论文标题
确定具有最小数据的水下群的空间配置
Determination of spatial configuration of an underwater swarm with minimum data
论文作者
论文摘要
该主题是线束项目框架中的一群自主水下机器人（AUV）的本地化问题；通过定位，我们的意思是相对群构型，即组的几何形状。结果是通过使用机器人交换的信号来实现的。该群是由规则组织的，并构想执行任务，从环境监测到恐怖主义攻击监视。提出了两种确定群体形状的方法，均基于三尾液计算。第一种方法侧重于机器人的速度。在这种情况下，我们使用机器之间的速度和距离的知识，而第二种方法仅考虑机器人的距离和方向角。与三材问题不同，我们不知道信标的位置，这使问题很难。而且，我们很少有数据。由于系统的对称性以及一个或多个目标函数的优化过程，需要多个运动步骤来解决找到的多个解决方案。随后，我们使用模拟器考虑了影响测量结果的随机错误检查了我们的算法
The subject is the localization problem of an underwater swarm of autonomous underwater robots (AUV), in the frame of the HARNESS project; by localization, we mean the relative swarm configuration, i.e., the geometrical shape of the group. The result is achieved by using the signals that the robots exchange. The swarm is organized by rules and conceived to perform tasks, ranging from environmental monitoring to terrorism-attack surveillance. Two methods of determining the shape of the swarm, both based on trilateration calculation, are proposed. The first method focuses on the robot's speed. In this case, we use our knowledge of the speeds and distances between the machines, while the second method considers only distances and the orientation angles of the robots. Unlike a trilateration problem, we do not know the position of the beacons and this renders the problem a difficult one. Moreover, we have very few data. More than one step of motion is needed to resolve the multiple solutions found, owing to the symmetries of the system and optimization process of one or more objective functions leading to the final configuration. We subsequently checked our algorithm using a simulator taking into account random errors affecting the measurements
