摘要
针对传统移动机器人在多目标点的导航问题--多目标点的最优遍历和移动机器人的避障运行,设计了一种基于多传感器融合同步定位与地图构建(SLAM)移动机器人。通过引入基于外观的实时建图(RTAB-Map)及Gmapping算法对比,优化参数,构建优质地图,利用蚁群优化(ACO)算法对多目标点进行最优遍历。对于传统的A^(*)算法,提出一种分段多阶次贝塞尔曲线优化路径轨迹,利用Python仿真,验证其可行性,并构建地图对算法进行验证,结果表明:该移动机器人能够实现自主导航和建图,并从地图质量、路径距离、功能性、路径平滑度等验证该设计的可行性,运动效率更高,安全性和鲁棒性均有提升。
Aiming at the navigation problems of traditional mobile robots in multi-target points,two aspects are considered:optimal traversal of multiple target points and obstacle avoidance for mobile robots.A mobile robot based on multi-sensor fusion simultaneous localization and mapping(SLAM)is designed.By integrating real-time appearance-based mapping(RTAB-Map)and Gmapping algorithms,parameters are optimized to construct highquality maps.Meanwhile,the ant colony optimization(ACO)algorithm is utilized for the optimal traversal of multitarget points.For the traditional A^(*)algorithm,a segmented multi-order Bezier curve is proposed to optimize the path trajectory.The feasibility is verified through Python simulation,and maps are constructed to validate the algorithm.The results indicate that the mobile robot can achieve autonomous navigation and mapping,and the feasibility of the design is verified from map quality,path distance,functionality,and path smoothness.The motion efficiency is improved,and both safety and robustness are enhanced.
作者
徐耀辉
刘祚时
李凯杰
XU Yaohui;LIU Zuoshi;LI Kaijie(School of Mechanical and Electrical Engineering,Jiangxi University of Science and Technology,Ganzhou 341000,China)
出处
《传感器与微系统》
北大核心
2026年第4期7-11,共5页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(52365033)。
