基于双目视觉导航的仿生机器人鲁棒控制算法

仿生机器人在定姿过程中受到空间扰动因素的影响容易产生控制误差,需要对机器人进行精确标定,提高仿生机器人的定位控制精度,因此提出一种基于双目视觉导航的仿生机器人鲁棒控制算法。利用光学CCD双目视觉动态跟踪系统进行仿生机器人的末端位姿参量测量,建立被控对象的运动学模型;以机器人的转动关节的6自由度参量为控制约束参量,建立机器人的分层子维空间运动规划模型;采用双目视觉跟踪方法实现仿生机器人的位姿自适应修正,实现鲁棒性控制。仿真结果表明,采用该方法进行仿生机器人控制的姿态定位时对机器人末端位姿参量的拟合误差较低,动态跟踪性能较好。     

双目立体视觉栅格地图构建方法

本文基于立体视觉定位技术,提出了基于双目立体视觉的栅格地图构建方法,用以解决目前视觉SLAM技术构建的稀疏特征地图难以直接用于自主导航的问题。本文提出的方法仅以视觉信息作为输入实时完成移动机器人自定位与外界环境栅格地图的构建。首先采用双目立体视觉定位获取机器人运动参数,利用稠密匹配估算空间点云分布,在考虑机器人实际高度的情况下将三维点云投影成二维数据,最后通过二值贝叶斯滤波器在线构建栅格地图。本文所构建的栅格地图包含环境几何信息,可直接应用于机器人路径规划与导航。实验结果验证了本文所以出的定位与地图构建方法的可行性。     

基于投影直方图匹配的双目视觉跟踪算法

为了在机器人机械手双目视觉伺服系统中跟踪并精确定位目标的空间位置,提出了一种利用投影直方图匹配和极线几何约束的目标跟踪方法。分别在2个视觉中人工标定目标,并提取目标在多颜色空间的水平、垂直投影直方图作为匹配模板;在一个视觉中利用目标的运动一致性原则和投影直方图匹配搜索并跟踪目标;在另一个视觉中依据双目视觉系统的极线几何原理限定目标搜索范围,搜索并定位目标。该方法利用水平、垂直投影直方图描述目标的结构信息,同时完成了双目视觉系统中的目标跟踪与配准功能,有利于目标的精确定位和视觉测量。实验结果表明,该方法可在双目视觉系统中有效跟踪目标,运算效率高,鲁棒性强。     

利用平面单应分解实现服务机器人视觉伺服

智能空间中家庭服务机器人所需完成的主要任务是协助人完成物品的搜寻、定位与传递。而视觉伺服则是完成上述任务的有效手段。搭建了由移动机器人、机械臂、摄像头组成的家庭服务机器人视觉伺服系统,建立了此系统的运动学模型并对安装在机械臂末端执行器上的视觉系统进行了内外参数标定,通过分解世界平面的单应来获取目标物品的位姿参数,利用所获取的位姿参数设计了基于位置的视觉伺服控制律。实验结果表明,使用平面单应分解方法来设计控制律可简单有效地完成家庭物品的视觉伺服任务。     

空间机器人捕获非合作目标的测量与规划方法

提出了基于立体视觉的空间机器人捕获非合作目标的测量与规划方法,包括图像处理与特征提取、3D 重构及位姿测量、自主规划与控制等．同时,还建立了一套仿真系统,可进行包括图像采集、位姿测量、追踪星 GNC、空间机器人规划与控制、航天器动力学计算等在内的闭环仿真．仿真结果验证了算法的有效性．     

基于视觉FastSLAM的移动机器人自主探索方法*

针对室内环境下机器人的移动和定位需要,提出基于视觉FastSLAM的移动机器人自主探索方法.该方法综合考虑信息增益和路径距离,基于边界选取探索位置并规划路径,最大化机器人的自主探索效率,确保探索任务的完整实现.在FastSLAM 2.0的基础上,利用视觉作为观测手段,有效融合全景扫描和地标跟踪方法,提高数据观测效率,并且引入地标视觉特征增强数据关联估计,完成定位和地图绘制.实验表明,文中方法能正确选取最优探索位置并合理规划路径,完成探索任务,并且定位精度和地图绘制精度较高,鲁棒性较好.     

