480 research outputs found

    Mobile Formation Coordination and Tracking Control for Multiple Non-holonomic Vehicles

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    This paper addresses forward motion control for trajectory tracking and mobile formation coordination for a group of non-holonomic vehicles on SE(2). Firstly, by constructing an intermediate attitude variable which involves vehicles' position information and desired attitude, the translational and rotational control inputs are designed in two stages to solve the trajectory tracking problem. Secondly, the coordination relationships of relative positions and headings are explored thoroughly for a group of non-holonomic vehicles to maintain a mobile formation with rigid body motion constraints. We prove that, except for the cases of parallel formation and translational straight line formation, a mobile formation with strict rigid-body motion can be achieved if and only if the ratios of linear speed to angular speed for each individual vehicle are constants. Motion properties for mobile formation with weak rigid-body motion are also demonstrated. Thereafter, based on the proposed trajectory tracking approach, a distributed mobile formation control law is designed under a directed tree graph. The performance of the proposed controllers is validated by both numerical simulations and experiments

    Comprehensive review on controller for leader-follower robotic system

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    985-1007This paper presents a comprehensive review of the leader-follower robotics system. The aim of this paper is to find and elaborate on the current trends in the swarm robotic system, leader-follower, and multi-agent system. Another part of this review will focus on finding the trend of controller utilized by previous researchers in the leader-follower system. The controller that is commonly applied by the researchers is mostly adaptive and non-linear controllers. The paper also explores the subject of study or system used during the research which normally employs multi-robot, multi-agent, space flying, reconfigurable system, multi-legs system or unmanned system. Another aspect of this paper concentrates on the topology employed by the researchers when they conducted simulation or experimental studies

    Distributed, adaptive deployment for nonholonomic mobile sensor networks : theory and experiments

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    In this work we show the Lyapunov stability and convergence of an adaptive and decentralized coverage control for a team of mobile sensors. This new approach assumes nonholonomic sensors rather than the usual holonomic sensors found in the literature. The kinematics of the unicycle model and a nonlinear control law in polar coordinates are used in order to prove the stability of the controller applied over a team of mobile sensors. This controller is adaptive, which means that the mobile sensors are able to estimate and map a density function in the sampling space without a previous knowledge of the environment. The controller is decentralized, which means that each mobile sensor has its own estimate and computes its own control input based on local information. In order to guarantee the estimate convergence, the mobile sensors implement a consensus protocol in continuous time assuming a fixed network topology and zero communication delays. The convergence and feasibility of the coverage control algorithm are verified through simulations in Matlab and Stage. The Matlab simulations consider only the kinematics of the mobile sensors and the Stage simulations consider the dynamics and the kinematics of the sensors. The Matlab simulations show successful results since the sensor network carries out the coverage task and distributes itself over the estimated density function. The adaptive law which is defined by a differential equation must be approximated by a difference equation to be implementable in Stage. The Stage simulations show positive results, however, the system is not able to achieve an accurate estimation of the density function. In spite of that, the sensors carry out the coverage task distributing themselves over the sampling space. Furthermore, some experiments are carried out using a team of four Pioneer 3-AT robots sensing a piecewise constant light distribution function. The experimental results are satisfactory since the robots carry out the coverage task. However, the accuracy of the estimation is affected by the approximation of the adaptation law by difference equations, the number of robots and sensor sensitivity. Based on the results of this research, the decentralized adaptive coverage control for nonholonomic vehicles has been analyzed from a theoretical approach and validated through simulation and experimentation with positive results. As a future work we will investigate: (i) new techniques to improve the implementation of the adaptive law in real time,(ii) the consideration of the dynamics of the mobile sensors, and (iii) the stability and convergence of the adaptive law for continuous-time variant density function

    Distributed formation control with time and connectivity constraints

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    [Abstract] In this paper, we propose a distributed control law for non-holonomic vehicles that guarantees to achieve the desired formation and location before a given deadline, while maintaining the connectivity of the group. The group is commanded by a a selected subset of the agents, which know the location of the desired objective, while the rest of the vehicles only have information about their relative desired positions respect their set of neighbors. The analytical results are illustrated with a simulation example.[Resumen] En este documento, proponemos una ley de control distribuido para vehículos no holonómicos que garantiza alcanzar la formación y ubicación deseadas antes de un plazo determinado, mientras se mantiene la conectividad del grupo. El grupo está comandado por un subconjunto seleccionado de agentes, que conocen la ubicación del objetivo deseado, mientras que el resto de los vehículos solo tienen información sobre sus posiciones relativas deseadas con respecto a su conjunto de vecinos. Los resultados analíticos se ilustran con un ejemplo de simulación
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