Optimization of configurations of four beacons in a difference range finding navigation system within the visibility cone

By the criterion of the spatial factor of worsening the accuracy of the PDOP (Position Dilution of Precision), it is proved that, depending on the opening of the circular cone of visibility of beacons, the commonly accepted regular configuration or a new semiregular configuration of the beacons is optimal. In the case when the opening of the three-dimensional cone of visibility of beacons is less than 38° by the PDOP criterion, the semiregular configuration (maximum by 13%) is preferable; otherwise, the commonly accepted regular configuration is preferable (but no greater than by 17% according to the PDOP criterion).     

Guidance using bearing-only measurements with three beacons in the plane

This paper proposes a bearing-only measurement based guidance algorithm for a mobile agent to navigate in a two-dimensional plane. Based on the bearing vectors and the subtended angles related to three stationary beacons, the proposed algorithm allows the agent to reach its desired location. We show that the agent reaches its desired location globally asymptotically based on Lyapunov stability theory. Under some assumptions, the agent is also proved to reach the desired location exponentially based on Lyapunov's indirect method. Simulations and actual experimental tests on quadrotor system are also provided to verify the effectiveness of the proposed algorithm in outdoor environment.     

浅谈石化装置防爆设计及爆炸危险区域划分

石油化工装置爆炸危险区域划分和防爆设计是工程设计中的一项基础性工作,它对于石油化工装置的建设、验收和运行都有很重要的作用,本文通过对国内外防爆设计手册和标准规范的学习,系统分析了爆炸危险区域和防爆设计的概念,并举例说明应用,以求正确指导爆炸危险区域划分和防爆设计。     

Reactive navigation in real environments using partial center of area method

Using inspiration from our perception on how humans select the path to walk in crowded areas, a new method for reactive autonomous robot navigation is proposed. The method uses only a part of the detected free space in front of the robot to compute a partial center of area. It can guide the robot safely for robust wandering while the center of area remains accessible. In some cases it is necessary to split and shrink the detected area used for navigation to overcome a transitional inaccessible center of area. The method was slightly modified so that the robot can reach a stimulus goal while avoiding obstacles. Method implementation and modifications are explained in detail. Some experiments were carried to test the method with a real robot in mid-complex environments. In previous works the method was extensively tested in simulations and the good results obtained there are confirmed by the real robot tests.     

Real-time autonomous navigation of an electric wheelchair in large-scale urban area with 3D map*

This paper presents the real-time autonomous navigation of an electric wheelchair in a large-scale urban area. Accurate self-pose localization and well-chosen motion control are crucial for application to urban areas, as electric wheelchairs move on paved roads in dynamic environments and travel along sidewalks at a brisk speed. Our system is equipped with a localization module based on a 3D map and a path planning module based on a navigation map. However, the large-scale 3D map causes a high memory load, and the embedded PC can not deal with the map data. In addition, the large-scale navigation map increases the computational cost of path planning, which causes delays in navigation. To achieve real-time navigation independent of map size, we propose a 6-DoF pose localization switching reference 3D map and a two-step path planning framework. We ran tests by using an electric wheelchair on a real street in Tokyo and found that the proposed navigation system achieved autonomous navigation for over 8.8?km in about 133 minutes. The experimental results showed that the memory load was kept constant and the path planning was performed at high frequency, regardless of the size of the map or the distance to the destination.     

