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Development of Navigation Control Algorithm for AGV Using D* search Algorithm  [cached]
Jeong Geun Kim,Dae Hwan Kim,Sang Kwun Jeong,Hak Kyeong Kim
International Journal of Science and Engineering , 2013, DOI: 10.12777/ijse.v4i2.4310
Abstract: In this paper, we present a navigation control algorithm for Automatic Guided Vehicles (AGV) that move in industrial environments including static and moving obstacles using D* algorithm. This algorithm has ability to get paths planning in unknown, partially known and changing environments efficiently. To apply the D* search algorithm, the grid map represent the known environment is generated. By using the laser scanner LMS-151 and laser navigation sensor NAV-200, the grid map is updated according to the changing of environment and obstacles. When the AGV finds some new map information such as new unknown obstacles, it adds the information to its map and re-plans a new shortest path from its current coordinates to the given goal coordinates. It repeats the process until it reaches the goal coordinates. This algorithm is verified through simulation and experiment. The simulation and experimental results show that the algorithm can be used to move the AGV successfully to reach the goal position while it avoids unknown moving and static obstacles. [Keywords— navigation control algorithm; Automatic Guided Vehicles (AGV); D* search algorithm]
Navigation Facility for High Accuracy Offline Trajectory and Attitude Estimation in Airborne Applications  [PDF]
A. Renga,G. Fasano,D. Accardo,M. Grassi,U. Tancredi,G. Rufino,A. Simonetti
International Journal of Navigation and Observation , 2013, DOI: 10.1155/2013/397686
Abstract: The paper focuses on a navigation facility, relying on commercial-off-the-shelf (COTS) technology, developed to generate high-accuracy attitude and trajectory measurements in postprocessing. Target performance is cm-level positioning with tenth of degree attitude accuracy. The facility is based on the concept of GPS-aided inertial navigation but comprises carrier-phase differential GPS (CDGPS) processing and attitude estimation based on multiantenna GPS configurations. Expected applications of the system include: (a) performance assessment of integrated navigation systems, developed for general aviation aircraft and medium size unmanned aircraft systems (UAS); (b) generation of reference measurements to evaluate the flight performance of airborne sensors (e.g., radar or laser); and (c) generation of reference trajectory and attitude for improving imaging quality of airborne remote sensing data. The paper describes system architecture, selected algorithms for data processing and integration, and theoretical performance evaluation. Experimental results are also presented confirming the effectiveness of the implemented approach. 1. Introduction Field test refers to the testing of a device or sensor in the conditions under which it will be actually used. Field testing becomes necessary when numerical and indoor testing may fail, that is, in all the cases in which the operative conditions are difficult to be reproduced with high fidelity by software or laboratory simulations. A typical example is the performance assessment of integrated navigation systems for airborne applications. In this case several factors must be taken into account, including but not limited to: (a) the intrinsic dynamical and statistical models of sensor and systems, (b) the selected data fusion strategy, and (c) the typical and the worst case manoeuvres that must be considered to determine a trustworthy dynamical model of the aircraft where the system is installed. Indeed, high performance heading and attitude determination units are needed both in general aviation and in unmanned aircraft systems (UAS) applications to attain an adequate control performance. UAS are more demanding in terms of attitude determination performance than manned aircraft for a series of issues. First, the absence of a human pilot onboard prevents the aircraft from using the human senses such as vision and coordination to integrate onboard systems. Furthermore, UAS are required to perform autonomous flight in case of loss of data link with the ground control station where the remote pilot is located [1, 2].
Moving Object Tracking and Avoidance Algorithm for Differential Driving AGV Based on Laser Measurement Technology  [cached]
Pandu Sandi Pratama,Sang Kwun Jeong,Soon Sil Park,Sang Bong Kim
International Journal of Science and Engineering , 2013,
Abstract: This paper proposed an algorithm to track the obstacle position and avoid the moving objects for differential driving Automatic Guided Vehicles (AGV) system in industrial environment. This algorithm has several abilities such as: to detect the moving objects, to predict the velocity and direction of moving objects, to predict the collision possibility and to plan the avoidance maneuver. For sensing the local environment and positioning, the laser measurement system LMS-151 and laser navigation system NAV-200 are applied. Based on the measurement results of the sensors, the stationary and moving obstacles are detected and the collision possibility is calculated. The velocity and direction of the obstacle are predicted using Kalman filter algorithm. Collision possibility, time, and position can be calculated by comparing the AGV movement and obstacle prediction result obtained by Kalman filter. Finally the avoidance maneuver using the well known tangent Bug algorithm is decided based on the calculation data. The effectiveness of proposed algorithm is verified using simulation and experiment. Several examples of experiment conditions are presented using stationary obstacle, and moving obstacles. The simulation and experiment results show that the AGV can detect and avoid the obstacles successfully in all experimental condition.
