Formation Control Of Multiple Robots Research Articles

Polygon formation of multiple nonholonomic mobile robots with double-level-control collision avoidance scheme

This paper considers a polygon formation control of multiple robots with nonholonomic constraints enclosing a goal target and double-level-control collision avoidance scheme. Double-level-control scheme consisted of upper-level and lower-level controls are proposed for trajectory generation and tracking control of multi-robot systems. Both upper-level and lower-level controls operate collision avoidance mechanisms based on potential functions. The proposed control scheme guarantees that the group of robots are kept in the polygon formation and driven to a goal, while avoiding collisions during the travel. Moreover, the designed interaction between the upper- and lower-level controls guarantees that the mobile robots are not trapped in local minima or deadlock case. Experiments of the formation of three-robots are conducted to show the performance of the mobile robots in accomplishing a polygon formation while achieving the goal without any collision and no local minima.

Relative Position Estimation for Formation Control with the Fusion of Predicted Future Information and Measurement Data

This paper addresses a relative position estimation problem for formation control of multiple robots. In the authors' previous paper, a relative position estimation method has been proposed, w...

Two Algorithms For Static Polygon Shape Formation Control

This paper provides a two algorithms for designing robust formation control of multiple robots called Leader- Neighbor algorithm and Neighbor-Leader algorithm in unknown environment. The main function of the robot group is to use the RP lidar sensor attached to each robot to form a static geometric polygon. The algorithms consist of two phases implemented to investigate the formation of polygon shape. In the leading- neighbor algorithm, the first stage is the leader alignment and the adjacent alignment is the second stage. The first step uses the information gathered by the main RP Lidar sensor to determine and compute the direction of each adjacent robot. The adjacent RP Lidar sensors are used to align the adjacent robots of the leader by transferring these adjacent robots to the leader. By performing this stage, the neighboring robots will be far from the leader. The second stage uses the information gathered by adjacent RP sensors to reposition the robots so that the distance between them is equal. On the other hand, in the neighbor-leader algorithm, the adjacent robots are rearranged in a regular distribution by moving in a circular path around the leader, with equal angles between each of the two neighbor robots. A new distribution will be generated in this paper by using one leader and four adjacent robots to approve the suggested leader neighbor algorithm and neighbor-leader algorithm.

Second-Order Sliding Mode Formation Control of Multiple Robots by Extreme Learning Machine

This paper addresses a second-order sliding mode control method for the formation problem of multirobot systems. The formation patterns are usually symmetrical. This sliding mode control is based on the super-twisting law. In many real-world applications, the robots suffer from a great diversity of uncertainties and disturbances that greatly challenge super-twisting sliding mode formation maneuvers. In particular, such a challenge has adverse effects on the formation performance when the uncertainties and disturbances have an unknown bound. This paper focuses on this issue and utilizes the technique of an extreme learning machine to meet this challenge. Within the leader–follower framework, this paper investigates the integration of the super-twisting sliding mode control method and the extreme learning machine. The output weights of this extreme learning machine are adaptively adjusted so that this integrated formation design has guaranteed closed-loop stability in the sense of Lyaponov. In the end, some simulations are implemented via a multirobot platform, illustrating the superiority and effectiveness of the integrated formation design in spite of uncertainties and disturbances.

Variable formation control of multiple robots via VRc and formation switching to accommodate large heading changes by leader robot

This article describes a novel multi-robot formation control based on a switching technique that allows follower robots to maintain formation when the leader robot’s direction changes rapidly or unexpectedly. The formation pattern is determined using Virtual Robot’s Center of the multi-robot formation. To avoid collision, the formation of robots reformed in optimal size by estimating the distance between the robot and an obstacle in real time. When the leader robot suddenly changes its direction, waypoints of follower robots are switched and the formation is quickly reconstructed. This prevents follower robots from colliding with each other and reduces their radius of movement and allows them to follow the leader robot at higher speed. The proposed method which is inherently a flexible control of multi-robot formation guarantees collision avoidance and prevents sudden changes in waypoints of the system by gradually changing its size. The validity of the proposed method is demonstrated via simulation and experimental results.

Research on Arbitrary Formation Control of Multiple Robots in Obstacle Environment

To overcome the multi-robots form arbitrary formation in obstacle environment, we propose a control algorithm that combines target allocation algorithm and obstacle avoidance strategy. Firstly, we express the distance between the position of robots and target points by distance information matrix, thus ensure each robot find the corresponding target point. The key idea of the algorithm is to avoid robots from detours and reduce the possibility of collisions between robots. Secondly, the obstacle avoidance is achieved by improving the artificial potential field method integrated with the strategy of moving along the periphery of obstacles. Finally, a simulation environment is established by pygame modules. Simulation results show that the proposed method is feasible and effective.

Decentralized behavior-based formation control of multiple robots considering obstacle avoidance

This paper proposes a decentralized behavior-based formation control algorithm for multiple robots considering obstacle avoidance. Using only the information of the relative position of a robot between neighboring robots and obstacles, the proposed algorithm achieves formation control based on a behavior-based algorithm. In addition, the robust formation is achieved by maintaining the distance and angle of each robot toward the leader robot without using information of the leader robot. To avoid the collisions with obstacles, the heading angles of all robots are determined by introducing the concept of an escape angle, which is related with three boundary layers between an obstacle and the robot. The layer on which the robot is located determines the start time of avoidance and escape angle; this, in turn, generates the escape path along which a robot can move toward the safe layer. In this way, the proposed method can significantly simplify the step of the information process. Finally, simulation results are provided to demonstrate the efficiency of the proposed algorithm.

Leader-Following Formation Control of Multiple Robots with Uncertainties through Sliding Mode and Nonlinear Disturbance Observer

Leader-Following Formation Control of Multiple Robots with Uncertainties through Sliding Mode and Nonlinear Disturbance Observer

Robust formation control of electrically driven nonholonomic mobile robots via sliding mode technique

This paper proposes a sliding mode formation control method for electrically driven nonholonomic mobile robots in the presence of model uncertainties and disturbances. We use the kinematic model based on the leader-following approach for the formation control of multiple robots. Unlike many researches considering only the kinematic model, we also consider the dynamic model including actuator dynamics to obtain the voltage input because it is more realistic to use the voltage as input than the velocity. Then, the sliding mode control method is used to deal with model uncertainties and disturbances acting on the mobile robots. The stability of the proposed control system is proven using Lyapunov stability theory. Finally, we perform computer simulations to demonstrate the performance of the proposed control system.

Dynamic Formation Control for Multiple Robots in Uncertain Environments

A novel dynamic formation control approach for multiple robots in uncertain environments is proposed, which adopts the formation parameter matrix to establish the relative relationship among the robots, transforms the global-level formation control problem into the problem that the-off-axis point of the follower tracks the-off-axis point on the virtual robot which has the same orientation with the leader robot and maintains the desired relative distance and desired observation angle with respect to its leader robot. The control law based on the derived error tracking system model about the follower and leader is designed to maintain the formation, and an obstacle avoidance strategy is proposed to prevent the robot from possible collisions with obstacles and other robots. Simulation results are given to demonstrate the feasibility and effectiveness of the approach.