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Parallel Object Motion Prediction in a Robotic Navigational Environment

机译:机器人导航环境中的并行对象运动预测

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In a dynamic Robot navigation system , the Robot has to deal with multiple number of moving objects in the environment simultaneously. The control loop of Robot motion planning comprising of sense-plan-act cycle has very short duration . Predicting the next instance position (Short Term Prediction) and the trajectory (Long Term Prediction) of moving objects in a dynamic navigation system is a part of sense-plan-act cycle. With increase in the number of moving objects under observation, the performance of the prediction techniques reduce gradually. To overcome this drawback, in this paper we propose a parallel motion prediction algorithm to keep track of multiple number of moving objects within the Robotic navigational environment. The implementation of parallel algorithm is done on a cluster computing setup. Performance of the algorithm is tested for different test case scenarios with detailed analysis on efficiency and speedup.
机译:在动态的机器人导航系统中,机器人必须同时处理环境中的多个移动物体。包括感觉计划-行动周期在内的机器人运动计划的控制环持续时间很短。预测动态导航系统中移动对象的下一个实例位置(短期预测)和运动轨迹(长期预测)是感知计划-行为循环的一部分。随着所观察的移动物体的数量增加,预测技术的性能逐渐降低。为了克服这个缺点,在本文中我们提出了一种并行运动预测算法,以跟踪机器人导航环境中的多个运动对象。并行算法的实现是在群集计算设置上完成的。通过针对效率和加速进行详细分析,针对不同的测试案例场景测试了算法的性能。

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