Wireless Sensor Network and RFID Fusion Approach for Mobile Robot Navigation  [PDF]
Guillermo Enriquez,Sunhong Park,Shuji Hashimoto
ISRN Sensor Networks , 2013, DOI: 10.1155/2013/157409
Abstract: There are numerous applications for mobile robots that require relatively high levels of speed and precision. For many systems, these two properties are a tradeoff, as oftentimes increasing the movement speed can mean failing to detect some sensors. This research attempts to create a useful and practical system by combining a wireless sensor network with a passive radio frequency identification system. The sensor network provides fast general navigation in open areas and the radio frequency identification system provides precision navigation near static obstacles. By fusing the data from both systems, we are able to provide fast and accurate navigation for a mobile robot. Additionally, with WSN nodes and passive RFID tag mats, the system infrastructure can be easily installed in existing environments. 1. Introduction In ubiquitous robotics, there are several applications for mobile robots that require relatively high levels of precision. In this research, we developed a system that balances the trade-off of speed and precision for mobile robot navigation around static obstacles. The system uses higher speeds when the area is free of obstacles, via a wireless-sensor-network-based (WSN) navigation approach. Around obstacles, or when a specific path or pose is required, the system incorporates a Radio Frequency IDentification (RFID) system, for precise navigation. By fusing the data from both systems using a simple, vector-based approach, we are able to provide fast and accurate navigation for a mobile robot. RFID tag mats were also developed which, along with easily installed wireless sensor nodes, make for quickly deployed system infrastructure. This system focuses on using this fusion approach for indoor mobile robot navigation with static obstacle avoidance. While the avoidance of dynamic obstacles is also key for ubiquitous robotics, there is still room for improvement in static obstacle avoidance. Moreover, the vast majority of applications for indoor robot navigation have a large static obstacle component to them. It is for this reason that we chose to focus first on this aspect. A simple taxonomy for robot sensors (pertaining to navigation) could be listed as such: vision (cameras, etc.), range-finding (laser, sonar, etc.), inertial (encoders, etc.), active beacons (active RFID, WSN, etc.), and passive beacons (passive RFID, magnetic strips, etc.). All of these systems have their advantages and disadvantages. For instance, range-finding can suffer from inaccuracy when there are few reflective surfaces and vision systems often have a high
A Hybrid Trajectory Clustering for Predicting User Navigation  [PDF]
Hazarath Munaga,J. V. R. Murthy,N. B. Venkateswarlu
Computer Science , 2011,
Abstract: Wireless sensor networks (WSNs) suffers from the hot spot problem where the sensor nodes closest to the base station are need to relay more packet than the nodes farther away from the base station. Thus, lifetime of sensory network depends on these closest nodes. Clustering methods are used to extend the lifetime of a wireless sensor network. However, current clustering algorithms usually utilize two techniques; selecting cluster heads with more residual energy, and rotating cluster heads periodically to distribute the energy consumption among nodes in each cluster and lengthen the network lifetime. Most of the algorithms use random selection for selecting the cluster heads. Here, we propose a novel trajectory clustering technique for selecting the cluster heads in WSNs. Our algorithm selects the cluster heads based on traffic and rotates periodically. It provides the first trajectory based clustering technique for selecting the cluster heads and to extenuate the hot spot problem by prolonging the network lifetime.
Distributed Navigation Algorithms for Sensor Networks  [PDF]
Chiranjeeb Buragohain,Divyakant Agrawal,Subhash Suri
Computer Science , 2005,
Abstract: We propose efficient distributed algorithms to aid navigation of a user through a geographic area covered by sensors. The sensors sense the level of danger at their locations and we use this information to find a safe path for the user through the sensor field. Traditional distributed navigation algorithms rely upon flooding the whole network with packets to find an optimal safe path. To reduce the communication expense, we introduce the concept of a skeleton graph which is a sparse subset of the true sensor network communication graph. Using skeleton graphs we show that it is possible to find approximate safe paths with much lower communication cost. We give tight theoretical guarantees on the quality of our approximation and by simulation, show the effectiveness of our algorithms in realistic sensor network situations.
