• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.313-320
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• 2019

Nowadays, as the availability of tiny, low-cost microcomputer increases at a high level, mobile robots are experiencing remarkable enhancements in hardware design, software performance, and connectivity advancements. In order to control Turtlebot 2, several algorithms have been developed using the Robot Operating System(ROS). However, ROS requires to be run on a high-cost computer which increases the hardware cost and the power consumption to the robot. Therefore, design an algorithm based on low-cost hardware is the most innovative way to reduce the unnecessary costs of the hardware, to increase the performance, and to decrease the power consumed by the computer on the robot. In this paper, we present a path-finding algorithm for TurtleBot 2 based on low-cost hardware. We implemented the algorithm using Raspberry pi, Windows 10 IoT core, and RPLIDAR A2. Firstly, we used Raspberry pi as the alternative to the computer employed to handle ROS and to control the robot. Raspberry pi has the advantages of reducing the hardware cost and the energy consumed by the computer on the robot. Secondly, using RPLIDAR A2 and Windows 10 IoT core which is running on Raspberry pi, we implemented the path-finding algorithm which allows TurtleBot 2 to navigate from the starting point to the destination using the map of the area. In addition, we used C# and Universal Windows Platform to implement the proposed algorithm.

• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.1-23
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• 2005

The shortest-paths problem is a fundamental problem in graph theory and finds diverse applications in various fields. This is why shortest path algorithms have been designed more thoroughly than any other algorithm in graph theory. A large number of optimization problems are mathematically equivalent to the problem of finding shortest paths in a graph. The shortest-path between a pair of vertices is defined as the path with shortest length between the pair of vertices. The shortest path from one vertex to another often gives the best way to route a message between the vertices. This paper presents an $O(n^2)$ time sequential algorithm and an $O(n^2/p+logn)$ time parallel algorithm on EREW PRAM model for solving all pairs shortest paths problem on circular-arc graphs, where p and n represent respectively the number of processors and the number of vertices of the circular-arc graph.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3100-3116
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• 2016

With the rapid development of urban traffic system and fast increasing of vehicle numbers, the traditional centralized ways to generate the source-destination shortest path in terms of travel time(the optimal path) encounter several problems, such as high server pressure, low query efficiency, roads state without in-time updating. With the widespread use of smart cameras in the urban traffic and surveillance system, this paper maps the optimal path finding problem in the dynamic road network to the shortest routing problem in the smart camera networks. The proposed distributed optimal path generation algorithm employs the delay routing and caching mechanism. Real-time route update is also presented to adapt to the dynamic road network. The test result shows that this algorithm has advantages in both query time and query packet numbers.

• Journal of the military operations research society of Korea
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• v.25 no.1
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• pp.29-36
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• 1999

In this paper, we are concerned with the K-shortest loopless path problem. The MPS algorithm, recently proposed by Martins et al., finds paths efficiently because it solves the shortest path problem only one time unlike other algorithms. But its computational complexity has not been known yet. We propose a few techniques by which the MPS algorithm can be implemented efficiently. First, we use min-heap data structure for the storage of candidate paths in order to reduce searching time for finding minimum distance path. Second, we prevent the eliminated paths from reentering in the list of candidate paths by lower bounding technique. Finally, we choose the source mode as a deviation node, by which selection time for the deviation node is reduced and the performance is improved in spite of the increase of the total number of candidate paths.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.1
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• pp.61-67
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• 1999

There has been an ever increasing interest in mobile robot for home services. However, issues currently being investigated for path planning of the mobile robot is concentrated to solving the problem of finding the optimal path from the initial location to the final location under the given performance index. In this study, we newly present a sweeping algorithm for autonomous mobile robot to cover the whole closed area under the unknown environment. And we verify the validity the validity of the formalized algorithm by computer simulation with the changing environment conditions. In addition to this, we analyse the effect of real system implementation of the proposed algorithm to a experimental miniature mobile robit(Khepera).

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1389-1391
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• 1996

In this paper, we applies two methods - Genetic Algorithm(GA) and $A^*$ Algorithm - to find the optimal path in route guidance system. Under the assumption that the traveling costs of each link are given, the task to find the optimal path becomes very complicated problem if the number of nodes or links increase. Two well-known algorithms are modified to resolve the problem and the preliminary demonstration show both optimistic result and needs to improvement.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.19-31
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• 2016

A design method of the network for automated transporters mounted on rails is addressed for automated container terminals. In the network design, the flow directions of some path segments as well as routes of transporters for each flow requirement must be determined, while the total transportation and waiting times are minimized. This study considers, for the design of the network, the waiting times of the transporters during the travel on path segments, intersections, transfer points below the quay crane (QC), and transfer points at the storage yard. An algorithm, which is the combination of a modified Dijkstra's algorithm for finding the shortest time path and a queuing theory for calculating the waiting times during the travel, is proposed. The proposed algorithm can solve the problem in a short time, which can be used in practice. Numerical experiments showed that the proposed algorithm gives solutions better than several simple rules. It was also shown that the proposed algorithm provides satisfactory solutions in a reasonable time with only average 7.22% gap in its travel time from those by a genetic algorithm which needs too long computational time. The performance of the algorithm is tested and analyzed for various parameters.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.2
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• pp.47-58
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• 2001

The purpose of this study is to present methods for determining the k most vital arcs (k-MVAs) in shortest path problem (SPP) using evolutionary algorithms. The problem of finding the k-MVAs in SPP is to find a set of k arcs whose simultaneous removal from the network causes the greatest increase in the shortest distance between two specified nodes. Generally, the problem of determining the k-MVAs in SPP has been known as NP-hard. Therefore, to deal with problems of the real world, heuristic algorithms are needed. In this study we present three kinds of evolutionary algorithms for finding the k-MVAs in SPP, and then to evaluate the performance of proposed algorithms.

• Journal of Information Processing Systems
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• v.13 no.1
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• pp.104-113
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• 2017

In this paper, we present an approach to transmit data from the source to the destination through a minimal path (least-cost path) in a computer network of n nodes. The motivation behind our approach is to address the problem of finding a minimal path between the source and destination. From the work we have studied, we found that a Steiner tree with bounded Steiner vertices offers a good solution. A novel algorithm to construct a Steiner tree with vertices and bounded Steiner vertices is proposed in this paper. The algorithm finds a path from each source to each destination at a minimum cost and minimum number of Steiner vertices. We propose both the sequential and parallel versions. We also conducted a comparative study of sequential and parallel versions based on time complexity, which proved that parallel implementation is more efficient than sequential.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.2
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• pp.63-70
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• 2009

This paper proposes a novel path finding approach of a mobile robot using RF strength in sensor network. In the experiments based on the proposed method, a mobile robot attempts to find its location, heading direction and the shortest path in the indoor environment. The experimental system consisting of mesh network shares node data and send them to base station. The triangulation and the proposed Grid method calculate the location and heading angle of the robot. In addition, the robot finds the shortest path by using the base station attached on it to receive data of environment around each node. Kalman filter reduces the straight line error when the robot estimates the strength of received signal. The experimental results show the effectiveness of the proposed algorithm.