摘要
针对复杂环境自动化机器人的路径规划问题,采用改进的人工势场法与改进的A*算法进行路径规划寻优;同时,针对机器人轨迹跟踪控制问题,提出基于干扰观测器的自适应滑模控制算法。结果显示,与传统算法相比,改进后的A*算法的转弯角度减少了37.43%,路径长度减少了2.21%,为机器人提供了安全且平滑的路径,实现了全局路径优化。与传统人工势场法相比,采用改进后的人工势场法不仅使运行时间降低了59.13%,而且使路径长度减少了52.3%,既避免了在障碍物附近震荡,又绕过局部极小值陷阱区域。而基于干扰观测器构建的自适应滑膜控制算法,既能有效降低跟踪误差,又能有效提升机器人轨迹跟踪的收敛速度。因此,自动化机器人轨迹跟踪与路径规划技术研究的创新性,表现为既有效弥补了传统人工势场法的缺点与不足,又实现了自动化机器人轨迹跟踪在线估算最优增益。
For the path planning problem of automated robots in complex environments, the improved artificial potential field method and the improved A* algorithm are adopted for path planning optimization;meanwhile, for the robot trajectory tracking control problem, the adaptive sliding mode control algorithm based on interference observer is proposed. The results show that compared with the traditional algorithm, the improved A* algorithm reduces the turning angle by 37.43% and the path length by 2.21% and provides a safe and smooth path for the robot to achieve global path optimization. Compared with the traditional artificial potential field method, the use of the improved artificial potential field method not only reduces the running time by 59.13%, but also reduces the path length by 52.3%, avoiding both oscillation near obstacles and bypassing the local minimal value trap region. And the adaptive sliding film control algorithm constructed based on the interference observer can effectively reduce the tracking error as well as improve the convergence speed of robot trajectory tracking. Therefore, the innovation of the research on trajectory tracking and path planning technology for automated robots is demonstrated both by effectively compensating the shortcomings and deficiencies of the traditional artificial potential field method, and by realizing the online estimation of optimal gain for the trajectory tracking of automated robots.
作者
杨金铎
王林波
曾惜
王冕
周慧
YANG Jinduo;WANG Linbo;ZENG Xi;WANG Mian;ZHOU Hui(Guiyang Power Supply Bureau,Guizhou Power Grid Co.,Ltd.,Guiyang 550001,China;Guangzhou Zhongke Yuntu Intelligent Technology Co.,Ltd.,Guangzhou 510180,China)
出处
《自动化仪表》
CAS
2022年第7期40-45,共6页
Process Automation Instrumentation
基金
贵州电网有限责任公司科技基金资助项目(GZKJXM20190687)。
关键词
自动化机器人
A*算法
人工势场算法
滑模算法
轨迹跟踪
路径规划
全局路径寻求
Automated robot
A*algorithm
Artificial potential field algorithm
Sliding mode algorithm
Trajectory tracking
Path planning
Global path finding
