planning problem in a two-dimensional map with the presence of constraints. This approach gives the possibility to find the path for a wheel mobile robot considering some constraints during the robot movement in both known and unknown environments. The feasible path is determined between the start and goal positions by generating wave of points in all direction towards the goal point with adhering to constraints. In simulation, the proposed method has been tested in several working environments with different degrees of complexity. The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. The results revealed that the proposed method has shortest path length, less computational time and the best smooth path. As an average, GLS is faster than A* and LS by 7.8 and 5.5 times, respectively and presents a path shorter than A* and LS by 1.2 and 1.5 times. In order to verify the performance of the developed method in dealing with constraints, an experimental study was carried out using a Wheeled Mobile Robot (WMR) platform in labs and roads. The experimental work investigates a complete autonomous WMR path planning in the lab and road environments using a live video streaming. Local maps were built using data from a live video streaming with real-time image processing to detect segments of the analogous-road in lab or real-road environments. The study shows that the proposed method is able to generate shortest path and best smooth trajectory from start to goal points in comparison with laser simulator.     

基于拓扑降维法路径规划的状态空间划分原则

在拓扑降维法理论的基础上，提出了划分状态空间的一个原则，即用机器人肘关节运动禁止区划分机器人腰关节角度集合，并对状态空早分原则做了归纳和总结。     

运动学约束情况下的移动机器人导航控制研究

对未知环境下的移动机器人导航与避障进行了研究。在导航的过程中考虑了移动机器人的非完整运动学约束。机器人采用三个距离传感器从三个方向实时探测环境中的障碍,其运动方向根据目标位置和传感器的探测数据进行实时规划。在本文设计的一种新的导航控制作用下,机器人在满足运动学约束的情况下可以实时跟踪奔向目标行为和避悼行为规划的路径,以接近最优的轨迹避开环境中的障碍并到达目标。仿真结果表明了该方法的有效性。