Algorithms for path planning, navigation and guidance of an AGV

Algorithms for path navigation and generation of guidance setpoints for an AGV are developed. Navigation is based on a simple flat world model of connected nodes using a suboptimal path solution for execution speed. The guidance algorithms use vision data from a stereo pair of linear image array cameras, which described an obstacle location and height where intersected by the vision system plane of view. The development of a map of the area on the AGV path allows the detection of obstacles, which may be passed subject to the aisle markings. The complete vision-guidance system can be implemented using inexpensive commercially available 16 bit microprocessors.     

On computational methods for variational inequalities

In this note, we focus on optimised mesh design for the Finite Element (FE) method for variational inequalities using global norm estimates for local error control. The strategies are based on the so called dual-weighted-residual (DWR) approach to a posteriori error control for FE-schemes (see, e.g., Rannacher et al. [19, 6, 2]), where error control for the primal problem is established by solving an auxiliary (dual) problem. In this context we blamed (cf. e.g., Rannacher and Suttmeier [18, 19]) global norm estimates being not that useful in applications. But having a closer look at the DWR-concept, one observes that in fact global (energy) error bounds can be employed to establish local error control. Our ideas and techniques are illustrated at the socalled obstacle problem.It turns out, that reliable and efficient energy error control is one main ingredient to establish useful a posteriori error bounds for local quantities. Therefore, in addition, we derive an unified approach to a posteriori error control in the energy norm for elliptic variational inequalities of first kind. Eventually, this framework is applied to Signorinis problem.     

PRIAMOS: An experimental platform for reflexive navigation

In this paper the new mobile robot system PRIAMOS is presented. The system emphasizes on fast navigation algorithms. In a (partially) unknown or changing environment fast perception and reaction is necessary for efficient task execution. Low level mapping and planning modules are used to span the period until higher control layers have enough time to react. The first part of this paper briefly describes the mechanical and technical construction of PRIAMOS. After an explanation of the software architecture the solutions for motion control and reflexive navigation, as realized in PRIAMOS, are given.     

An opportunistic global path planner

In this paper we describe a robot path-planning algorithm that constructs a global skeleton of free-space by incremental local methods. The curves of the skeleton are the loci of maxima of an artificial potential field that is directly proportional to distance of the robot from obstacles. Our method has the advantage of fast convergence of local methods in uncluttered environments, but it also has a deterministic and efficient method of escaping local extremal points of the potential function. We first describe a general roadmap algorithm, for configuration spaces of any dimension, and then describe specific applications of the algorithm for robots with two and three degrees of freedom.This research was supported by a David and Lucile Packard Foundation Fellowship and by NSF Presidential Young Investigator Grant number IRI-8958577.     

Monocular obstacle detection using reciprocal-polar rectification

Our obstacle detection method is applicable to deliberative translation motion of a mobile robot and, in such motion, the epipole of each image of an image pair is coincident and termed the focus of expansion (FOE). We present an accurate method for computing the FOE and then we use this to apply a novel rectification to each image, called a reciprocal-polar (RP) rectification. When robot translation is parallel to the ground, as with a mobile robot, ground plane image motion in RP-space is a pure shift along an RP image scan line and hence can be recovered by a process of 1D correlation, even over large image displacements and without the need for corner matches. Furthermore, we show that the magnitude of these shifts follows a sinusoidal form along the second (orientation) dimension of the RP image. This gives the main result that ground plane motion over RP image space forms a 3D sinusoidal manifold. Simultaneous ground plane pixel grouping and recovery of the ground plane motion thus amounts to finding the FOE and then robustly fitting a 3D sinusoid to shifts of maximum correlation in RP space. The phase of the recovered sinusoid corresponds to the orientation of the vanishing line of the ground plane and the amplitude is related to the magnitude of the robot/camera translation. Recovered FOE, vanishing line and sinusoid amplitude fully define the ground plane motion (homography) across a pair of images and thus obstacles and ground plane can be segmented without any explicit knowledge of either camera parameters or camera motion.     

基于多传感器的家庭服务机器人局部导航方法研究

本文提出了一种基于多传感器的家庭服务机器人局部导航方法。首先,采用单个摄像头获取居室内障碍物的图像信息,利用超声波传感器和红外线传感器探测障碍物的距离信息。然后,据此计算在机器人运动方向上障碍物的遮挡空间或者多个障碍物之间的实际距离,再根据机器人自身的大小计算避开障碍物应该转动的方向及角度,从而实现居室内的自主导航。最后,仿真实验结果证明了该方法的有效性。     

基于改进人工势场法的机器人避障及路径规划研究

在不确定和复杂的移动环境中,利用传统的人工势场法进行机器人避障很难满足对环境动态适应性的需要。提出了一种相对速度的改进的人工势场法,针对于传统的路径规划中局部最小值问题,提出设置中间目标点的方法,给机器人一个外力以避免其在局部最小点处停止或者徘徊,确保机器人能够逃出最小值陷阱并顺利到达目标位置。最后在Matlab平台上进行了仿真实验,实验结果表明,改进后的人工势场法能较好地实现动态环境下移动机器人的路径规划。     

结合模糊逻辑和改进人工势场的局部路径规划

针对人工势场法的死点问题和较为复杂的局部障碍物环境,采取模糊逻辑与改进的人工势场相结合的方式,提出了一种结合模糊控制器与人工势场算法的并行避障处理结构。依据静态目标点位置与多路超声波传感器返回的障碍物距离信息,实行稳定环境的人工势场路径规划与危险环境的模糊控制,使移动机器人能够到达预定目标点。在Mobotsim仿真软件中验证了算法的可行性与有效性。     

基于虚拟力场的移动机器人避障方法

提出了用虚拟力场方法来实现移动机器人的避障。此方法采用确定栅格描述障碍物，具有简易、直观的特点。它使机器人在移动过程中能够检测到未知的障碍物并避开它，实现机器人朝着目标点移动。实验结果表明，用这种方法可以达到避障的效果，但机器人受到干扰时容易出现运动不稳定现象。     

家用aPTT检测技术芯片修饰方法的研究

采用凝血检测光学透射比浊方法检测活化部分凝血活酶时间(aPTT), 尝试用聚乙烯(PE)、聚苯乙烯(PS)和Parylene-C 3种疏水材料, 研究压电石英晶体微电平(QCM)传感芯片表面修饰。 修饰后,芯片品质用网络分析仪衡量,PE、PS和Parylene-C 3种疏水材料的疏水修饰接触角分别为92.3°、90.7°和93.3°。结果表 明,Parylene-C修饰后QCM芯片的品质提高,有效信号峰-峰值提高了11%;用于 光学aPTT检测 对比体现出良好重复性,血浆7次检测变异系数(CV)为1.51%, 重复性良 好,全血7次检测CV为1.15%。本文的Pary lene-C修饰QCM,可为家用aPTT检测仪器的开发提供参考。