论文标题
以人为中心的自主观察的主动感知
Human-Centric Active Perception for Autonomous Observation
论文作者
论文摘要
随着机器人自主权的提高，自主观察系统的作用正在越来越多地考虑机器人 - 自由飞行的摄像机，能够在某些感兴趣的预定义领域内积极跟踪人类活动。在这项工作中，我们通过多目标优化制定了自主观察问题，并提出了一种新型的半MDP公式，对自主人类观察问题进行了新的观察问题，该公式在考虑以人为和机器人为中心的成本的同时，可以最大化观察奖励。我们证明，可以通过基于标量化的多目标MDP方法和受约束的MDP方法来解决该问题，并讨论每种方法的相对好处。我们使用在模拟的国际空间站环境中运行的NASA Astrobee机器人来验证我们在活动跟踪方面的工作。
As robot autonomy improves, robots are increasingly being considered in the role of autonomous observation systems -- free-flying cameras capable of actively tracking human activity within some predefined area of interest. In this work, we formulate the autonomous observation problem through multi-objective optimization, presenting a novel Semi-MDP formulation of the autonomous human observation problem that maximizes observation rewards while accounting for both human- and robot-centric costs. We demonstrate that the problem can be solved with both scalarization-based Multi-Objective MDP methods and Constrained MDP methods, and discuss the relative benefits of each approach. We validate our work on activity tracking using a NASA Astrobee robot operating within a simulated International Space Station environment.
