CAJ | 학술논문

针对搜救环境中蛇形机器人实时地图构建中计算量大、实时性差等问题，提出一种 MiniSLAM算法。采用基于Monte-Carlo定位的粒子滤波算法对机器人位姿进行估计和更新，采用改进的 Bresenham 算法对环境地图进行更新。实验平台采用基于激光测距仪的自主研制的变结构仿生蛇形机器人，实验结果表明，与传统 SLAM相比，该算法计算量较少，实时性高，在复杂环境中精度高，适用于搜救环境下蛇形机器人的应用。
침대수구배경중사형궤기인실시지도구건중계산량대、실시성차등문제，제출일충 MiniSLAM산법。채용기우Monte-Carlo정위적입자려파산법대궤기인위자진행고계화경신，채용개진적 Bresenham 산법대배경지도진행경신。실험평태채용기우격광측거의적자주연제적변결구방생사형궤기인，실험결과표명，여전통 SLAM상비，해산법계산량교소，실시성고，재복잡배경중정도고，괄용우수구배경하사형궤기인적응용。
Aiming at the problems of large amount of calculation and poor real-time in real-time map building of snake-like robot in search and rescue environment,a MiniSLAM algorithm was presented.Based on Monte-Carlo particle filter positioning algo-rithmm,the pose of the robot was estimated and the modified Bresenham algorithm was used to update the environment map. Experimental platform used biomimetic snake-like robot with independently developed variable structure based on a laser range finder.Experimental results show that,compared with the traditional SLAM,the algorithm is of small amount of calculation, high real-time and high accuracy in complex environments.It is suitable for snake-like robot applications in search and rescue en-vironment.