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基于混合整数线性规划的爬壁机器人路径规划
引用本文:岳荣刚,王少萍.基于混合整数线性规划的爬壁机器人路径规划[J].北京航空航天大学学报,2013,0(6):792-797.
作者姓名:岳荣刚  王少萍
作者单位:中国空间技术研究院钱学森空间技术实验室,北京,100094;北京航空航天大学自动化科学与电气工程学院,北京,100191
基金项目:111计划资助项目;LIA资助项目
摘    要:为研究City-Climber爬壁机器人在3D建筑物环境中的路径规划问题,基于混合整数线性规划(MILP, Mixed Integer Linear Programming),提出了一种适用于City-Climber的路径规划方法.为了用MILP方法解决避障问题,首先用限制机器人控制输入的方法对City-Climber的数学模型进行解耦和线性化,再介绍了用MILP方法对控制输入进行描述的数学表达式,并提出了适用于爬壁机器人的新型代价函数,最后以一个方形房间为运动环境,用AMPL和CPLEX优化软件,以及Matlab软件解算路径规划问题.仿真结果表明:MILP方法较好地解决了City-Climber在3D环境下的路径规划和避障问题.

关 键 词:爬壁机器人  混合整数线性规划  路径规划  避障
收稿时间:2012-06-05

Path planning of a climbing robot using mixed integer linear programming
Yue RonggangQian Xuesen Laboratory of Space Technology,China Academy of Space Technology,Beijing,China Wang Shaoping.Path planning of a climbing robot using mixed integer linear programming[J].Journal of Beijing University of Aeronautics and Astronautics,2013,0(6):792-797.
Authors:Yue RonggangQian Xuesen Laboratory of Space Technology  China Academy of Space Technology  Beijing  China Wang Shaoping
Institution:1. Qian Xuesen Laboratory of Space Technology, China Academy of Space Technology, Beijing 100094, China;2. School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
Abstract:To study path planning problem in 3D building environments for a climbing robot which is named as City-Climber, a path planning method using mixed integer linear programming (MILP) was developed. In order to use MILP to solve obstacle avoidance problems, the robot dynamic model was simplified and decoupled into linear system by introducing a restricting admissible control. The decoupled model can be rewritten as a linear program with mixed integer linear constraints that account for the collision avoidance. Moreover, a new cost function that is suitable for wall-climbing robot was proposed. A key benefit of this approach is that the path optimization can be readily solved using the AMPL and CPLEX optimization software with a Matlab interface. Simulation results in a cuboid room show that the framework of MILP is suited for path planning and obstacle avoidance problems for the climbing robot in 3D building environments.
Keywords:
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