This paper presents a novel real-time path planning algorithm, called Insertbug, for an autonomous mobile agent in completely unknown environment. By using the algorithm, all the planned paths are described and stored...
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This paper presents a novel real-time path planning algorithm, called Insertbug, for an autonomous mobile agent in completely unknown environment. By using the algorithm, all the planned paths are described and stored by vectors. The algorithm combines range sensor data with safety radius to determine the blocking obstacles and calculate the shortest path by choosing the intermediate points. When there is obstacle blocking the current path, the intermediate points will be calculated, and the planned path will be regenerated by inserting the intermediate points. The local optimum avoidance strategy is also considered in this algorithm by specifying a fixed direction. The agent will return to the optimal direction after running out of the local optimum. Different simulation parameters are taken to show the advantages of this algorithm. Moreover, the performance of this algorithm has also been evaluated by comparing with another usual method via simulations. The results show that the safety performance and time requirements of this algorithm are significant superior to the algorithm contrasted with.
The bug algorithm family are well-known robot navigation algorithms with proven termination conditions for unknown environments. Eleven variations of bug algorithm have been implemented and compared against each other...
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The bug algorithm family are well-known robot navigation algorithms with proven termination conditions for unknown environments. Eleven variations of bug algorithm have been implemented and compared against each other on the EyeSim simulation platform. This paper discusses their relative performance for a number of different environment types as well as practical implementation issues.
The scope of this paper is to analyze and compare three path planning methods for omni-directional robots, which are based on a) the bug algorithm b) the Potential Fields algorithm, and c) the A* algorithm for minimum...
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ISBN:
(纸本)9781424405367
The scope of this paper is to analyze and compare three path planning methods for omni-directional robots, which are based on a) the bug algorithm b) the Potential Fields algorithm, and c) the A* algorithm for minimum cost path with multiresolution grids. The approaches are compared in terms of computational costs and the resulting path lengths. Results obtained indicate that the bug algorithm is a suitable choice for this type of application as its computational cost is lower than that of the other methods. Furthermore, minor modifications of the standard bug algorithm, such as the tangent following modification, allow the path planner to handle well the situations encountered in typical multi-robot environments.
Práce se zabývá návrhem mobilního robotu pro pohyb v neznámém prostředí. Úvod práce se věnuje rešerši v oblasti možností konstrukce mobilních robotů, vhodn&...
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Práce se zabývá návrhem mobilního robotu pro pohyb v neznámém prostředí. Úvod práce se věnuje rešerši v oblasti možností konstrukce mobilních robotů, vhodných typů senzorů, algoritmům pro plánování trasy a řízení robotu. Druhá část práce se zabývá samotnou konstrukcí robotu. Robot je poté sestaven a jsou na něm testovány vybrané algoritmy pro plánování trasy v praxi.
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