Autonomous Robotic Systems

机器人的使用已经从制造业的主要基础转向家庭，医疗保健，安全和探索应用。因此，该领域未来的挑战将包括开发能够在不同层面上与环境交互的自主机器人系统。因此，这项资助申请是为了支持我们对当代重点的自主多智能体系统的开发，规划和控制的研究。我们期望在两个协同子主题上取得显着进展：（i）开发用于时变几何对象的定位，跟踪和定位的多智能体传感方法，以及（ii）开发用于跟踪，拦截和操纵这些动态对象的多智能体团队部署和运动协调方法（即，目标）。*子主题1： 我们的目标是建立在我们正在进行的工作，多摄像机主动视觉系统，为发展通用的在线传感方法的定位，跟踪和识别的变形物体在混乱，动态的环境。作为这个子主题的第一个目标，我们的重点将是开发新的技术，通过融合的视觉船体和范围数据，结合状态预测的形状恢复未知的无标记可变形物体。无标记形状恢复的主要动机是消除对先验已知对象模型的数据库的潜在依赖性。作为第二个目标，我们将为多摄像机重新配置开发强大的优化流程-这是一个将在子主题2的框架内解决的目标。** 副主题2： 我们的目标是在我们正在进行的工作的基础上，发展多智能体团队部署和运动协调策略，用于跟踪，拦截和操纵动态目标。作为这个子主题的第一个目标，我们的重点将是开发新的确定性集中的方法，用于可跟踪目标的多智能体部署和协调问题，其位置可以被查看，其运动预测在线-与子主题1相关的目标。作为第二个目标，我们的重点将是开发新的确定性方法的多代理部署和协调问题拦截不可跟踪的目标-例如，机器人在荒野中的搜救对于平衡的任务分配，我们将首先研究分解方法，其中一个全球规格分解成子规格的个别代理，并开发相应的本地控制器。作为第三个目标，我们的重点将是实现具有可重构拓扑结构的高灵活性并行机构，这些机构允许在相对有限的时间内精确操纵目标-例如，MRI引导的机器人手术。**

The utilization of robots has been shifting from their principal base of manufacturing toward household, healthcare, security, and exploration applications. Future challenges in the field will, thus, include the development of autonomous robotic systems that can interact with their environment on different levels. Hence, this grant application is in support of our research on the development, planning, and control of autonomous multi-agent systems with a contemporary focus. We expect to make notable advancements on two synergetic sub-themes: (i) development of multi-agent sensing methodologies for the localization, tracking, and recog-ni-tion of time-varying-geometry objects, and (ii) development of multi-agent team-deployment and motion-coordination methodologies for the tracking, interception, and manipulation of these dynamic objects (i.e., targets).******Sub-Theme 1:   Our goal is to build on our ongoing work, on multi-camera active-vision systems, for the development of generic on-line sens-ing methodologies for the localization, tracking and recognition of deformable objects in cluttered, dynamic environments. As the first objective for this Sub-Theme, our focus will be on developing novel techniques for the shape recovery of unknown markerless deformable objects through fusion of visual hulls and range data, integrated with state prediction. The primary motivation in markerless shape recovery is removing potential dependency on a database of a priori known object models. As the second objective, we will develop robust optimization processes for multi-camera reconfiguration - an objective to be addressed within the framework of Sub-Theme 2.**** *** ***Sub-Theme 2:   Our goal is to build on our ongoing work, on the on the development of multi-agent team-deployment and motion-coordination strategies, for the tracking, interception, and manipulation of dynamic targets. As the first objective for this Sub-Theme, our focus will be on developing novel deterministic centralized methods for the multi-agent deployment and coordination problem for trackable targets, whose location can be viewed and their motion predicted on-line - an objective interrelated to Sub-Theme 1. As the second objective, our focus will be on developing novel deterministic methods for the multi-agent deployment and coordination problem for intercepting untrackable targets - e.g., robotic search and rescue in the wilderness. For balanced task allocation, we will first investigate decomposition approaches, where a global specification is decomposed into sub-specifications for individual agents, and corresponding local controllers are developed. As the third objective, our focus will be on the implementation of high-dexterity parallel mechanisms with reconfigurable topologies that allow accurate manipulation of targets in relatively limited workspaces - e.g., MRI-guided robotic surgery.**