Teach-and-Replay of Mobile Robot with Particle Filter on Episode
Teach-and-Replay of Mobile Robot with Particle Filter on Episode
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DOI：
10.1109/icra.2018.8461235
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发表时间：
2018-05
期刊：
影响因子：
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通讯作者：
R. Ueda;Masahiro Kato;Atsushi Saito;Ryo Okazaki
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文献类型：
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作者：
R. Ueda;Masahiro Kato;Atsushi Saito;Ryo Okazaki
本文提出了一种根据移动机器人的历史记忆重现其行为的新方法。该方法是一种基于情节的粒子滤波算法(PFoE)，它在内存中加入粒子过滤器，以有效地发现与当前情况相似的情况。虽然最初的PFoE是作为一种强化学习方法提出的，但我们曾经将奖励机制从原来的PFoE中删除，以便将其应用于任务教学。在实验中，我们通过一个游戏手柄，用所提出的方法给出了一个微型鼠标机器人的几种运动。在多次重复示教后，机器人通过传感器反馈实现了行为的稳健再现。
A novel method for replaying behavior of a mobile robot from its memory of past experiences is presented in this paper. The method is a version of a particle filter on episode (PFoE), which applies a particle filter on the memory so as to efficiently find some similar situations with the current one. Though the original PFoE was proposed as a reinforcement learning method, we once removed the reward system from the original one so as to apply it to task teaching. In the experiment, we gave several kinds of motion to a micromouse type robot with the proposed method through a gamepad. The robot replayed the behaviors robustly with sensor feedback after several number of repetitive teaching.