13 val can be computed: Here one common focus is on-line revising pre-planned paths in previously known environments to avoid robot collisions with newly added recog- nizable obstacles, which could be static (e.g., ) or performing particular kinds of motions (e.g., [103, 108]). These schemes usually assume partial changes to known C-space or CT-space to limit the scale of re-computing or re-planning for facilitating real-time computation. There is also work on motion planning to avoid static or moving obstacles with certain known velocities within some time interval [25, 52]. Only the geometries of obstacles are known: Here the obstacles are assumed known (or recognizable), but with unknown future trajectories. There are a few planners (e.g., [20, 35, 50, 89]) that address mobile-robot motion planning in such an environment. A real-time adaptive motion planning (RAMP) approach [91, 92] is very effective for planning high-DOF robot motion, characterized by simultaneous planning and execution based on sensing.
isting strategies, with minimal communication overhead. We introduce the Host Routing strategy, which makes use of an overlay network to discover the location of mobile objects. Overlay networks, such as CAN , Chord , Pastry  et al, are distributed systems that do not rely on centralised con- trol or hierarchical organisation . They are typically self- organising networks, layered upon an IP-based network, that use a flat logical addressing scheme. Each host only needs knowledge of O(log n) other hosts, yet can send a message to an unknown host, through other hosts using key-based rout- ing, which only takes O(log n) hops - in both cases n is the number of hosts. This creates a global yet distributed index of hosts which is scalable, efficient and reliable.
An efficient stereovision-based motion compensation method for moving robots is presented in [ 15 ] using the disparity map and three modules: segmentation, feature extraction, and estimation. In the segmentation module, the authors propose the use of extended type-2 fuzzy information theory to recognize the obstacles. Fuzzy logic is used to implement the design and coordination [ 36 ] of a memory grid and to develop a minimum risk method for robot navigation, and is able to avoid collision with obsta- cles in different scenarios, such as long walls, large concave and recursive UU-shaped regions, unstructured regions, cluttered regions, and maze-like obstacles that repre- sent dynamic indoor environments. In [ 1 ] a fuzzy logic controller is developed based on the Mamdani-type fuzzy method for robot navigation and obstacle avoidance in a cluttered environment. A fuzzy controller with three inputs and a single output pro- vides safe navigation for the robot motion in a static environment while taking into account the accuracy of the measurements of its position, distance to the obstacles and the goal point, speed, orientation, and the rate of change of its heading angle. The authors in [ 1 ] describe a fast and reliable method of obstacle avoidance for both for outdoor and indoor navigation. The method is applicable in various mobile robotic systems regardless of whic sensors are used and is based on two complementary ap- proaches: non-complex implementation and human-like smooth steering. In [ 37 ] a conceptual approach is considered based on fuzzy logic to solve the local navigation and obstacle avoidance problem for multi-link robots. The fuzzy rule-based approach is considered as an on-line local navigation method for the generation of instantaneous collision-freetrajectories.
 again deals with path planning and intelligent control of an autonomous robot which should move safely in partially structured environment. However, it addresses both the problems – Findspace problem and Findpath problem and uses two neural networks – one to map the space and hence solve the Findspace problem and the other to deal with the construction of a collisionfree path through the partially structured space to avoid the nearest obstacles.
In this paper a minimalist approach to establish obstacle avoidance and course stabilization behavior of an autonomous robot in a region evaluating 2D virtual world is proposed. The robot uses ultrasonic sensor to evade the hindrances and with distance measurements of barriers predict itself the shortest path to travel on through the destination and updating the virtual environment in database. The robot will be communicated with full duplex communication using ZigBee technology with computer interface. The environment around the rover will be visualized in GUI itself. Even robot can be made navigated searching for maximum light intensity in environment. The proposal is intense to aid the defense system and space exploration. It brings sophisticated method of practice by learning through virtual world of environment which can be enhanced even to 3D with technologies available.
The Lin-Canny algorithm does not handle penetrating polytopes, however, and if such a condition arises the algorithm enters an infinite loop. A possible solution to this problem is to force termination after a maximum iteration, and return a simple result stating that the objects have collided. However, this solution is quite slow, and no measure of inter-penetration is provided. Inter-penetrating objects will occur very frequently unless they are moving quite slowly, and/or if the detection time-step is quite small. This is unlikely to be the case in real-time applications such as games and Virtual Environments. If inter-penetration occurs, and more information is needed about the exact time of contact, backtracking is necessary to pinpoint the exact instant in time when collision occurred, a slow and cumbersome process. Pseudo internal Voronoi regions for convex polyhedra were introduced in [Ponamgi et al. 1997] to try to circumvent this problem. Another problem is the need to handle many special cases separately (e.g. parallel features), and the difficulty of configuration, with several numerical tolerances that need to be adjusted to achieve the desired performance.
