Comparative study and experimental implementation of different path tracking controllers in mobile robots

SUMMARYThis paper considers finite‐time formation control problem for a group of nonholonomic mobile robots. The desired formation trajectory is represented by a virtual dynamic leader whose states are available to only a subset of the followers and the followers have only local interaction. First of all, a continuous distributed finite‐time observer is proposed for each follower to estimate the leader's states in a finite time. Then, a continuous distributed cooperative finite‐time tracking control law is designed for each mobile robot. Rigorous proof shows that the group of mobile robots converge to the desired geometric formation pattern in finite time. At the same time, all the robots can track the desired formation trajectory in finite time. Simulation example illustrates the effectiveness of our method. Copyright © 2012 John Wiley & Sons, Ltd.

This paper investigates the distributed formation control problem for multiple nonholonomic wheeled mobile robots. A variable transformation is first proposed to convert the formation control problem into a state consensus problem. Then, when the dynamics of the mobile robots are considered, the distributed kinematic controllers and neural network torque controllers are derived for each robot such that a group of nonholonomic mobile robots asymptotically converge to a desired geometric pattern along the specified reference trajectory. The specified reference trajectory is assumed to be the trajectory of a virtual leader whose information is available to only a subset of the followers. Also the followers are assumed to have only local interaction. Moreover, the neural network torque controllers proposed in this work can tackle the dynamics of robots with unmodeled bounded disturbances and unstructured unmodeled dynamics. Some sufficient conditions are derived for accomplish the asymptotically stability of the systems based on algebraic graph theory, matrix theory, and Lyapunov control approach. Finally, simulation examples illustrate the effectiveness of the proposed controllers.

This paper investigated the formation control of multi-mobile robots under the environment without obstacles, the feedback linearization is used for the robot, a nonlinear sliding mode controller is proposed in accordance with multi-robot system to coordinate a group of nonholonomic mobile robots so that a desired formation can be achieved. A prescribed trajectory is followed by using sliding mode control approaches, We prove theoretically that under certain reasonable assumptions the formation is asymptotically stable, that is, the proposed sliding mode controller can asymptotically stabilize the formation. The simulation results verify the effectiveness of the control laws.

