Intelligent Real-time Navigation and Cooperation of Multiple Autonomous Surface and Underwater Robotic Systems

无人水面和水下航行器有许多重要的应用，如安全监视，环境监测和河流，湖泊和海洋的勘探，特别是在非结构化和危险的环境中。一组无人驾驶车辆可以一起工作，快速有效地完成指定的任务。多机器人系统比单机器人系统具有运行速度快、效率高、可靠性高等优点。关键的挑战是在不断变化的复杂环境中，多个水面和水下机器人的实时无碰撞导航和有效合作，受到不确定性，干扰和噪音，以成功完成指定的任务。该研究计划为期5年，旨在利用新颖的生物智能方法，为多个自主水面和水下机器人系统的实时无碰撞导航和合作做出重大的原创和创新贡献。为解决这一关键问题，本研究计划将重点研究：（1）自主式水面和水下机器人的实时无碰撞智能导航，包括多传感器实时融合与时间同步，以及机器人的实时路径规划、跟踪和控制;（2）多个水面和水下机器人的智能通信和协作，以完成通常是多目标的任务，包括受不确定性和干扰影响的动态任务分配，以及有效的通信和协作，以实现整体最优性能;（3）对真实的机器人进行广泛的理论分析和实验研究，以评估和验证新开发的方法与现有解决方案的比较。生物系统，如鱼类和昆虫，可以有效地感知动态环境，并使用非常简单的机制采取有效的行动;生物物种表现出集体行为，可以合作完成许多复杂的任务，这些任务超出了有限的隐式通信下的个人能力。拟议的研究的新奇和预期的意义将是提供新的知识，各自的研究领域和新的生物启发的智能技术的实时多传感器融合，路径规划，控制，通信和合作的多个自主的表面和水下机器人的发展。此外，它还将为其他研究领域（如多辆无人驾驶汽车）的生物启发方法提供一些见解。此外，该研究计划将为机器人和人工智能领域的高素质人才的培训提供许多机会，并导致巨大的知识转移和商业应用。

Unmanned surface and underwater vehicles have many important applications such as security surveillance, environmental monitoring and exploration in rivers, lakes, and seas, particularly in unstructured and hazardous environments. A team of unmanned vehicles could work together to accomplish an assigned task rapidly and efficiently. A multi-robotic system has obvious advantages such as faster operation, higher efficiency, and better reliability than a single robot. The key challenges are the real-time collision-free navigation and efficient cooperation of multiple surface and underwater robots in changing complex environments subject to uncertainties, disturbances and noises, for successful completion of designated tasks. The proposed 5-year research program aims to make significant original and innovative contributions in real-time collision-free navigation and cooperation of multiple autonomous surface and underwater robotic systems, using novel biologically inspired intelligent approaches. To address the key challenge, the proposed research program will focus on: (1) Real-time collision-free intelligent navigation of autonomous surface and underwater robots, including real-time multi-sensor fusion with time synchronization of acquired information from onboard sensors and other available sensed information, and real-time path planning, tracking and control of the robots; (2) Intelligent communication and cooperation of the multiple surface and underwater robots to accomplish a task that is usually multi-objective, including dynamic task assignment subject to uncertainties and disturbances, and efficient communication and cooperation to achieve an overall optimal performance; (3) Extensive theoretical analysis and experimental studies on real robots to evaluate and validate the newly developed approaches in comparison to existing solutions. The proposed research has been motivated by the fact that biological systems, such as fishes and insects, can efficiently sense the dynamic environments and take effective actions using very simple mechanisms; and biological species exhibit collective behaviours and can cooperatively accomplish many complex tasks that are beyond the capabilities of an individual under limited implicit communications. The novelty and anticipated significance of the proposed research will be the provision of new knowledge to the respective research fields and the development of new bioinspired intelligent techniques for real-time multi-sensor fusion, path planning, control, communication, and cooperation of multiple autonomous surface and underwater robots. In addition, it will offer some insights into biologically inspired methodologies for other research areas such as multiple unmanned cars. Furthermore, this research program will provide many opportunities for the training of highly qualified personnel in the areas of robotics and artificial intelligence, and lead to great knowledge transfer and commercial applications.