Current research of the cooperative obstacle-avoidance tracing is based on traditional flocking control model which was proposed by Reynolds and implemented by Tanner. The authors improved it and added the Steer to Avoid obstacle avoidance method. This model has a high efficiency in avoiding convex obstacle in tracking target. If the method is applied to the environment of concave obstacles, nodes will stuck in the concave zone and could not get out, because the target has an attraction power to nodes when it comes to a Steer to Avoid judgment. This paper proposed a new model for concave obstacles by further improving the Steer to Avoid method. The attraction from the target was temporarily cancelled when it came to a concave environment judgment, and then the path was constantly searched along the edge of obstacles. Finally, nodes could get out of the concave obstacles and reach target. The simulation results show that the proposed model, while compared to the traditional model, has a marked increase on average rate and time efficiency in avoiding obstacle. Also, it can succeed in avoiding mobile concave obstacles in unknown environment.%传统蜂拥控制模型在协同避障跟踪方面,目前有Reynolds和Tanner的蜂拥模型.笔者曾对其做出了改进,提出了与Steer to Avoid法则相结合的避障模型,该模型在跟踪过程中对凸形障碍有较高的避障效率.由于在Steer to Avoid的方向判断中,目标对节点具有引力,使节点群陷入凹形区域无法绕出.将协同避障模型引入凹形障碍环境中,对模型进一步改进,在Steer to Avoid转向判断时暂时取消目标对节点群的引力,让节点群在进入凹形后自行做出环境的判断并沿着障碍边缘不断搜索路径,最终绕出障碍到达目标.仿真实验结果表明:与传统两个模型相比,该模型在避障的平均速率和时间效率上有显著提高,适用于避开未知的凹形障碍.
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