CISE Research Infrastructure: Asymmetric Bandwidth Channels: Applications to Real-Time Computing and Robotics

CDA-9703220 Bajcsy，Ruzena宾夕法尼亚大学 非对称带宽信道：在实时计算和机器人技术中的应用 该奖项旨在收购支持研究的基础设施，以研究具有成本效益和广泛部署的通信模型，非对称带宽信道，在计算机科学中几乎没有抽象。 研究客户端与服务器之间的低带宽交互通道和服务器到客户端的高带宽广播的系统应用。 拟议的工作将开发通信抽象，应用程序可以有效地使用这样的基础设施，这些抽象和计算模型。 然后，将在多个半自主机器人代理的测试平台上评估模型性能。 在这个项目中要解决的挑战性问题包括：（1）选择从服务器到客户端的路径;（2）确定在计算机通信环境中可能的广播信道共享程度;（3）调度来自共享广播终端的传输。 该研究还将针对机器人智能体协调的三个基本问题：（1）基于个体智能体的观察和对未知或部分已知环境的探索来建立完整的世界模型;（2）基于世界模型的任务规划，同时考虑可能的不确定性和延迟;以及（3）基于视觉和其他感觉信息的机器人代理的控制。

CDA-9703220 Bajcsy, Ruzena University of Pennsylvania Asymmetric Bandwidth Channels: Applications to Real-Time Computing and Robotics This award is for the acquisition of infrastructure to support research which is to investigate a cost-effective and broadly deployed communication model, Asymmetric Bandwidth Channels, for which few abstractions in computer science are available. Research into the application of systems characterized by low-bandwidth interactive channels between clients and server, and a high-bandwidth broadcast from server to clients will be conducted. The proposed work will develop communications abstractions that applications can effectively use for such an infrastructure, and computational models for these abstractions. Model performance will then be evaluated on a testbed of multiple semi-autonomous robotic agents. The challenging problems to be addressed in this project include: (1) selecting which path to take from server to client; (2) determining the degree of broadcast channel sharing possible in a computer communications environment; and (3) scheduling transmissions from the shared broadcast terminal. The research will also target three fundamental problems underlying coordination of robotic agents: (1) development of world models based on observations of individual agents and exploration of an unknown or a partially known environment to build a complete model; (2) task planning based on the world model while accounting for possible uncertainties and latencies; and (3) control of robotic agents based on visual and other sensory information.