In the last decade, robotic systems have penetrated human life more than human can imagine. In particular, the multi-mobile robotic systems have faced a fast growing due to the fact that by deploying a large collection of mobile robots the overall system has a high redundancy and offers the capability of handling more complex tasks. A group of mobile robots increases robustness against failures and provide flexibility to system changes. In order to achieve a fully autonomous operation, the control algorithm to coordinate the robots becomes more important and decisive. The controller has to meet different requirements that sometimes are conflicting. The main goal of this thesis is to evaluate performance of coordination control algorithms for a group of mobile robots. In the first part of this thesis, a modular framework for simulation and experiments of coordination control of mobile robots is presented. All connections between the modules follow the subscriber/publisher paradigm on the exchanged data, i.e. a component publishes data and other components can subscribe on that data. The data is identified by a named magazine, and actual data packets are called issues of the magazine. By means of simulation and experiments, it is demonstrated how the modularity in the framework allows straightforward modification of system configurations, design parameters, and control algorithms. In the second part, hierarchical coordination control of mobile robots is presented. The hierarchy consists of three layers: a high-level control for motion planning of the robots, a low-level control for motion execution, and a flexible layer to accommodate shifting of responsibilities. One advantage of using a hierarchical approach is the isolation of control design in each layer. Changes in the control strategy of a layer do not necessarily require adaptation of other layers. The proposed control algorithms are used to coordinate a group of unicycle mobile robots that realize the transportation system of an automated warehouse. Using the framework, series of simulations with different design parameters are conducted, as well as real-time experiments. Subsequently, performance analysis of the results is carried out. It is shown that the proposed algorithms are flexible to system changes and scalable to variation in the warehouse demands. The algorithms are robust against failures in the transportation systems. It is found that an algorithm, denoted high-level control, with higher throughputs requires more information sharing between the robots. This algorithm is less robust against failures compared to the algorithm, denoted low-level control, that yields lower throughput. In addition, a cost analysis of the proposed control algorithms is given. It is studied that the cost of realizing the transport using a group of mobile robots, coordinated by the proposed control algorithm, has similar performance-to-cost ratio compared to conveyor systems. This conclusion is very promising having in minds that the proposed control algorithm is not necessarily the optimal one. In the third part, the problem of simultaneous tracking of individual references and formation keeping for a group of mobile robots is investigated. The control algorithm is developed using dynamic feedback linearization. The stability proof is analyzed using the theorem on interconnected systems. Using a root-mean-square-like indicator, the trade off between individual tracking and formation keeping, as well as the influences of communication topologies are analyzed. From the analysis of real-time experiment results, it is found that the best formation keeping is obtained when all robots communicate. As a trade off, this requires a larger communication bandwidth and yields large individual tracking errors. Furthermore, the analysis suggests that to achieve optimal individual tracking and formation keeping simultaneously, there is less need to share information between the robots. In the fourth part, as a complement to the hierarchical control approach, a coordination control algorithm based on Model Predictive Control (MPC) is presented. Focusing on the practical aspects, a sequentially decentralized MPC, i.e. a single MPC computes the control signals of all robots where priority rules are used to determine which robots handled earlier in optimization procedure, is implemented. Using the similar automated warehouse environment, the sequentially decentralized MPC is validated in simulations and real-time experiments. For comparison purposes, a centralized MPC, i.e. a single MPC computes the control signals of all robots, is also implemented. Using completion time as indicators, the influences of the MPC parameters are investigated. It is found that the centralized MPC is better than the sequentially decentralizwed MPC, but with the cost of high computation load and limited number of robots in real-time application. Relevance and performance comparison between the MPC and the hierarchical control approach are presented. It is found that regardless of the control algorithm choices, in terms of completion time, a better performance is obtained when the control algorithm uses information from all robots in computing the control signals.

Formation Control and Obstacle Avoidance for Multiple Mobile Robots

A Remote Laboratory for Mobile Robot Applications

In this article, the problem of performing different tasks with a group of mobile robots is addressed. To cope with issues like regulation to a point or trajectory tracking, a consensus scheme is considered. Three topologies were tested in simulation. The first goal was to make consensus in the group of robots, after the consensus point was relocated to achieve a regulation control. The last objective was to follow a desired trajectory moving the consensus point along the predefined path. The proposal was validated through experimental test with a group of three differential mobile robots.

This brief investigates the flexible leader–follower formation tracking problem for a group of nonholonomic mobile robots, while most of the formation control related work in the literature focuses on the rigid formation. The flexible formation discussed in this brief is defined in curvilinear coordinates in terms of longitudinal separations between robots along the reference trajectory and lateral deviations with respect to this trajectory. Unlike the previous studies on flexible formation control, this brief is under a more challenging assumption that the global position and orientation measurements are not available. To obtain the relative pose relationships amongst robots, a stereo camera is mounted on each follower. In consideration of the fact that visual observations are noise-corrupted and intermittently available, a particle filter-based relative pose estimation approach is employed to estimate the position and orientation of the leader in the local reference frame of the follower using the polluted and discontinuous information. Also, to form a flexible formation, the leader historical trajectory is reconstructed with respect to the current local frame attached on the follower, based on which a reference point is generated. In addition, this brief considers the situation where robots operate in unknown obstacle environments. To ensure robot safety in such environments, a multiobjective control law is proposed to balance reference tracking and collision avoidance in different situations. Simulation and real-robot experiment have been performed to demonstrate the efficacy of the proposed method.

In this paper, a novel cooperative coevolution (CC)-based model predictive control (MPC) is proposed to deal with formation control problem. While conventional evolutionary algorithm (EA)-based MPC approaches cannot guarantee the stability, the proposed CC-based MPC guarantees the asymptotic stability regardless of the optimality of the solution that the CC-based algorithm generates with a small number of individuals. To guarantee the stability, a terminal state constraint is found, and then a repair algorithm is applied to all candidate solutions to meet the constraint. The cooperatively coevolving particle swarm optimization (CCPSO), most recently developed algorithm among CC-based EAs, is adopted and modified to fit into the formation control problem. Experiments are performed on a group of nonholonomic mobile robots to demonstrate the effectiveness of the CC-based MPC.

