基于态势评估技术的移动机器人局部路径规划  

Local Path Planning of Mobile Robot Based on Situation Assessment Technology

作　　者：柴慧敏[1] 方敏[1] 吕少楠 CHAI Hui-min;FANG Min;LV Shao-nan(School of Computer Science and Technology,Xidian University,Xi’an 710071,China)

机构地区：[1]西安电子科技大学计算机科学与技术学院,西安710071

出　　处：《计算机科学》2019年第4期210-215,共6页Computer Science

基　　金：陕西省工业科技攻关项目(2016GY-112)资助

摘　　要：从认知的角度,提出采用态势评估技术来求解移动机器人局部路径规划的问题。首先,在机器人坐标系下将机器人前方[10°,170°]的范围划分为5个区域,在二维激光测量数据与图像数据的融合结果中,提取不同区域的机器人环境态势要素;建立机器人行为选择贝叶斯网络模型,以机器人的环境态势要素为证据进行推理,选择推理结果中后验概率值最大的某种行为:直线行走、避障和逃离U型陷阱;对选择的行为处理后,依据声纳测量数据选择下一步要移动的栅格,并调整机器人的行进方向。11种典型仿真场景的测试中,1种场景测试失败,其余10种场景中机器人均能够以最短或次短的行进路线到达目的地。实验结果表明,利用态势评估技术解决移动机器人局部路径规划问题是一种有效且可行的方法。From the cognitive perspective,an approach by situation assessment technology was proposed for local path planning of mobile robot.First,the angle rang [10°,170°] in the front of mobile robot is divided into five parts under the robot coordinate system.The environmental situation factors of the five parts can be extracted for mobile robot from the fusion results of laser data and image data.Then,Bayesian networks model for robot action choosing is constructed.The environmental situation factors are regarded as evidences for the Bayesian networks mode.The inference can be made and the action in which the posterior probability is maximum is chosen.The action can be straight line walking,obstacle avoidance,escaping from U trap.Furthermore,the chosen action is processed to let robot move to the next grid.The next grid cell is chosen according to sonar data and the direction of robot is adjusted at the same time.Experiments including eleven typical simulation scenes were given.In these experiments,one scene test fails and the rest ten scenes are successful.In the ten scenes,mobile robot can reach the destination with the shortest route or secondary shortest route.The results show that the approach about situation assessment technology is effective and available for local path planning of mobile robot.

关 键 词：移动机器人 局部路径规划 态势评估 贝叶斯网络模型 栅格选择 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]