信息与控制2025，Vol.54Issue(4)：556-569,14.DOI:10.13976/j.cnki.xk.2024.2691
面向RatSLAM的一种改进的基于RRT算法的自主探索策略
An Improved Autonomous Exploration Strategy Based on RRT Algorithm for RatSLAM
摘要
Abstract
Rat-simultaneous localization and mapping(RatSLAM)is a brain-inspired navigation model that simulates the neural processing mechanisms of navigation in the rodent brain.Unfortunately,the existing RatSLAM systems primarily rely on passive datasets for experimentation and map building.This passive SLAM approach generally involves collecting environmental data through preset paths or manually controlling the robot,which often limits its performance in new environments.To overcome this limitation,this paper reports the proposal of an improved autonomous exploration strategy based on the rapidly exploring random tree(RRT)algorithm for active environmental ex-ploration.The existing mainstream autonomous exploration algorithms are generally characterized by their insufficient coverage of the internal areas of target environments and may require frequent path adjustments in dynamic environments,which is not conducive to the localization and map up-dating performances of RatSLAM.Conversely,conventional RRT algorithm-based autonomous ex-ploration strategies can efficiently explore high-dimensional,complex environments,adapt to dy-namic changes in real time,and provide comprehensive environmental data.However,the paths generated by these exploration methods are not always sufficiently smooth,do not conform to the regularities of exploring animals' environments,and cannot readily simulate the real movement trajectories of animals,thus failing to satisfy the data collection requirements of brain-inspired nav-igation.Therefore,an improved autonomous exploration strategy is proposed in this study based on the integration of the RRT algorithm with the RatSLAM system.This strategy enables the autono-mous movement of a robot to collect environmental data in unknown environments,whereas the in-tegrated RatSLAM system processes these data to generate a cognitive map of the target environ-ment.Finally,the results obtained from simulation and real-world experiments reveal that the pro-posed method achieves good results in active map building,similar to how biological entities ex-plore environments,thereby validating the feasibility of the algorithm.关键词
自主探索/RatSLAM/机器人操作系统/移动机器人Key words
autonomous exploration/RatSLAM/robot operating system(ROS)/mobile robot分类
信息技术与安全科学引用本文复制引用
武彤,张志慧,唐凤珍,许茗..面向RatSLAM的一种改进的基于RRT算法的自主探索策略[J].信息与控制,2025,54(4):556-569,14.基金项目
辽宁省优秀青年基金计划项目(202402112-JH3/102) （202402112-JH3/102）
沈阳市中青年科技创新人才培养专项(RC231112) （RC231112）
