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Quasi-real-time confined environment path generation for mobile robotic manipulator arms

机译:移动机器人机械臂的准实时受限环境路径生成

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摘要

Path generation for mobile robotic manipulator arms is challenging in dynamic environments because high-speed calculations are required to deal with fast-moving obstacles. A novel path-planning algorithm has been developed which solves in quasi-real time the problem of path generation in confined environments for interconnected multi-body systems, specifically a robotic manipulator arm with three links. The work presented in this article builds upon the previous work by reformulating the technique to increase the speed at which the algorithm is able to calculate a safe path. The complexity of the task space has increased substantially compared to previous work, and the algorithm has been reformulated to speed up the calculation in order to maintain or even improve its ability to plan a safe path in real time. The method is now able to calculate a safe path through environments significantly more quickly than the previous method, and the results presented in this article expand the complexity of the environment by a large amount and test the ability of the reformulated algorithm to still operate in real time, which the method achieves. It was found that the reformulated method reduces the calculation time for path generation exponentially when used to plan safe paths through test environments involving different numbers of obstacles. The new algorithm thus has the potential to facilitate path planning in challenging dynamic environments, such as those used in sensitive manufacturing and maintenance tasks as well as bomb disposal and similar applications.
机译:在动态环境中,移动机器人操纵器臂的路径生成具有挑战性,因为需要高速计算来应对快速移动的障碍物。已经开发了一种新颖的路径规划算法,该算法准实时地解决了在受限环境中互连多体系统(特别是具有三个链接的机械手臂)在路径生成中的问题。本文介绍的工作是在先前的工作基础上,通过重新设计技术来提高算法能够计算安全路径的速度。与以前的工作相比,任务空间的复杂性已大大增加,并且对算法进行了重新设计以加快计算速度,从而维持甚至提高其实时规划安全路径的能力。该方法现在能够比以前的方法更快地计算出通过环境的安全路径,并且本文中提供的结果大大扩展了环境的复杂性,并测试了重新制定的算法仍可在实际环境中运行的能力该方法实现的时间。结果发现,当用于计划通过涉及不同数量障碍物的测试环境的安全路径时,重新制定的方法以指数方式减少了路径生成的计算时间。因此,新算法具有在挑战性的动态环境中促进路径规划的潜力,例如在敏感的制造和维护任务以及炸弹处理和类似应用中使用的那些环境。

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