A general approach to coordination control of mobile agents with motion constraints

This paper proposes a general approach to design convergent coordination control laws for multi-agent systems subject to motion constraints. The main contribution of this paper is to prove in a constructive way that a gradient-descent coordination control law designed for single integrators can be easily modified to adapt for various motion constraints such as nonholonomic dynamics, linear/angular velocity saturation, and other path constraints while preserving the convergence of the entire multi-agent system. The proposed approach is applicable to a wide range of coordination tasks such as rendezvous and formation control in two and three dimensions. As a special application, the proposed approach solves the problem of distance-based formation control subject to nonholonomic and velocity saturation constraints

Posture regulation for unicycle-like robots with prescribed performance guarantees

This study aims to address the regulation problem for the unicycle model while guaranteeing prescribed performance. Different controllers based either on polar coordinates or time-varying laws are proposed. The main contribution is the combination of the standard control laws that allow to achieve posture regulation for the unicycle, with the prescribed performance control technique that imposes time-varying constraints to the system coordinates. To apply prescribed performance to the unicycle system which is subject to a non-holonomic constraint, the authors design a specific transformation function that is instrumental in the proof of asymptotic convergence with prescribed guaranties

A self-triggered position based visual servoing model predictive control scheme for underwater robotic vehicles

An efficient position based visual sevroing control approach for Autonomous Underwater Vehicles (AUVs) by employing Non-linear Model Predictive Control (N-MPC) is designed and presented in this work. In the proposed scheme, a mechanism is incorporated within the vision-based controller that determines when the Visual Tracking Algorithm (VTA) should be activated and new control inputs should be calculated. More specifically, the control loop does not close periodically, i.e., between two consecutive activations (triggering instants), the control inputs calculated by the N-MPC at the previous triggering time instant are applied to the underwater robot in an open-loop mode. This results in a significantly smaller number of requested measurements from the vision tracking algorithm, as well as less frequent computations of the non-linear predictive control law. This results in a reduction in processing time as well as energy consumption and, therefore, increases the accuracy and autonomy of the Autonomous Underwater Vehicle. The latter is of paramount importance for persistent underwater inspection tasks. Moreover, the Field of View constraints (FoV), control input saturation, the kinematic limitations due to the underactuated degree of freedom in sway direction, and the effect of the model uncertainties as well as external disturbances have been considered during the control design. In addition, the stability and convergence of the closed-loop system has been guaranteed analytically. Finally, the efficiency and performance of the proposed vision-based control framework is demonstrated through a comparative real-time experimental study while using a small underwater vehicle. © 2020 by the authors

Sensor-network-based robust distributed control and estimation

This paper proposes a novel distributed estimation and control method for uncertain plants. It is of application in the case of large-scale systems, where each control unit is assumed to have access only to a subset of the plant outputs, and possibly controls a restricted subset of input channels. A constrained communication topology between nodes is considered so the units can benefit from estimates of neighboring nodes to build their own estimates. The paper proposes a methodology to design a distributed control structure so that the system is asymptotically driven to equilibrium with L2-gain disturbance rejection capabilities. A difficulty that arises is that the separation principle does not hold, as every single unit ignores the control action that other units might be applying. To overcome this, a two-stage design is proposed: firstly, the distributed controllers are obtained to robustly stabilize the plant despite the observation errors in the controlled output. At the second stage, the distributed observers are designed aiming to minimize the effects of the communication noise in the observation error. Both stages are formulated in terms of linear matrix inequalities. The performance is shown on a level-control real plant.Ministerio de Ciencia y Tecnología DPI2010-1915

Real-time Optimized Rendezvous on Nonholonomic Resource-Constrained Robots

Abstract In this work, we consider a group of differential-wheeled robots endowed with noisy relative positioning capabilities. We develop a decentralized approach based on a receding horizon controller to generate, in real-time, trajectories that guarantee the convergence of our robots to a common location (i.e. rendezvous). Our receding horizon controller is tailored around two numerical optimization methods: the hybrid-state A * and trust-region algorithms. To validate both methods and test their robustness to computational delays, we perform exhaustive experiments on a team of four real mobile robots equipped with relative positioning hardware