Research on Efficient Algorithm of Robot Along the Wall Combined With Historical Motion State
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摘要: 针对目前室内移动机器人沿墙走算法过于复杂、路径易重复、不能完全遍历、效率低等问题, 采用室内未知环境下结合历史状态的机器人沿墙高效遍历研究来解决这些问题. 该算法由移动机器人的上一个周期历史环境运动状态(分8类)、当前环境运动状态(分8类)和旋向信息(分2类)建立运动规则库, 沿墙行走时移动机器人时时采集这三类信息(上一个周期历史环境运动状态、当前环境运动状态和旋向信息)决定移动机器人当前的运动方向, 如此循环直到完成指定的沿墙任务. 最后对该算法进行了仿真与实际实验, 实验结果证明该算法可以在不同的、复杂的环境中高效、快速地完成沿墙走的任务, 并且对室内未知环境有很好的适应性.Abstract: The indoor mobile robots moving along the wall will encounter the issue of complex algorithm, easy repetitive path, partial traversal and low efficiency, to end these problems, efficient traversal research of robots along the wall in the unknown environment is proposed in this work. The algorithm establishes a motion rule based on the previous cycle historical environment motion state of the mobile robot (in 8 categories), the current environmental motion state (in 8 categories), and the direction information (in 2 categories). The mobile robot collects timely while walking along the wall. These three types of information (previous cycle historical environment motion state, current environmental motion state, and direction information) determine the current motion direction of the mobile robot, and thus cycle until the specified wall-to-wall task is completed. Finally, the algorithm is simulated and experimented. The experimental results show that the algorithm can efficiently and quickly complete the task along the wall in different and complex environments, which indicates that the algorithm has good adaptability to indoor unknown environment.
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图 14 室内中央有墙体的模拟环境
Fig. 14 A simulated environment with a wall in the center of the room
图 18 拐角较多环境下
$ k $ 值变化Fig. 18 Change in
$ k $ value in indoor simulated environment with more corners
图 20 室内中央有墙体的模拟环境下
$ k $ 值变化Fig. 20 Change in
$ k $ value in a simulated environment with a wall in the center of the room
图 21 拐角较多环境下机器人运动方向判断局部图
Fig. 21 Partial diagram of the direction of motion of the robot in a corner environment
图 23 室内中央有墙体下机器人运动方向判断局部图
Fig. 23 The local figure of the movement direction of the robot under the wall in the center of the room
图 19 不规则墙体模拟下
$ k $ 值变化Fig. 19 Variation of
$ k $ value under irregular wall simulation
图 22 不规则墙体下机器人运动方向判断局部图
Fig. 22 Figure of the motion direction of the robot under the irregular wall
图 26 空环境下采用算法与不采用算法对比图
Fig. 26 Comparison diagram between using algorithm and not using algorithm in empty environment
表 1 移动机器人运动转向判断关系
Table 1 Mobile robot motion steering judgment relationship
$k$ $k_1$ 1 2 3 4 5 6 7 8 1 前进 左转 $f_x$ 决定右转 左转 右转 $f_x$ 决定$f_x$ 决定2 前进 前进 前进 右转 前进 右转 $f_x$ 决定$f_x$ 决定3 $f_x$ 决定左转 $f_x$ 决定右转 左转 右转 $f_x$ 决定$f_x$ 决定4 前进 左转 前进 前进 左转 前进 $f_x$ 决定$f_x$ 决定5 右转 右转 右转 右转 右转 右转 右转 右转 6 左转 左转 左转 左转 左转 左转 左转 左转 7 前进 前进 前进 前进 前进 前进 前进 前进 8 $f_x$ 决定右转 $f_x$ 决定左转 右转 左转 $f_x$ 决定$f_x$ 决定
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表 2 机器人沿墙顺时针行走运动转向判断表
Table 2 Robot walking along the wall clockwise movement steering judgment table
$k$ $k_1$ 1 3 7 8 1 左转 左转 左转 2 前进 前进 3 右转 右转 左转 左转 4 左转 左转 8 右转 右转 右转 右转
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表 3 机器人沿墙逆时针行走运动转向判断表
Table 3 Counterclockwise walking movement steering judgment table of robot along the wall
$k$ $k_1$ 1 3 7 8 1 右转 右转 右转 2 右转 右转 3 左转 左转 右转 右转 4 前进 前进 8 左转 左转 左转 左转
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表 4 机器人状态转移表
Table 4 Robot state transfer table
$k$ $k_1$ 1 2 3 4 5 6 7 8 1 $p_{11}$ $p_{12}$ $p_{13}$ $p_{14}$ $p_{15}$ $p_{16}$ $p_{17}$ $p_{18}$ 2 $p_{21}$ $p_{22}$ $p_{23}$ $p_{24}$ $p_{25}$ $p_{26}$ $p_{27}$ $p_{28}$ 3 $p_{31}$ $p_{32}$ $p_{33}$ $p_{34}$ $p_{35}$ $p_{36}$ $p_{37}$ $p_{38}$ 4 $p_{41}$ $p_{42}$ $p_{43}$ $p_{44}$ $p_{45}$ $p_{46}$ $p_{47}$ $p_{48}$ 5 $p_{51}$ $p_{52}$ $p_{53}$ $p_{54}$ $p_{55}$ $p_{56}$ $p_{57}$ $p_{58}$ 6 $p_{61}$ $p_{62}$ $p_{63}$ $p_{64}$ $p_{65}$ $p_{66}$ $p_{67}$ $p_{68}$ 7 $p_{71}$ $p_{72}$ $p_{73}$ $p_{74}$ $p_{75}$ $p_{76}$ $p_{77}$ $p_{78}$ 8 $p_{81}$ $p_{82}$ $p_{83}$ $p_{84}$ $p_{85}$ $p_{86}$ $p_{87}$ $p_{88}$
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