Simulation of Trajectory Tracking and Motion Coordination for Heterogeneous Multi-Robots System (original) (raw)
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2008 IEEE International Conference on Robotics and Automation, 2008
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AbstrAct: The cooperative control of small unmanned aerial vehicles such as the multicopters has been extensively investigated worldwide for functionality augmentation and cost reduction with respect to a single larger vehicle. The present paper proposes a software-in-the-loop simulation scheme for performance evaluation and demonstration of formation flight control systems of multicopters. The simulation scheme consists of a computer network where each computer simulates one of the vehicles using the MATLAB/Simulink for implementing the local control system and the X-Plane for simulating the flight dynamics and environment. For cooperation, the local control systems exchange position data by means of the network. In order to illustrate the proposed scheme, a group of 3 octocopters is taken into consideration and a leader-follower strategy is chosen for triangular position formation, with the leader moving in a straight line with constant speed.
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AUT Journal of Modeling and Simulation, 2018
This paper investigates the problem of controlling a team of quadrotors that cooperatively transport a common payload. The main contribution of this study is to propose a cooperative control algorithm based on a decentralized algorithm. This strategy is comprised of two main steps: the first one is calculating the basic control vectors for each quadrotor using Moore-Penrose theory aiming at cooperative transport of an object and the second one is combining these vectors with individual control vectors, which are obtained from a closed-loop non-linear robust controller. In this regard, a nonlinear robust controller is designed based on Second Order Sliding Mode (SOSMC) approach using Extended Kalman-Bucy Filter (EKBF) to estimate the unmeasured states which is capable of facing external disturbances. The distinctive features of this approach include robustness against model uncertainties along with high flexibility in designing the control parameters to have an optimal solution for the nonlinear dynamics of the system. Design of the controller is based on Lyapunov method which can provide the stability of the end-effecter during the tracking of the desired trajectory. Finally, simulation results are given to illustrate the effectiveness of the proposed method for the cooperative quadrotors to transport a common payload in various maneuvers. 147 1-Introduction The cooperative control of multiple vehicle systems despite its wide range of practical applications requires tackling important theoretical and practical challenges which have attracted many researchers in recent years. Formation control problems for multiple vehicle systems can be categorized with applications to unmanned aerial vehicles (UAVs), autonomous underwater vehicles, cooperative transport, mobile robots, cooperative role assignment and cooperative search. In this paper, we seek to drive a control algorithm for cooperation between quadrotors that allow the robots to control their position and angles to grasp and transport a common payload in various maneuvers. The controller is designed to move the object by two or more quadrotors. To make a framework for interplay between a group of quadrotors and payload, many control schemes have been extensively used to solve the problems of creating formation control for UAVs. Some of them have focused on centralized and leader-follower approach to access interaction between cooperative quadrotors and payload [1-7]. Although these methods have acceptable results on small robotic systems but suffer from several disadvantages including high computational complexity of centralized methods in large-scale systems and possibility of disappearing the group formation in leader-follower strategy due to not receiving the position of leader by the followers. In this regard, there is a plethora of research in cooperative multi-robot controller design based on decentralized control methods which can solve a significant number of problems in cooperative control strategies and benefit also from the advantages such as decreased number of sensors and fast performance. In [8], the problem of cooperation by a team of ground robots is addressed under quasi-static assumptions based on decentralize controllers considering a unique solution to robot and object motion. Also, transporting a payload by aerial manipulation using cables based on decentralized control is studied in [9,10]. In other research, cooperative aerial towing-based decentralized mechanism is studied [11]. The authors of [12] employ bilinear matrix inequalities to present optimal solutions for decentralized nonlinear multi-agent systems. Despite the numerous advantages of decentralized methods, there are still some critical issues related to the performance of the control system in presence of disturbances and uncertainties. On the other hand, some of the most popular control schemes for uncertain nonlinear systems are based on discontinuous schemes; in particular, sliding mode controllers (SMC) have shown robustness against uncertainties and matched disturbances [13-18]. Moreover, the finite-time convergence of SMC as well as their simplicity have made them suitable for a large variety of applications such as designing a robust formation control scheme. A high order sliding mode concept can effectively reduce the chattering while keeping the invariant characteristics in the sliding mode. Some successful implementations of high order (second order) SMC schemes in UAVs have been reported in [19,20]. Also, in [21] a robust second order sliding mode controller was proposed for the attitude stabilization of a four-rotor helicopter. This controller was able to overcome the chattering phenomena in classical sliding mode control while preserving the invariance property of sliding mode. In [22], using an equivalent
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Journal of Intelligent and Robotic Systems, 2010
This paper describes the development of a simulator for multiple Unmanned Aerial Vehicles (UAVs) utilizing the commercially available simulator X-Plane and Matlab. Coordinated control of unmanned systems is currently being researched for a wide range of applications, including search and rescue, convoy protection, and building clearing to name a few. Although coordination and control of Unmanned Ground Vehicles (UGVs) has been a heavily researched area, the extension towards controlling multiple UAVs has seen minimal attention. This lack of development is due to numerous issues including the difficulty in realistically modeling and simulating multiple UAVs. This work attempts to overcome these limitations by creating an environment that can simultaneously simulate multiple air vehicles as well as provide state data and control input for the individual vehicles using a heavily developed and commercially available flight simulator (X-Plane). This framework will allow researchers to study multi-UAV control algorithms using realistic unmanned and manned aircraft models in real-world modeled environments. Validation of the system's ability is shown through the demonstration of formation control algorithms implemented on four UAV helicopters with formation and navigation controllers built in Matlab/Simulink.