机器人抓取视觉传感目标精确定位方法

机器人抓取目标时,准确完成任务的前提是可以精准检测到目标位置,当距离目标较远时,以信号传感为基础的定位精度和稳定性会受到影响。为解决上述问题,提出基于视觉传感器的机器人抓取目标精确定位方法。利用视觉传感器获取目标图像,并标定目标位姿。采取直线段检测方法提取目标位姿特征,将提取的特征输入到改进粒子群算法的支持向量机回归模型中,输出定位结果。利用回归误差补偿模型对定位结果补偿,完成机器人抓取目标精确定位。实验结果显示,利用视觉传感器后,机器人抓取目标的定位时间为35s、与实际位置的接近程度高于81%、置信度高于92%,由此可知机器人抓取视觉传感目标定位效果较好。     

基于多传感器的大口径器件自动对准策略

针对大口径器件的装配, 基于搭建的实验平台, 提出了一种多传感器反馈的分阶段自动对准策略, 实现了大口径器件的六自由度位姿对准. 对准过程中, 在机器人末端远离装配位置时, 采用视觉测量安装框架的相对位姿进行粗对准; 在机器人末端接近装配位置时, 由于安装框架尺寸大导致视觉不能获得完整的框架相对于大口径器件的位姿, 所以采用视觉采集安装框架的局部图像, 利用基于图像的控制消除绕Z轴的旋转误差和沿X、Y轴的平移误差, 采用多个激光测距传感器测量相对距离, 利用基于位置的控制消除沿Z轴的平移误差和绕X、Y轴的旋转误差, 实现大口径器件与安装框架的精对准. 采用增量式PI控制算法, 实现了对准的运动控制. 实验结果验证了所提方法的有效性.     

便携式车轮定位参数视觉检测系统研究

将双目视觉测量技术应用到汽车四轮定位中,采用两个摄像机的立体视觉方法,采集目标板图像并提取目标板上特征点,并根据几何模型计算特征点的空间位置,求得目标板的空闯位姿,通过分析车轮运动模型建立车轮参数模型,进而得到需要的角度;完成了亚像素级角点提取并正确匹配,标定了两个摄像机的内外参数与视觉系统参数,得到了目标板的空间位姿,通过实验的方法,验证了方案的可行性,分析了误差来源,同时初步搭建了WINCE嵌入式实验平台进行嵌入式算法研究.     

机器人柔性视觉检测系统现场标定技术

针对江淮车身厂的轿车车身提出了一种基于工业机器人的柔性视觉检测系统．通过控制机器人在空间的位姿变换,立体视觉传感器能够依次到达空间指定测量位置采集空间特征点的图像信息,并通过计算图像数据获得该点的三维坐标数据．利用双经纬仪和精密靶标对机器人视觉测量系统进行整体标定,同时完成了测试试验数据的采集及计算,取得了较好的测量效果．该系统柔性好、测量无死角,能适应生产线多车型检测的需要．     

Planning of collision-free paths for a reconfigurable dual manipulator equipped mobile robot

In this paper, we study the problem of finding a collision-free path for a mobile robot which possesses manipulators. The task of the robot is to carry a polygonal object from a starting point to a destination point in a possibly culttered environment. In most of the existing research on robot path planning, a mobile robot is approximated by a fixed shape, i.e., a circle or a polygon. In our task planner, the robot is allowed to change configurations for avoiding collision. This path planner operates using two algorithms: the collision-free feasible configuration finding algorithm and the collision-free path finding algorithm. The collision-free feasible configuration finding algorithm finds all collision-free feasible configurations for the robot when the position of the carried object is given. The collision-free path finding algorithm generates some candidate paths first and then uses a graph search method to find a collision-free path from all the collision-free feasible configurations along the candidate paths. The proposed algorithms can deal with a cluttered environment and is guaranteed to find a solution if one exists.     

