Autonomous Robotic Systems

机器人的应用已经从主要的制造业转向家庭、医疗保健、安全和勘探应用。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互动的自主机器人系统。因此，这项拨款申请是为了支持我们对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著进展：(i)开发用于定位、跟踪和识别时变几何物体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物体（即目标）的多智能体团队部署和运动协调方法。******子主题1：我们的目标是建立在我们正在进行的工作上，在多摄像头主动视觉系统上，为在混乱的动态环境中定位、跟踪和识别可变形物体开发通用的在线传感方法。作为这个子主题的第一个目标，我们的重点将是通过融合视觉船体和距离数据，结合状态预测，开发未知无标记可变形物体形状恢复的新技术。无标记形状恢复的主要动机是消除对先验已知对象模型数据库的潜在依赖。作为第二个目标，我们将开发多摄像机重构的稳健优化过程-一个目标将在子主题2的框架内解决。**** **** ***子主题2：我们的目标是建立在我们正在进行的工作上，在多智能体团队部署和运动协调策略的发展上，用于跟踪，拦截和操纵动态目标。作为本子主题的第一个目标，我们的重点将是为可跟踪目标的多智能体部署和协调问题开发新的确定性集中方法，这些目标的位置可以在线查看并预测其运动-一个与子主题1相关的目标。作为第二个目标，我们的重点将是为拦截无法追踪目标的多智能体部署和协调问题开发新的确定性方法——例如，荒野中的机器人搜索和救援。为了平衡任务分配，我们将首先研究分解方法，其中将全局规范分解为单个代理的子规范，并开发相应的本地控制器。作为第三个目标，我们的重点将放在具有可重构拓扑结构的高灵巧并行机构的实现上，该机构允许在相对有限的工作空间内精确操作目标-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.**