基于子目标的中型足球机器人ERSOW动态避障研究

Renardi Adryantoro Priambudi, Iwan Kurnianto Wibowo, Bagus Nugraha Deby Ariyadi, B. S. B. Dewantara, M. Bachtiar, Erna Alfi Nurrohmah
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引用次数: 1

摘要

提出了一种基于足球机器人的虚拟障碍物增强子目标生成算法。我们需要考虑的一件事是我们的机器人在处理障碍时的行为。机器人必须拥有的最具挑战性的能力是尽可能快地避开场地上的障碍物。避障技术必须适应对手机器人的高动态运动,并且计算量要低。子目标算法是考虑到每个目标的速度和机器人足球环境的正确答案。采用线性等速法将速度转换为若干虚拟障碍物,并将其输入子目标算法。根据实验结果进行了分析。如果我们的机器人速度和对手机器人速度的虚拟障碍都不超过限制,这个算法就能很好地工作。机器人速度可达70厘米/秒。该机器人能够100%的成功避开多个静态障碍物和单个静态障碍物。在第二个实验中,我们尝试了0.25 m/s, 0.6 m/s, 0.65 m/s不同的虚拟障碍物设定值速度,机器人可以正确避开,成功率为100%。第三,我们增加虚拟障碍物的速度,直到1 m/s的极限,机器人的成功率下降到90%。如果我们继续提高速度,这种趋势将在其余部分变得更糟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic Obstacle Avoidance on Middle Size League Robot Soccer ERSOW Using Subtargets
This paper presents the generation of a virtual obstacle to enhance subtargets algorithm that is implemented on robot soccer. One thing that we need to consider is the behavior of our robot when dealing with obstacles. The most challenging ability that must be owned by the robot is to avoid obstacles on the field as fast as possible. Obstacle avoidance skills must be adaptive to highly dynamic movement of the opponent robot and must have cheap computation. Subtargets algorithm is the right answer with considering the speed of each object and the environment of robot soccer. Speed will be converted to several virtual obstacles using a linear constant velocity method and will be input for subtargets algorithm. Based on the result of the experiments have been done. This algorithm worked great if both our robot speed and the virtual obstacles of the opponent robot speed are not exceeding the limits. Robot speed can reach 70 cm/s. The robot has a 100% rate of success to avoid both multiple static obstacles and single static obstacles flawlessly. In the second experiment, we try with different setpoint speeds of virtual obstacle which is 0.25 m/s, 0.6 m/s, 0.65 m/s and the robot can avoid correctly with a 100% rate of success. Third, we increase the virtual obstacles speed until the limits on 1 m/s, the robot is decreasing the rate of success to 90%. This trend will get worst on the rest of the speed if we keep increasing it.
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