A general information quality based approach for satisfying sensor constraints in multirobot tasks
A general information quality based approach for satisfying sensor constraints in multirobot tasks
复制标题
一种基于通用信息质量的方法，用于满足多机器人任务中的传感器约束
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
L. Parker
中科院分区：
文献类型：
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作者：
Yu Zhang;L. Parker
许多架构已被提出来解决紧耦合多机器人任务（MT）通过联盟的异构机器人。然而，若干问题仍未得到解决。随着联盟的形成，机器人之间的传感器约束也建立起来。例如，在领导者-跟随者任务中，跟随者机器人必须将领导者机器人保持在他们的视线内，而在推箱子任务中，监督机器人需要跟踪箱子的移动方向并监视推到目标的路径以避免障碍物。如何在整个执行过程中，从初始配置到任务的完成，保持这些约束满足的问题，仍然是一个悬而未决的问题。此外，静态和动态的环境因素也会影响约束的维持。此外，在当前情况下，当约束条件无法满足时，就会出现问题。例如，引线的视线可能被阻挡，或者可能有障碍物阻挡了盒子的视线。本文提出了一种通用的方法来解决这些问题的各种应用具有一定的特性的传感器。我们的方法结合使用传感器模型，环境采样，信息质量的措施，采样的运动模型，和约束模型。我们相信，这种方法提供了第一个通用的制定机器人传感器的限制，可以应用到各种各样的应用。为了说明这种方法，我们应用该方法来解决机器人跟踪和导航任务，在模拟和物理机器人。实验结果表明了该方法的灵活性和鲁棒性。
Many architectures have been proposed to solve tightly-coupled multirobot tasks (MT) through coalitions of heterogeneous robots. However, several issues remain unaddressed. As coalitions are formed, sensor constraints among robots are also established. For example, in a leader-follower task, follower robots must keep leader robots within their sights, while in a box-pushing task, a supervisor robot needs to track the moving direction of the box and monitor the pushing path to the goal for obstacle avoidance. The question of how to keep these constraints satisfied during the entire execution, from initial configurations to completeness of the task, remains an open issue. In addition, environmental factors, both static and dynamic, can influence the maintenance of the constraints. Moreover, problems arise when the constraints are unsatisfiable given the current circumstances. For example, the sight of the leader might be blocked or there might be obstacles blocking the view of the box. This paper proposes a general method to address these issues for various applications with sensors having certain characteristics. Our approach combines the use of sensor models, environment sampling, measures of information quality, a motion model with sampling, and a constraint model. We believe that this approach offers the first generic formulation of robotic sensor constraints that can be applied to a wide variety of applications. To illustrate this method, we apply the approach to solve robot tracking and navigation tasks both in simulation and with physical robots. Experimental results illustrate the flexibility and robustness of the approach.