基于IBWO-TEB算法的移动机器人自主路径规划  

Mobile robot autonomous path planning based on IBWO-TEB algorithm

作　　者：梁凯 韩西 LIANG Kai;HAN Xi(Science and Technology Information Research Institute of Ganzi Tibetan Autonomous Prefecture,Kangding 626000,CHN)

机构地区：[1]甘孜藏族自治州科学技术信息研究所,四川康定626000

出　　处：《制造技术与机床》2025年第3期49-55,共7页Manufacturing Technology & Machine Tool

基　　金：国家自然科学基金项目(62173319)。

摘　　要：为解决移动机器人自主进行路径规划时存在的规划效率低、动态性不足、环境适应力差等问题,提出一种结合改进白鲸优化算法(improved beluga whale optimization,IBWO)和时间弹性带(timed elastic band,TEB)的路径规划方法。首先,利用准对立学习机制和自适应螺旋捕食策略改进的IBWO算法进行全局规划,从而获取全局寻优阶段的最佳路径。其次,在局部规划阶段,采用改进的两阶段TEB算法,根据当前实时环境对全局最佳路径进行局部调整及优化。最后,在不同场景下进行仿真及试验,仿真结果表明IBWO-TEB算法较其他算法在行驶距离、规划时长方面均更短;试验验证了IBWO-TEB算法优良的真实性能,可有效帮助移动机器人完成自主路径规划。To solve problems such as low planning efficiency,insufficient dynamics and poor environmental adaptability when mobile robots independently carry out path planning,a path planning method combining improved beluga whale optimization(IBWO)and timed elastic band(TEB)was proposed.Firstly,the IBWO algorithm was improved by a quasi-opposition learning mechanism and adaptive spiral predation strategy was used for global planning,to obtain the optimal path in the global optimization stage.Secondly,in the local planning stage,the improved two-stage TEB algorithm was used to locally adjust and optimize the global optimal path according to the current real-time environment.Finally,simulation and experiments were carried out in different scenarios,and the simulation results show that the IBWO-TEB algorithm was shorter than other algorithms in terms of driving distance and planning time.The experiment verified the excellent real performance of the IBWO-TEB algorithm,which can effectively help mobile robots to complete autonomous path planning.

关 键 词：白鲸优化算法 时间弹性带 移动机器人 路径规划 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] TP18[自动化与计算机技术—控制科学与工程]