摘要
为了提高井下救灾机器人的搜救效率,减少救援时间,提出了一种结合共轭梯度和粒子群算法的救灾机器人路径规划算法CGPSO。共轭梯度算法规划出起点到终点的最短路径;去除路径中在障碍物内的点,采用粒子群算法重新规划该子路径。仿真实验表明该算法可以有效地提高粒子群的规划效率和可靠性。
In order to raise the efficiency of rescue for robot in underground mine and decrease rescue-time, a path planning algorithm named CGPSO is proposed for path planning of coal mine recuse robot in this paper. This algorithm combine conjugate gradient method and particle swarm optimization. Conjugate gradient method is used to search the shortest path from start point to destination; Deleting points which are in the obstacle area and re-planning this path section. Simulation indicated that CGPSO is more efficient and reliable than PSO.
出处
《煤矿机械》
北大核心
2013年第7期62-64,共3页
Coal Mine Machinery
关键词
煤矿救灾机器人
路径规划
共轭梯度
粒子群
coal mine rescue robot
path planning
conjugate gradient
particle swarm optimization
