Integration of cooperative mobile robots and networked sensor fusion in Safety/Security-Critical tasks

几位著名的美国研究人员提议为美国国防部的多学科大学研究计划(MURI)进行“用于可靠融合的传感器网络结构工程”的研究。美国陆军研究办公室(ARO)最近资助了这个项目。美国的提案确认不列颠哥伦比亚大学的克拉伦斯·德席尔瓦博士是这项计划中的研究的唯一加拿大合作者。MURI的成功申请为我们在这一具有重大共同利益的研究项目中进行合作提供了一个独特的机会之窗。美国研究人员将主要关注非结构化城市环境中的动态传感器网络和信息融合，以实现安全/安保关键操作。考虑到这些动态联网信息获取和融合技术，拟议的SRO项目将集中研究开发多机器人协作技术，在非结构化城市环境中执行对人类安全/安保至关重要的任务。具体地说，SRO项目将侧重于：用于机器人自主合作的基于行为的学习；使用遗传算法(GA)来优化机器人的结构和动作；将GA和强化学习(RL)相结合来生成最佳合作策略；使用人工免疫系统(AIS)来实现系统的健壮性和自组织；将软计算和基于知识的决策用于智能控制；以及整合美国发起的动态传感器网络和融合研究。这些活动将包括分析研究；计算机模拟；在多个移动机器人的原型实验室系统中开发和实施技术；将物理系统与用于通信和信息融合的动态网络拓扑集成在一起(由美国研究人员开发)；实际演示现实的安全/安保关键活动；以及通过严格的物理测试进行系统评估。

Several prominent US researchers have proposed research on "Engineering of Sensor Network Structure for Dependable Fusion" for the Multidisciplinary University Research Initiative (MURI) of the US Department of Defense (DoD). The US Army Research Office (ARO) has recently funded this project. The US proposal has identified Dr. Clarence de Silva of the University of British Columbia as the only Canadian collaborator of the planned research. The successful MURI application provides a unique window of opportunity for us to collaborate in this research project which is of significant mutual interest. The US researchers will primarily focus on dynamic sensor networking and information fusion in an unstructured urban environment for safety/security critical operations. Given these technologies of dynamically networked information acquisition and fusion, the proposed SRO project will concentrate on research to develop technologies for multi-robot cooperation in carrying out tasks critical for human safety/security in an unstructured urban environment. Specifically the SRO project will focus on: Behaviour-based Learning for Self-deterministic Cooperation of Robots; Use of Genetic Algorithms (GA) for Optimization of the Robotic Structure and Actions; Integration of GA with Reinforcement Learning (RL) for Generating Optimal Cooperation Policies; Use of Artificial Immune Systems (AIS) for System Robustness and Self-organization; Soft Computing and Knowledge Based Decision Making for Intelligent Control; and Integration of US-originated Research on Dynamic Sensor Networking and Fusion. The activities will involve analytical research; computer simulation; technology development and implementation in a prototype laboratory system of multiple mobile robots; integration of the physical system together with a dynamic networking topology for communication and information fusion (developed by US researchers); practical demonstration of a realistic safety/security critical activity; and system evaluation through rigorous physical testing.