Collaborative Research: An Adaptive Dynamic Programming Approach to the Coordination of Heterogeneous Robotic Sensors Networks

本研究的目的是开发用于搜索和救援行动、人道主义排雷和环境监测的自主传感器网络的自适应协调和控制方法。该方法是为这种新型混合系统开发自适应动态规划算法，根据传感器在线获得的先验知识和信息，通过智能地协调和实现未来传感器的动作，随着时间的推移优化其性能。本研究为机器人传感器网络开发了一种新的混合自适应动态规划理论和算法。在线学习和自适应控制对机器人传感器网络至关重要，因为它们必须部署在高度非结构化和不确定的环境中，很少或根本没有关于障碍物或目标的先验信息。本研究将融合计算机科学、机器人技术和工程学的最新跨学科发展，开发一种新的系统理论方法，将混合控制与计算几何算法相结合，并利用信息和概率论优化目标函数。通过优化新兴传感器技术的性能并提高其自主性水平，该研究将使它们能够移除或协助人类执行危险但至关重要的任务，例如人道主义排雷，以及飓风、火灾或雪崩后的救援工作。研究成果将通过与工业界和国际机构的现有合作在实际系统上传播和展示。杜克大学和新墨西哥州大学将从代表性不足的少数族裔中招募学生，参加刺激的教育活动，包括机器人游戏、电脑游戏比赛和环境研究。

The objective of this research is to develop adaptive coordination and control methods for autonomous sensor networks employed for search and rescue operations, humanitarian demining, and ambient monitoring. The approach is to develop adaptive dynamic programming algorithms for this new class of hybrid systems, to optimize their performance over time by coordinating and implementing future sensor actions intelligently, based on prior knowledge and information obtained by the sensors online.Intellectual meritThis research develops novel hybrid adaptive dynamic programming theory and algorithms for robotic sensor networks. Online learning and adaptive control are crucial to robotic sensor networks because they are, by necessity, deployed in highly unstructured and uncertain environments, with little or no prior information about the obstacles or the targets. This research will merge recent interdisciplinary developments in computer science, robotics, and engineering to develop a novel system-theoretic approach that integrates hybrid control with computational geometry algorithms, and optimizes objective functions derived using information and probability theories.Broader impactBy optimizing the performance of emerging sensor technologies and increasing their level of autonomy, this research will enable them to remove or assist humans in carrying out dangerous yet vital missions, such as humanitarian demining, and rescue efforts following hurricanes, fires, or avalanches. Research results will be disseminated and demonstrated on real systems through existing collaborations with the industry and international institutions. Students will be recruited from underrepresented minorities at both institutions, Duke and UNM, to participate in stimulating education activities, including robotic games, computer game competitions, and environmental research.