This paper proposes a receding horizon control (RHC) scheme incorporating a cooperative particle swarm optimization (CPSO) to deal with formation control problem. The CPSO is modified to fit on solving the formation control problem. A numerical simulation is performed on a group of nonholonomic mobile robots to demonstrate the effectiveness of the proposed RHC scheme incorporating CPSO.

Presents a target assignment strategy for multiple robots that are scattered in the environment and they are expected to build an ordered formation. The described approach is general and can be used together with a variety of trajectory planning methods. The presented approach produces some constraints for trajectories generation, however, in most cases the constraints can be easily satisfied. Simulation results for Hilare-type holonomic robots are presented. The possibility of use for a group of nonholonomic mobile robots is also discussed.

Formation control of nonholonomic mobile robots is considered in this paper and decentralized linear controllers based on cascade design are proposed for a group of nonholonomic mobile robots. By using the theory of cascaded systems and cooperative control of linear agents, multiple nonholonomic robots' formation control problem is converted into multi-linear time-varying systems' stabilization problem. Linear decentralized cooperative controllers are brought out for the formation control problem when the reference targets satisfy the condition of persistent excitation which has relaxed the requirements on reference trajectory than those given in previous papers.

Coordination between mobile robots is a mature research topic. Yet, different approaches and new idea in improving stability condition emerge. Other aspect is on the practicability of solution for over actuated mobile robot type. In this work we propose a practical control algorithm that coordinates tracking of the reference trajectories for a group of four-wheels omnidirectional mobile robots. Exploiting the kinematic property of the robot, coordination can be achieved by a combination of inverse based individual trajectory control and information sharing between robots. A globally asymptotically stable error dynamics is proven using Lyapunov approach. A simulation validation shows that the proposed controller can achieved tracking accuracy up to 0.02 [m] and responsive to disturbances occurred in the group.

The method to organize a safe and optimal joint movement of a group of intelligent mobile robots that solve common tasks in a potentially dangerous territory is purpose. Such territories include: territory covered by fire, chemically contaminated territory, and another territory with the manifestation of an emergency in which robots will be of high utility. To solve this problem, a software platform for organizing group interactions of mobile objects has been developed and the principles of building its modular architecture are given. Using the platform, the developed technique for solving the problem was implemented and a series of experiments was conducted to evaluate its effectiveness. The technique is based on algorithms for efficiently representing the movement space in the form of a directed graph, finding the shortest path based on the a-star algorithm with an optimal heuristic function, and the logic of joint interaction of a group of mobile robots with the possibility of task distribution. Evaluation of the effectiveness of the developed method was carried out on the basis of a generalized method for calculating the stabilized value of the indication of the effectiveness criterion. A demonstration experiment is the task of simultaneously and safely collecting a group of robots in a target area in a potentially dangerous territory. The main parameter to be evaluated is simultaneity of the arrival of a group of robots depending on the number of robots in a group.

This article describes the design of a linear observer–linear controller-based robust output feedback scheme for output reference trajectory tracking tasks in the case of nonlinear, multivariable, nonholonomic underactuated mobile manipulators. The proposed linear feedback scheme is based on the use of a classical linear feedback controller and suitably extended, high-gain, linear Generalized Proportional Integral (GPI) observers, thus aiding the linear feedback controllers to provide an accurate simultaneous estimation of each flat output associated phase variables and of the exogenous and perturbation inputs. This information is used in the proposed feedback controller in (a) approximate, yet close, cancelations, as lumped unstructured time-varying terms, of the influence of the highly coupled nonlinearities, and (b) the devising of proper linear output feedback control laws based on the approximate estimates of the string of phase variables associated with the flat outputs simultaneously provided by the disturbance observers. Simulations reveal the effectiveness of the proposed approach.