中文摘要：

研究了个体利益与整体利益在多机器人多目标观测（CMOMMT）问题中的表现以及采取不同折中方法对于系统性能的影响．引入代表机器人个性的利它性因子，提出了基于个性的多目标观测（P-CMOMMT）算法．根据观测时的具体环境、目标的观测情况以及机器人和目标的密度确定利它性的大小，从而决定牺牲个体利益的程度以及个体观测率来提升系统的整体利益和整体观测率．该算法解决了利己性与利它性之间的矛盾，在个体利益和整体利益之间、个体独自的观测率和系统整体的观测率之间进行折中．仿真表明，系统的整体观测率以及协作模式的多样性都得到了提高．

英文摘要：

The exhibition of individual benefit and collective benefit in cooperative multi-robot observation of multiple moving targets （CMOMMT） problem was discussed, and the influence of their compromise degree was investigated. An altruistic factor was introduced and an algorithm based on personality called P-CMOMMT was proposed. In P-CMOMMT, the environment, observation of targets, density of robots and targets were taken into consideration to set the altruistic factor, then the compromise degree between individual benefit and collective benefit was set. This algorithm can settle the conflict between altruism and selfishness and reach a compromise between individual benefit and collective benefit, and between the observation rates of single robot and the whole system. Simulation of the system performance showed the improvement of the collective observation rate and the diversity of cooperation mode.