摘要
为机器人在复杂地质条件下规划最佳井下避障巡检路线,合理指导矿用智能巡检机器人高效率巡检,研究复杂地质条件下矿用智能巡检机器人自动避障方法。以最快前进运动和保持目标方向统一为矿用智能巡检机器人巡检目标函数,建立巡检路径规划数学模型;以模型为基础,通过改进蚁群算法获取从矿用智能巡检机器人初始点位置到终止点位置的最优路径;利用人工势场法将最优路径与自动避障问题相结合,通过叠加引力和斥力的势场合力,判断复杂地质条件下障碍物位置,实现矿用智能巡检机器人在复杂的地质环境中自动避障规划。实验结果表明,该方法可实现复杂地质条件下矿用智能巡检机器人避障路径规划,矿用智能巡检机器人可在最短时间内成功躲避障碍物,用较少的迭代次数便可获取最短避障路径。
Study the automatic obstacle avoidance method of intelligent mining inspection robots under complex geological conditions,plan the optimal underground obstacle avoidance inspection route for robots under complex geological conditions,and reasonably guide the efficient inspection of mining intelligent inspection robots.Establish a mathematical model for inspection path planning by unifying the fastest forward motion and maintaining the target direction as the inspection objective function of mining intelligent inspection robots.Based on the model,an improved ant colony optimization algorithms is used to obtain the optimal path from the initial point position to the end point position of the intelligent inspection robot for mining.By combining the optimal path with the automatic obstacle avoidance problem using the artificial potential field method,the position of obstacles under complex geological conditions can be determined through the combined force of gravitational and repulsive potential fields,achieving automatic obstacle avoidance planning for mining intelligent inspection robots in complex geological environments.The experiment shows that this method can achieve obstacle avoidance path planning for mining intelligent inspection robots under complex geological conditions.The mining intelligent inspection robot can successfully avoid obstacles in the shortest possible time and obtain the shortest obstacle avoidance path with fewer iterations.
作者
王旭辉
魏鸣
张红娥
WANG Xuhui;WEI Ming;ZHANG Honge(Henan Academy of Geology,Zhengzhou 450016,China;Henan Institute of Geological Sciences Co.,Ltd.,Zhengzhou 450001,China)
出处
《电子设计工程》
2024年第22期82-86,共5页
Electronic Design Engineering
基金
河南省自然科学基金项目(182300410106)。
关键词
复杂地质条件
巡检机器人
自动避障
蚁群算法
人工势场法
最优路径
complex geological conditions
inspection robot
automatic obstacle avoidance
ant colony algorithm
artificial potential field method
optimal path
