Abstract
A research arena (WARA-PS) for sensing, data fusion, user interaction, planning and control of collaborative autonomous aerial and surface vehicles in public safety applications is presented. The objective is to demonstrate scientific discoveries and to generate new directions for future research on autonomous systems for societal challenges. The enabler is a computational infrastructure with a core system architecture for industrial and academic collaboration. This includes a control and command system together with a framework for planning and executing tasks for unmanned surface vehicles and aerial vehicles. The motivating application for the demonstration is marine search and rescue operations. A state-of-art delegation framework for the mission planning together with three specific applications is also presented. The first one concerns model predictive control for cooperative rendezvous of autonomous unmanned aerial and surface vehicles. The second project is about learning to make safe real-time decisions under uncertainty for autonomous vehicles, and the third one is on robust terrain-aided navigation through sensor fusion and virtual reality tele-operation to support a GPS-free positioning system in marine environments. The research results have been experimentally evaluated and demonstrated to industry and public sector audiences at a marine test facility. It would be most difficult to do experiments on this large scale without the WARA-PS research arena. Furthermore, these demonstrator activities have resulted in effective research dissemination with high public visibility, business impact and new research collaborations between academia and industry.
Highlights
The Wallenberg AI, Autonomous Systems and Software Program (WASP) [1] is a recent large-scale Swedish national endeavor with a research focus on the strategic areas of Artificial Intelligence, Autonomous Systems and Future Software Systems
For example Kockums AB is interested in experimenting with one of their products, Navel SE, a maritime simulation and real-time tracking system that visualizes maritime vehicles at sea and offers information about them. This system is currently wrapped as a Sensor agent, where positions of all maritime vehicles in the WASP Research Arenas (WARAs)-PS operational environment can be broadcast to other robotic systems and ground stations
As indicated above we evaluated several combinations of approaches to object detection and tracking, and found that YOLOv4 for object detection / recognition and CSRT or KCF for tracking performed best overall, given the circumstances of a data set that was relatively unbalanced regarding the types of sea marks observed during the data collection
Summary
The Wallenberg AI, Autonomous Systems and Software Program (WASP) [1] is a recent large-scale Swedish national endeavor with a research focus on the strategic areas of Artificial Intelligence, Autonomous Systems and Future Software Systems. They have a wide range of research activities related to WARA-PS such as autonomous underwater perception, underwater navigation and docking and multi-agent mission planning and docking One of their demonstrators, the SMaRC long-range and longendurance maritime USV has been used actively in WARA-PS and is integrated in the larger WARA-PS architecture for future experimentation with collaborative robotics in sea rescue scenarios. SSRS has been teaming with other organizations and companies, such as Airpelago, to modernize their rescue services by using state-ofart autonomous technology such as USVs and UAVs. SSRS participates in WARA-PS as one of several units in our larger rescue scenarios at sea. 1.2 WARA-PS infrastructure WARA-PS supports a diverse environment of technology provided by both industrial and academic partners These systems are used for data collection, test development, demonstrations and development of research among PhD students, senior researchers at the many participating universities and industrial participants.
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