Iterative weighted tuning for a nonlinear model predictive formation control

A multi-robot system is formed when a group of robots interact with the environment as a single system. This system can also be in formation in order to accomplish tasks rather difficult or impossible to achieve with a single robot. A nonlinear model predictive formation control (NMPFC) was used to converge a group of middle sized mobile soccer robots towards a desired target using the concept of active target tracking. This paper presents a novel approach on formation controller's weight tuning in order to minimize an objective function that reflects the controller's efficiency with respect to a given criteria. Furthermore, the results of simulation and experiment with real robots are presented and discussed.

[1]  D. H. S. Maithripala,et al.  A Geometric Approach to Dynamically Feasible, Real-Time Formation Control , 2011 .

[2]  Fabio Morbidi,et al.  On active target tracking and cooperative localization for multiple aerial vehicles , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Eduardo F. Camacho,et al.  Distributed model predictive control based on a cooperative game , 2011 .

[4]  W. Marsden.  I and J , 2012 .

[5]  Pedro U. Lima,et al.  Perception-driven multi-robot formation control , 2013, 2013 IEEE International Conference on Robotics and Automation.

[6]  Martin A. Riedmiller,et al.  A direct adaptive method for faster backpropagation learning: the RPROP algorithm , 1993, IEEE International Conference on Neural Networks.

[7]  Fumin Zhang,et al.  Robust Control of Formation Dynamics for Autonomous Underwater Vehicles in Horizontal Plane , 2012 .

[8]  Mahdi Jadaliha,et al.  Adaptive Control of Multiagent Systems for Finding Peaks of Uncertain Static Fields , 2012 .

[9]  Stergios I. Roumeliotis,et al.  Multirobot Active Target Tracking With Combinations of Relative Observations , 2011, IEEE Transactions on Robotics.

[10]  António Paulo Moreira,et al.  Multi-robot nonlinear model predictive formation control: Moving target and target absence , 2013, Robotics Auton. Syst..

[11]  J. Hendrickx,et al.  Rigid graph control architectures for autonomous formations , 2008, IEEE Control Systems.

[12]  Pedro Costa,et al.  MODELING OMNIDIRECTIONAL MOBILE ROBOTS: AN APPROACH USING SIMTWO , 2012 .

[13]  Pedro U. Lima,et al.  Multi-Robot Cooperative Object Tracking Based on Particle Filters , 2011, ECMR.

[14]  Luís Almeida,et al.  A Loose Synchronisation Protocol for Managing RF Ranging in Mobile Ad-Hoc Networks , 2011, RoboCup.

[15]  Andreas Zell,et al.  A model-predictive approach to formation control of omnidirectional mobile robots , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.