基于劳动分工的群机器人地图创建探索策略研究

受社会性昆虫劳动分工的启发提出一种群机器人地图创建的探索策略,以提高群机器人创建地图的效率。当机器人所在顶点位置有未访问的路径时,机器人随机选择一条未访问路径进行访问;如果当前位置的所有路径都已被访问,机器人会根据响应函数对下一访问位置进行概率选择。对算法分别进行了不同地图规模和机器人数量的计算机仿真实验,根据算法评价指标(覆盖时间、路径重复覆盖次数和覆盖率)对实验结果进行了评价,并与随机选择的算法进行了对比,结果表明算法是可行、有效的。最后指出了下一步研究的方向。

Research on exploration strategy in map building of swarm roboticsbased on model of division of labor

Inspiring of division labor of the social insect, this paper proposed an exploration strategy of mapping in swarm robotics to improve the map building efficiency of swarm robot. When the robot found the paths not visited on vertex position, it would randomly chose an unvisited path to access. If all the paths of the current location had been visited, it designed the response function of algorithm in terms of the model of division labor and robots selected the next position according to the given probability. The simulation experiment set up various numbers of vertexes in map and the numbers of robots according to the evaluation metrics which included total coverage time, path repeat coverage time, rate of coverage and so on. This paper evaluated and compared the experimental results with random selection algorithm. The results show that the algorithm is efficient. At last, it put forward the further research.