摘要
精确的导航定位技术是机器人进行路径规划和避障的先决条件,在面对复杂多变的外部环境时,传统的路径规划算法收敛速度慢容易陷入局部最优,且单一传感器采集到的图像信息累计误差难以消除。针对这一情况,提出多传感器融合策略,将多个传感器采集到的场景信息通过一定的融合算法进行优势互补同时屏除冗余信息,增强系统的鲁棒性以及普适性;同时对传统的蚁群算法进行改进,采用动态参数对融合策略进行控制,降低死锁现象的发生增加避障能力,进而实现路径规划。通过实验仿真可知,该算法能够安全有效地得到最优路径,收敛速度得到了提升,具有一定的普遍适用性。
Accurate navigation and positioning technology is a prerequisite for robot path planning and obstacle avoidance.In the face of complex and changeable external environments,traditional path planning algorithms tend to converge slowly and easily fall into local optima,and image information collected by a single sensor The cumulative error is difficult to eliminate.In response to this situation,a multi-sensor fusion strategy is proposed.The scene information collected by multiple sensors is complemented by a certain fusion algorithm while eliminating redundant information,enhancing the robustness and universality of the system;The group algorithm is improved,and dynamic parameters are used to control the fusion strategy to reduce the occurrence of deadlock and increase the ability to avoid obstacles,thereby realizing path planning.Through experimental simulation,it can be known that the algorithm can safely and effectively obtain the optimal path,the convergence speed has been improved,and it has a certain general applicability.
作者
侯远韶
HOU Yuanshao(Department of Mechanical and Electrical Engineering,Henan Industry and Trade Vocational College,Zhengzhou,He’nan Province,451191 China)
出处
《科技创新导报》
2020年第31期85-87,共3页
Science and Technology Innovation Herald
基金
河南省高等学校重点科研项目计划:基于多传感器信息融合的移动机器人最优路径规划策略研究(项目编号:20A120007)。
关键词
导航定位
路径规划
信息融合
多传感器
机器人
Navigation and positioning
Route plan
Information fusion
Multi-sensor