仿生机器人视觉导航研究分析

视觉导航技术是保证机器人自主移动的关键技术之一。为了从整体上把握当前国际上最新的视觉导航研究动态,全面评述了仿生机器人视觉导航技术的研究进展,重点分析了视觉SLAM(Simultaneous Local-ization and Mapping)、闭环探测、视觉返家三个关键问题的研究现状及存在的问题。提出了一个新的视觉SLAM算法框架,给出了待解决的关键理论问题,并对视觉导航技术发展的难点及未来趋势进行了总结。     

iTPS: an improved location discovery scheme for sensor networks with long-range beacons

In this paper, we present time-based positioning scheme (iTPS), a purely localized location detection scheme for sensor networks with long-range beacons. iTPS relies on time difference of arrival (TDoA) of radio frequency (RF) signals measured locally at each sensor to detect range differences from the sensor to four base stations. These range differences are combined to estimate the sensor location through trilateration. iTPS is an improvement over TPS (Cheng et al., IEEE INFOCOM, 2004), which produces two ambiguous position estimates when sensors are close to any base station. iTPS substantially reduces the number of ambiguous estimates and can improve accuracy. Features of iTPS include low communication overhead for sensors, no requirements for time synchronization, low computational overhead due to simple algebraic operations, and high scalability. We conduct extensive simulation to test iTPS and compare it with TPS. The obtained results show that iTPS is an efficient and effective scheme for location discovery in sensor networks with long-range beacon stations.     

Intensity-based navigation with global guarantees

This article introduces simple, information-feedback plans that guide a robot through an unknown obstacle course using the sensed information from a single intensity source. The framework is similar to the well-known family of bug algorithms; however, our plans require less sensing information than any others. The robot is unable to access precise information regarding position coordinates, angular coordinates, time, or odometry, but is nevertheless able to navigate itself to a goal among unknown piecewise-analytic obstacles in the plane. The only sensor providing real values is an intensity sensor, which measures the signal strength emanating from the goal. The signal intensity function may or may not be symmetric; the main requirement is that the level sets are concentric images of simple closed curves. Convergence analysis and distance bounds are established for the presented plans. Furthermore, they are experimentally demonstrated using a differential drive robot and an infrared beacon.     

Autonomous navigation and obstacle avoidance using navigation laws with time-varying deviation functions

In this paper we introduce a new family of navigation functions for robot navigation and obstacle avoidance. The method can be used for both path finding and real-time path planning. Each navigation function is composed of three parts: a proportionality term, a deviation function and a deviation constant. Deviation functions are time-varying functions satisfying certain conditions. These functions and parameters are updated in real-time to avoid collision with obstacles. Our strategy uses polar kinematics equations to model the navigation problem in terms of the range and direction between the robot and the goal. The obstacles are mapped to polar planes, and represented by the range and the direction from the robot or the final goal in polar coordinates. This representation gives a certain weight to the obstacles based on their relative position from the robot and facilitates the design of the navigation law. There exists an infinite number of navigation functions obtained by changing the proportionality constant, the deviation constant or the deviation function. This offers an infinite number of possibilities for the robot's path. Our navigation strategy is illustrated using an extensive simulation where different navigation parameters are used.     

The centre of area method as a basic mechanism for representation and navigation

Potential methods and all their gradient-based derivations are extensively used in autonomous robotics, primarily in association with reactive navigational strategies. In this article we introduce the fundamentals, formalisation and application of a brand-new method based on first-order moments called the “centre of area method”. We also comment on its validity, at an individual level and in combination with other methods, in order to build a situated representation of the environment.     

无线传感器网络中的信标优化选择算法

针对无线传感器网络中节点定位精度的问题,提出了一种基于距离和Cramer-Rao下界的信标优化选择算法。该算法通过分析信标与节点间的距离和位置拓扑关系对定位精度的影响,选择CRLB值最小的信标子集进行位置估计,减少节点定位误差。仿真结果表明,该方法较大地提高了定位精度,降低了计算量,为合理选择信标子集提供了依据。     