Path planning for robobt manipulators in polyhhedral objects environment

A recent development in robotics is the increase of intelligence in robots. One of the research fields is to enable robots to autonomously avoid collisions with surrounding objects. This article presents an efficient method for planning collision-free paths for an articulated robot that is surrounded by polyhedral objects. The algorithm plans a hypothetical Archimedes's spiral path from the initial position to the goal position. When a collision among the arms and obstacles is detected, the hypothetical path will be modified to avoid the collision. The algorithm applies geometric methods to determine the upper and lower bounds of the reachable area of the wrist and then determines a collision-free path point on that reachable area. Because the equations, which represent the upper and lower bounds, are simple, the algorithm can rapidly determine a collision-free path. Moreover, with minor modifications, this path planning algorithm can also be applied to other robots such as spherical, cylindrical, and Cartesian types of robots. © 1995 John Wiley & Sons, Inc.     

A virtual-physical collision detection interface for AR-based interactive teaching of robot

At present, online lead-through and offline programming methods are widely used in programming of industrial robots. However, both methods have some drawbacks for unskilled shopworkers. This paper presents an Augmented Reality (AR)-based interactive robot teaching programming system, which virtually projected the robot onto the physical industrial environment. The unskilled shopworkers can use Handheld Teaching Device (HTD) to move end-effector of virtual robot to follow endpoint of the HTD. In this way, the path of the virtual robot can be planned or tested interactively. In addition, collisions detection between virtual robot and physical environment is key to test the feasibility of robot path. So, a method for detecting virtual-physical collisions is presented in this paper by comparing the depth values of corresponding pixels in depth image acquired by Kinect and computer-generated image in order to get collision-free paths of the virtual robot. The Quadtree model is used to accelerate the collision detection process and get distance between virtual model and physical environment. Using the AR-based interactive robot teaching programming system presented in this paper, all workers even unskilled ones in robot programming, can quickly and effectively get the collision-free robot path.     

基于混合模型的虚拟装配关键技术研究

针对虚拟装配中采用多边形网格模型引起的组件定位困难和碰撞检测精度低等问题,提出一种采用精确几何模型及其对应的多边形网格模型的混合模型作为底层数据,支持精确装配的虚拟装配系统构造方法,并基于Parasolid和Vir-tools平台进行了实现。基于混合模型的碰撞检测能根据计算精度和时间要求自适应求解,在速度快的同时,满足高精度碰撞检测要求;基于混合模型的组件装配,采用离散采样点定义装配路径,通过装配几何约束交互式定义限制组件的运动范围,通过自由度规约、装配约束求解实现了零部件精确定位,通过四元数插值实现装配路径中零部件位姿的平滑过渡,能满足高精度的装配要求。该方法已经在开发的多个系统中得到验证和应用。     

Haptic-aided robot path planning based on virtual tele-operation

The motivation of this work arises from the fact that it is very difficult for an automatic path planning method, e.g. probabilistic roadmap (PRM) to generate an optimized path, and sometimes it even fails for an automatic method to find a collision-free path, due to failure of discovering critical robot configurations. However, these critical configurations might be plain to an operator. Therefore, the advantages of human's intuition are exploited to facilitate the robot path planning process in this research. The objective of this paper is to combine the advantages of human's intuition or experiences and the huge computational power of computers to develop a semi-automatic robot path planner that can generate an user-preferred collision-free robot path. In the path planning process, the user interaction is made easy by the development of a haptically controlled virtual robot. By virtual tele-robot manipulation, a user can define or modify critical robot configurations based on which collision-free robot path can be automatically generated.     

Collision avoidance for Robot manipulators: Application to Catia/IBM 7565 interface

A collision avoidance algorithm has been developed to augment the capability of an automatic (off-line) robot path planning (programming) tool. The use of off-line programming tools for robot task programming is becoming increasingly important, but the advantages to be gained by off-line programming may be lost if collision-free path planning capabilities are not included. This article addressed the problem of collision-free path planning in the context of a gantry type robot. The collision avoidance algorithm described here uses the <heuristic approach> to collision-free path planning. The manipulator and obstacles are modeled as spheres to simplify tests for collision. An important feature of this algorithm is that it permits the manipulation of objects in the robot's environment. When compared against an algorithm from the literature, given a lightly cluttered environment modelled by spheres, the new algorithm finds a collision-free path much faster. This new algorithm has been implemented as part of the CATIA/IBM 7565 interface which forms an automatic off-line programming system for the IBM 7565 robot. It has also been implemented as a supervisory collision filter to allow collision-free control of the robot from the operator's console. In both cases the algorithm has been demonstrated to provide efficient and effective collision avoidance for the IBM 7565 robot.     