Mobile Sensor Waypoint Navigation via RF-Based Angle of Arrival Localization
Isaac Amundson,Janos Sallai,Xenofon Koutsoukos,Akos Ledeczi
International Journal of Distributed Sensor Networks , 2012, DOI: 10.1155/2012/842107
Abstract: Over the past decade, wireless sensor networks have advanced in terms of hardware design, communication protocols, and resource efficiency. Recently, there has been growing interest in mobility, and several small-profile sensing devices that control their own movement have been developed. Unfortunately, resource constraints inhibit the use of traditional navigation methods because these typically require bulky, expensive sensors, substantial memory, and a generous power supply. Therefore, alternative navigation techniques are required. In this paper, we present a navigation system implemented entirely on resource-constrained sensors. Localization is realized using triangulation in conjunction with radio interferometric angle-of-arrival estimation. A digital compass is employed to keep the mobile node on the desired trajectory. We also present a variation of the approach that uses a Kalman filter to estimate heading without using the compass. We demonstrate that a resource-constrained mobile sensor can accurately perform waypoint navigation with an average position error of 0.95 m.
A Sensing and Robot Navigation of Hybrid Sensor Network  [PDF]
Shuncai Yao, Jindong Tan, Hongxia Pan
Wireless Sensor Network (WSN) , 2010, DOI: 10.4236/wsn.2010.24037
Abstract: Traditional sensor network and robot navigation are based on the map of detecting fields available in advance. The optimal algorithms are explored to solve the energy saving, shortest path problems, etc. However, in practical environment, there are many fields, whose map is difficult to get, and need to detect. This paper explores a kind of ad-hoc navigation algorithm based on the hybrid sensor network without the prior map. The system of navigation is composed of static nodes and mobile nodes. The static nodes monitor events occurring and broadcast. In the system, a kind of cluster broadcast method is adopted to determine the robot localization. The mobile nodes detect the adversary or dangerous fields and broadcast warning message. Robot gets the message and follows ad-hoc routine to arrive the events occurring place. In the whole process, energy saving has taken into account. The algorithms of nodes and robot are given in this paper. The simulate and practical results are available as well.
Compressing Moving Object Trajectory in Wireless Sensor Networks  [PDF]
Yingqi Xu,Wang-Chien Lee
International Journal of Distributed Sensor Networks , 2007, DOI: 10.1080/15501320701204756
Abstract: Some object tracking applications can tolerate delays in data collection and processing. Taking advantage of the delay tolerance, we propose an efficient and accurate algorithm for in-network data compression, called delay-tolerant trajectory compression (DTTC). In DTTC, a cluster-based infrastructure is built within the network. Each cluster head compresses an object's movement trajectory detected within its cluster by a compression function. Rather than transmitting all sensor readings to the sink node, the cluster head communicates only the compression parameters, which not only provide the sink node expressive yet traceable models about the object movements, but also significantly reduce the total amount of data communication required for tracking operations. DTTC supports a broad class of movement trajectories using two proposed techniques, DC-compression and SW-compression, and an efficient trajectory segmentation scheme, which are designed for improving the trajectory compression accuracy at less computation cost. Moreover, we analyze the underlying cluster-based infrastructure and mathematically derive the optimum cluster size, aiming at minimizing the total communication cost of the DTTC algorithm. An extensive simulation has been conducted to compare DTTC with competing prediction-based tracking technique, DPR [28]. Simulation results show that DTTC exhibits superior performance in terms of accuracy, communication cost and computation cost and soundly outperforms DPR with all types of movement trajectories.
Information Potential Fields Navigation in Wireless Ad-Hoc Sensor Networks  [PDF]
Wei Wei,Yong Qi
Sensors , 2011, DOI: 10.3390/s110504794
Abstract: As wireless sensor networks (WSNs) are increasingly being deployed in some important applications, it becomes imperative that we consider application requirements in in-network processes. We intend to use a WSN to aid information querying and navigation within a dynamic and real-time environment. We propose a novel method that relies on the heat diffusion equation to finish the navigation process conveniently and easily. From the perspective of theoretical analysis, our proposed work holds the lower constraint condition. We use multiple scales to reach the goal of accurate navigation. We present a multi-scale gradient descent method to satisfy users’ requirements in WSNs. Formula derivations and simulations show that the method is accurately and efficiently able to solve typical sensor network configuration information navigation problems. Simultaneously, the structure of heat diffusion equation allows more flexibility and adaptability in searching algorithm designs.
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