基于量化的势场值在机器人路径规划中的应用  

Application of Quantized Potential Field Value on Robot Path Planning

作　　者：金何[1] 王烈准[1] JIN He;WANG Liezhun(School of Automotive and Mechanical Engineering,Lu＇an Vocational Technical College,Lu＇an 237000,China)

机构地区：[1]六安职业技术学院汽车与机电工程学院,安徽六安237000

出　　处：《邵阳学院学报（自然科学版）》2018年第5期21-26,共6页Journal of Shaoyang University：Natural Science Edition

基　　金：六安职业技术学院科研项目(XJKY201602);安徽省质量工程项目(2016msgzs068)

摘　　要：文中针对动态环境中机器人的避障问题,提出了基于量化的势场值的路径规划算法。势场值的大小表明了机器人从当前的位置和时间,向前随机的行进一步,撞上障碍物的概率。机器人通过使用当前的速度推算出它的位置,规划出一条路径,并计算从开始直到先行值时的势场值,先行值是由连通图评价指标计算出的最小路径长度来决定的。最后用Matlab对文中提出的算法进行仿真,仿真结果表明该算法的有效性和可行性。Aiming at the obstacle avoidance of robot in dynamic environment, a path planning algorithm was proposed based on the quantized potential field values whose size indicate the probability that a robot would collide with an obstacle, assuming that the robot executes a random walk from the current location and the time onwards. The robot planed a path by extrapolating its location using current velocities and by calculating the potential field values from start to a look-ahead value that was determined by calculating the minimum path length using connectivity evaluation index. Finally, the algorithm proposed was simulated with Matlab, and the simulation results show the effectiveness and feasibility of the algorithm.

关 键 词：量化 势场值 路径规划 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]