Abstract: This paper deals with the development of a desktop safety simulator (“simulator”) to ensure safe lathe turning (“cutting”). The revolving center for supporting work in the cutting plays an important role of holding the work against come-off and fly-off, though the revolving center is inclined to be avoided partly because its usage is bothersome. One of the possible worst cases due to no use of the revolving center is that a fatal accident is caused by the work come-off and fly-off. The necessity of using the revolving center depends on the protrusion length of the work from the chuck. However, the judgment of such necessity is too difficult to make for those who are not familiar with the cutting. In view of the above, this study intends to conduct experiments of risky work come-off and fly-off in order to clarify the conditions of the work come-off and fly-off and reflect the experimental data in the configuration of the simulator. To the configured simulator, the cutting conditions ar

• Publication Date: 11-Oct-2015
• DOI: 10.15224/978-1-63248-066-8-99
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Abstract: Sampling-based motion planning algorithms have been proven to work well with difficult planning tasks in a variety of problems. Recently, asymptotic optimal algorithms have been proposed to overcome the non-optimality inefficiency of these planners but with extra computational costs associated with the additional processing requirements. In this paper, new extensions of optimal sampling-based motion planning algorithms are presented which overcome this drawback by utilizing the Poisson-disk sampling distribution. The proposed planners replace the original uniform sampling with the Poisson-disk sampling by defining a sampling radius along with the neighborhood radius in the original optimal planners. The main advantage of the proposed planners is their ability to reach different levels of optimality with fewer sampling attempts which reduces the running time of the planner significantly. The proposed algorithms have shown to solve different motion planning tasks with considerably smalle

• Publication Date: 11-Oct-2015
• DOI: 10.15224/978-1-63248-066-8-105
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• Downloads: 0