The problem of determining a smoothest and collision-free path with maximum possible speed for a Mobile Robot (R) which is chasing a moving target in an unknown dynamic environment is addressed in this paper. Genetic Network Programming with Reinforcement Learning (GNP-RL) has several important features over other evolutionary algorithms such as combining offline and online learning on the one hand, and combining diversified and intensified search on the other hand. However, it was used in solving the problem of R navigation in static environment only. This paper presents GNP-RL as a first attempt to apply it for R navigation in dynamic environment. The GNP-RL is designed based on an environment representation called Obstacle-Target Correlation (OTC). The combination between features of OTC and that of GNP-RL provides safe navigation (effective obstacle avoidance) in dynamic environment, smooth movement, and reducing the obstacle avoidance latency time. Simulation in dynamic environment is used to evaluate the performance of collision prediction based GNP-RL compared with that of two state-of-the art navigation approaches, namely, Q-learning (QL) and Artificial Potential Field (APF). The simulation results show that the proposed GNP-RL outperforms both QL and APF in terms of smoothness movement and safer navigation. In addition, it outperforms APF in terms of preserving maximum possible speed during obstacle avoidance.
Analysis of the available free solutions for cloud data storage organization revealed the undoubted leader in this area - service OwnCloud. OwnCloud source code is distributed under a free license AGPLv31. In order to deploy OwnCloud the web- server is required with PHP interpreter and a database MySQL, PostgreSQL or SQLite . In this paper, we study the installation of the cloud storage OwnCloud on a local web-server. Specially for students of Computer science major there were developed guidelines on the subject Cloud technologies. The aim of the work is installing OwnCloud cloud storage on a local Web-server. Students learn OwnCloud and get familiar with project KDE SC (K Desktop Environment Software Compilation), learn to install the Web-server Open Server on the computer, set the cloud OwnCloud at Open Server, work with cloud storage OwnCloud.
segmentation accomplished by using histogram shape-based thresholding algorithm. There are two procedure to detect a pothole in elliptical shape based on the detected shades. First is morphological thinning to minimize the cracks effect from the potholes. The second one is elliptic regression to approximate an ellipse. A remote-controlled robot was used to collect the data and simulate a high speed vehicle. The data is classify by a high variety potholes such as by shapes and sizes, non-defect asphalt pavements and other defect such as cracking and patching, and shadows that caused by lighting condition. This method has 85.9% accuracy and 81.6% precision. Although it is inefficient for the computation due the redetected pothole from processing every single image of the road pavement videos .
In open-MASs, trust models serve as a social- based mechanism to control interactions among agents. In open, complex and uncertain environments, trust and reputation systems are social approaches used to support agents’ decision- making in choosing trusted agents to cooperate with [18, 19]. In such context, trust is discussed (i) as models to allow agents trusting other agents and reason over their trusting behaviour; (ii) as a mechanism to compute trust values of their interaction partners; trust models help agents to decide how, when and who to interact with .
To resolve this problem, we propose Hit- Ratio storage-tier partition strategy (HRSP) that aliens marked temperature data blocks to respective partitions and build custom metadata indexes for efficient accessibility. The proposed approach provides a contention-free data block access and decreases I/O accessibility latency.
experts.(Mohammad & Al Saiyd, 2010). The expert system is the program that stores the knowledge in a knowledge-base and executes a set of procedures and preconditions to arrive at the final results with the help of the specialists to be able to reach the optimal situation . The expert system stores the knowledge from the expertise and self-knowledge which called Meta knowledge which has already found a place in market position. Normally, expert system consists of the following components: (i) end user interface, (ii) inference engine, and (iii) knowledge base (; ;  ; ). Last decade, however, shows that a growing number of organizations have shifted their informational systems towards a rule-based expert system approach . This fact generates the need for new tools and environments that intelligently port the legacy systems in modern, extensible and scalable knowledge-integrated systems . The power of solving the problems in the expert system is to acquire the knowledge and structure to employ them in expert system services (; ). Therefore the achievement of expert system completely depends ongoing on how it fits the element which works as one. 5. PROPOSED EXPERT SYSTEM