Distributed Model Predictive Control for Cooperative Landing

Bereza, Robert; Persson, Linnéa; Wahlberg, Bo

doi:10.1016/j.ifacol.2020.12.2290

Cited by 7 publications

(2 citation statements)

References 13 publications

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“…MPC is particularly suitable for solving constrained control problems, since the constraints can be taken into account directly in the optimization problem. The work in [ 40 – 42 ] develops an MPC for the autonomous landing problem between a quadcoper UAV and a USV. The objective function is here expressed as the sum of weighted squared distance to the rendezvous state and input Spatial safety-based constraints are added for avoiding masts, antennas, and other protruding boat parts during the landing, see Fig.…”

Section: Collaborative Autonomous Drones (Uav) Experimentationmentioning

confidence: 99%

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

Andersson

Doherty

Lager

et al. 2021

Auton. Intell. Syst.

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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.

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Section: Collaborative Autonomous Drones (Uav) Experimentationmentioning

confidence: 99%

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

Andersson

Doherty

Lager

et al. 2021

Auton. Intell. Syst.

Self Cite

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“…A question which has not been directly addressed in previous research is that of efficient communication strategies between the agents. Instead, previous distributed solutions have communicated all state and trajectory information between the agents at each sample time, Bereza et al (2020). In this paper, we consider rendezvous control through distributed MPC, where the agents use an aperiodic exchange of information to negotiate and update their rendezvous point.…”

Section: Introductionmentioning

confidence: 99%

Aperiodic Communication for MPC in Autonomous Cooperative Landing

et al. 2021

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Framework for formation control of jet-propelled unmanned surface vehicles

Yan

Zhang

et al. 2023

AIP Advances

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This study focuses on the research of spray-pump type unmanned surface vehicles (USVs). Based on the analysis of the dynamics and motion characteristics of USVs, a method combining Dubins curves and the particle swarm optimization algorithm is proposed to find the optimal or suboptimal solution for the formation path. The research goal is to switch multiple USVs from an unordered state to a formation state, taking the speed of USVs and the formation endpoint as dynamic variables and integrating Dubins curve theory into the particle swarm optimization algorithm. A theoretical framework for the formation of spray-pump type USVs is proposed. Finally, the formation of three USVs is realized in a simulation platform.

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Distributed Model Predictive Control for Cooperative Landing

Cited by 7 publications

References 13 publications

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

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

Aperiodic Communication for MPC in Autonomous Cooperative Landing

Framework for formation control of jet-propelled unmanned surface vehicles

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