WARA-PS:a research arena for public safety demonstrations and autonomous collaborative rescue robotics experimentation

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.

Distributed strategies for pursuit-evasion of high-order integrators

This paper presents decentralized solutions for pursuit-evasion problems involving high-order integrators with intracoalition cooperation and intercoalition confrontation.Distinct error variables and hyper-variables are introduced to ensure the control strategies to be independent of the relative velocities,accelerations and higher order information of neighbors.Consequently,our approach only requires agents to exchange position information or to measure the relative positions of the neighbors.The distributed strategies take into consideration the goals of intracoalition cooperation or intercoalition confrontation of the players.Furthermore,after establishing a sufficient and necessary condition for a class of high-order integrators,we present conditions for capture and formation control with exponential convergence for three scenarios:one-pursuer-one-evader,multiple-pursuer-one-evader,and multiple-pursuer-multiple-evader.It is shown that the conditions depend on the structure of the communication graph,the weights in the control law,and the expected formation configuration.Finally,the effectiveness of the proposed algorithm is demonstrated through simulation results.