3D Collision-Free Motion Based on Collision Index

A collision-free motion planning method for mobile robots moving in 3-dimensional workspace is proposed in this article. To simplify the mathematical representation and reduce the computation complexity for collision detection, objects in the workspace are modeled as ellipsoids. By means of applying a series of coordinate and scaling transformations between the robot and the obstacles in the workspace, intersection check is reduced to test whether the point representing the robot falls outside or inside the transformed ellipsoids representing the obstacles. Therefore, the requirement of the computation time for collision detection is reduced drastically in comparison with the computational geometry method, which computes a distance function of the robot segments and the obstacles. As a measurement of the possible occurrence of collision, the collision index, which is defined by projecting conceptually an ellipsoid onto a 3-dimensional Gaussian distribution contour, plays a significant role in planning the collision-free path. The method based on reinforcement learning search using the defined collision index for collision-free motion is proposed. A simulation example is given in this article to demonstrate the efficiency of the proposed method. The result shows that the mobile robot can pass through the blocking obstacles and reach the desired final position successfully after several trials.     

Collision-free motion planning of dual-arm reconfigurable robots

Dual-arm reconfigurable robot is a new type of robot. It can adapt to different tasks by changing its different end-effector modules which have standard connectors. Especially, in fast and flexible assembly, it is very important to research the collision-free planning of dual-arm reconfigurable robots. It is to find a continuous, collision-free path in an environment containing obstacles. A new approach to the real-time collision-free motion planning of dual-arm reconfigurable robots is used in the paper. This method is based on configuration space (C-Space). The method of configuration space and the concepts reachable manifold and contact manifold are successfully applied to the collision-free motion planning of dual-arm robot. The complexity of dual-arm robots’ collision-free planning will reduce to a search in a dispersed C-Space. With this algorithm, a real-time optimum path is found. And when the start point and the end point of the dual-arm robot are specified, the algorithm will successfully get the collision-free path real time. A verification of this algorithm is made in the dual-arm horizontal articulated robot SCARATES, and the simulation and experiment ascertain that the algorithm is feasible and effective.     

受限管道空间内压壁机器人控制方法研究

为了能够在受限管道空间内自由移动,机器人必须适应管道的各种几何变化。提出了一种压壁式机器人,可以适应管道直径和坡度的变化。还提出了一种利用安装在压壁机构上的角度传感器估计机器人主体与管道之间的相对姿态的方法。由于法向力和姿态可以从角度传感器测量的角度信息估计,机器人的姿态控制比使用压力或视觉传感器更加简单、有效。相对于管道的几何姿态估计使机器人能够识别管道的倾斜度,机器人可以根据管道倾斜度的变化来控制法向力。经过实验验证,使用所提出的方法在机器人姿态控制的同时,还可以降低机器人部件的功耗和应力。     

Dual-layer multi-robot path planning in narrow-lane environments under specific traffic policies

Collision-free path planning is indispensable for the multi-robot system. Many existing multi-robot path planning algorithms may no longer work properly in the narrow-lane environment. We propose in this paper a dual-layer algorithm to deal with the multi-robot path planning problem in the narrow-lane environment. In the first layer, the integer programming technique primarily based on distance metrics balances the optimality of the generated collision-free paths and the computation time of the algorithm. In the second layer, fast feasible heuristics are applied to make sure the solvability of the proposed integer programming approach in the first layer. In the dual-layer algorithm, specific traffic policies for each narrow lane are implemented to generate a collision-free path for every robot while maintaining the narrow lane free, besides the collision avoidance approach at the robotic level. With this, inter-robot collision in the narrow lane is avoided, and the algorithm’s efficiency in producing collision-free paths increases. Simulations have been launched considerably based on the proposed assessment metrics. According to the extensive simulation data, our algorithm suggests a higher overall performance in the narrow-lane environment when in contrast with the present optimal, sub-optimal, and polynomial-complexity algorithms.