Evolving semantic web with social navigation

The Semantic Web (SW) is a meta-web built on the existing WWW to facilitate its access. SW expresses and exploits dependencies between web pages to yield focused search results. Manual annotation of web pages towards building a SW is hindered by at least two user dependent factors: users do not agree on an annotation standard, which can be used to extricate their pages inter-dependencies; and they are simply too lazy to use, undertake and maintain annotation of pages. In this paper, we present an alternative to exploit web pages dependencies: as users surf the net, they create a virtual surfing trail which can be shared with other users, this parallels social navigation for knowledge. We capture and use these trails to allow subsequent intelligent search of the web.People surfing the net with different interests and objectives do not leave similar and mutually beneficial trails. However, individuals in a given interest group produce trails that are of interest to the whole group. Moreover, special interest groups will be higher motivated than casual users to rate utility of pages they browse. In this paper, we introduce our system KAPUST1.2 (Keeper And Processor of User Surfing Trails). It captures user trails as they search the internet. It constructs a semantic web structure from the trails. The semantic web structure is expressed as a conceptual lattice guiding future searches. KAPUST is deployed as an E-learning software for an undergraduate class. First results indicated that indeed it is possible to process surfing trails into useful knowledge structures which can later be used to produce intelligent searching.     

Using mobile beacons to locate sensors in obstructed environments

Locating sensors in an indoor environment is a challenging problem due to the insufficient distance measurements caused by short ultrasound range and the incorrect distance measurements caused by multipath effect of ultrasound. In this paper, we propose a virtual ruler approach, in which a vehicle equipped with multiple ultrasound beacons travels around the area to measure distances between pairwise sensors. Virtual Ruler can not only obtain sufficient distances between pairwise sensors, but can also eliminate incorrect distances in the distance measurement phase of sensor localization. We propose to measure the distance between pairwise sensors from multiple perspectives using the virtual ruler and filter incorrect values through a statistical approach. By assigning measured distances with confidence values, the localization algorithm can intelligently localize each sensor based on high confidence distances, which greatly improves localization accuracy. Our performance evaluation shows that the proposed approach can achieve better localization results than previous approaches in an indoor environment.     

Image-based homing navigation with landmark arrangement matching

Many insects and animals exploit their own navigation systems to navigate in space. Biologically-inspired methods have been introduced for landmark-based navigation algorithms of a mobile robot. The methods determine the movement direction based on a home snapshot image and another snapshot from the current position. In this paper, we suggest a new landmark-based matching method for robotic homing navigation that first computes the distance to each landmark based on ego-motion and estimates the landmark arrangement in the snapshot image. Then, landmark vectors are used to localize the robotic agent in the environment and to choose the appropriate direction to return home. As a result, this method has a higher success rate for returning home from an arbitrary position than do the conventional image-matching algorithms.     

一种INS-GPS-DVL容错组合导航系统

针对某船载导航系统精度和容错性能不能满足应用要求的问题,提出了一种基于信息融合技术的容错组合导航系统方案。研究了该组合导航系统的滤波算法,通过半物理仿真实验研究了该导航系统的性能。结果表明：所设计的组合导航系统可提供高精度的导航信息,提高导航系统综合性能。     

Wheeled mobile robot navigation using proportional navigation

We present a method for wheeled mobile robot navigation based on the proportional navigation law. This method integrates the robot's kinematics equations and geometric rules. According to the control strategy, the robot's angular velocity is proportional to the rate of turn of the angle of the line of sight that joins the robot and the goal. We derive a relative kinematics system which models the navigation problem of the robot in polar coordinates. The kinematics model captures the robot path as a function of the control law parameters. It turns out that different paths are obtained for different control parameters. Since the control parameters are real, the number of possible paths is infinite. Results concerning the navigation using our control law are rigorously proven. An extensive simulation confirms our theoretical results.     

Dual Toll Pricing for Hazardous Materials Transport with Linear Delay

In this paper, we propose a dual toll pricing method to mitigate risk of hazardous materials (hazmat) transportation. We aim to simultaneously control both regular and hazmat vehicles to reduce the risk. In our model, we incorporate a new risk measure to consider duration-population-frequency of hazmat exposure. We first formulate the model as a Mathematical Program with Equilibrium Constraints (MPEC). Then we decompose the MPEC formulation into first-stage and second-stage problems. Separate methods are developed to solve each stage. A numerical example is provided and possible extensions are discussed.