Formations Of Nonholonomic Mobile Robots Research Articles

Adaptive Secure Control for Leader-Follower Formation of Nonholonomic Mobile Robots in the Presence of Uncertainty and Deception Attacks

This paper addresses an adaptive secure control problem for the leader-follower formation of nonholonomic mobile robots in the presence of uncertainty and deception attacks. It is assumed that the false data of the leader robot’s information attacked by the adversary is transmitted to the follower robot through the network, and the dynamic model of each robot has uncertainty, such as unknown nonlinearity and external disturbances. A robust, adaptive secure control strategy compensating for false data and uncertainty is developed to accomplish the desired formation of nonholonomic mobile robots. An adaptive compensation mechanism is derived to remove the effects of time-varying attack signals and system uncertainties in the proposed control scheme. Although unknown deception attacks are injected to the leader’s velocities and the model nonlinearities of robots are unknown, the boundedness and convergence of formation tracking errors of the proposed adaptive control system are analyzed in the Lyapunov sense. The validity of the proposed scheme is verified via simulation results.

Dynamic Leader Allocation in Multi-robot Systems Based on Nonlinear Model Predictive Control

This paper presents an approach to the dynamic leader selection problem in autonomous non-holonomic mobile robot formations when the current leader enters a failure state. Our method is based on a tree structure coupled with a modified version of the Nonlinear Model Predictive Control (NMPC) that allows for behavior change at the controller level. An explanation of the control algorithm, behavior selection, and leader selection structure is given, after which the results of both simulations and experiments using a three robot formation are shown and discussed.

Adaptation Mechanism of Asymmetrical Potential Field Improving Precision of Position Tracking in the Case of Nonholonomic UAVs

SummaryPosition-tracking problems in the structures of rigid formations of nonholonomic mobile robots, such as fixed-wing unmanned aerial vehicle (UAVs), must reconcile tracking precision and flight stability, which usually exclude each other due to nonholonomic motion constraints. Therefore, a position-tracking control that is based on distance and position displacement, defined as inputs of control loops, requires the application of dead zones around target positions, which are the points of instability. For this reason, the control becomes sensitive to any external disturbance causing oscillations of control signals and so it becomes difficult to maintain a zero value of position displacement over a long time horizon. Thus, we propose an approach based on the adaptive mechanism of an asymmetrical local artificial potential field, which is defined by a local frame of reference whose origin is located in the tracked position of a UAV in the formation frame. It couples controls of both airspeed and heading angle into a nonlinear potential function of relative position and orientation with respect to the tracked position and adapts it according to heading rate of the leader. The function splits the area around the tracked position longitudinally into two zones of acceleration and deceleration; therefore, velocity vectors are longer (higher airspeed) only when a UAV is behind the tracked position and shorter (lower airspeed) when it is ahead. The area is laterally symmetrical, and orientations of velocity vectors align asymptotically to the longitudinal direction accordingly with the decrease in the lateral error. Finally, velocity vectors are rotated proportionally to the heading rate of the leader, which improves the tracking precision during turns. If we assumed that a UAV’s tracked position is in motion, it could easily be proven that the position control based on the adaptive asymmetrical potential function becomes asymptotically stable in the tracked position. Numerical simulation verifies this thesis and presents more precise and stable position tracking due to the adaptation mechanism.

Distributed Estimation and Control for Leader-Following Formations of Nonholonomic Mobile Robots

The problem of the leader-following formation control of nonholonomic mobile robots is addressed in this paper. A distributed formation control strategy using explicitly the coordination errors among robots is proposed without assuming that each follower robot knows the full state of the leader. First, a distributed estimation law is proposed for each follower robot to estimate the states, including the position, orientation, and linear velocity of the leader. The distributed formation control law is then designed based on the estimated states of the leader, and the neighborhood formation tracking error. Under some mild assumptions on the interaction graph among the leader and the follower robots, and the velocity of the leader, asymptotic convergence of formation tracking errors to zero can be achieved. Finally, some numerical simulations and experiments on a group of nonholonomic mobile robots are presented to demonstrate the effectiveness of the proposed strategy. Note to Practitioners —The motivation of this paper is to investigate a practical control strategy for the leader-following formation of multiple autonomous mobile robots subjected to nonholonomic constraints. In most of the existing leader-following formation control schemes for nonholonomic mobile robots, having access to the full state of the leader is a requirement. However, due to limitations in communication bandwidth and range, it is reasonable to assume that the information of the leader is available only to a subset of followers. Hence, this paper suggests a new distributed leader-following formation control strategy based on the distributed estimation of the leader’s states. Moreover, the coordination error between a pair of interacting robots is explicitly used in the control design to weaken the dependence on the estimated state of the leader, and enhance the decentralized nature of the proposed control scheme. The stability and convergence of the system are analyzed mathematically and the experiment using unicycles provides promising results. In ongoing research, we are addressing the issues of collision avoidance and communication delays to provide more realistic setup for the industrial applications of multivehicle systems.

Leader Follower Formation Control of Ground Vehicles Using Dynamic Pixel Count and Inverse Perspective Mapping

This paper deals with leader-follower formations of non-holonomic mobile robots, introducing a formation control strategy based on pixel counts using a commercial grade electro optics camera. Localization of the leader for motions along line of sight as well as the obliquely inclined directions are considered based on pixel variation of the images by referencing to two arbitrarily designated positions in the image frames. Based on an established relationship between the displacement of the camera movement along the viewing direction and the difference in pixel counts between reference points in the images, the range and the angle estimate between the follower camera and the leader is calculated. The Inverse Perspective Transform is used to account for non linear relationship between the height of vehicle in a forward facing image and its distance from the camera. The formulation is validated with experiments.

Cooperative Visibility Maintenance for Leader–Follower Formations in Obstacle Environments

Vision-based formation control of multiple agents, such as mobile robots or fully autonomous cars, has recently received great interest due to its application in robotic networks and automated highways. This paper addresses the cooperative motion coordination of leader-follower formations of nonholonomic mobile robots, under visibility and communication constraints in known polygonal obstacle environments. We initially consider the case of N = 2 agents moving in L-F fashion and propose a feedback control strategy under which L ensures obstacle avoidance for both robots, while F ensures visibility maintenance with L and intervehicle collision avoidance. The derived algorithms are based on set-theoretic methods to guarantee visibility maintenance, dipolar vector fields to maintain the formation shape, and the consideration of the formation as a tractor-trailer system to ensure obstacle avoidance. We furthermore show how the coordination and control design extends to the case of N > 2 agents, and provide simulation results, which demonstrate the efficacy of the control solutions. The proposed algorithms do not require information exchange among robots, but are instead based on information locally available to each agent. In this way, the desired tasks are executed and achieved in a decentralized manner, with each robot taking care of converging to a desired configuration, while maintaining visibility with its target.

Asymptotic Adaptive Neural Network Tracking Control of Nonholonomic Mobile Robot Formations

In this paper, asymptotically stable control laws are developed for leader---follower based formation control using backstepping in order to accommodate the dynamics of the robots and the formation. First, a kinematic controller is developed around control strategies for single mobile robots and the idea of virtual leaders. The virtual leader is replaced with a physical mobile robot leader, and an auxiliary velocity control law is developed in order to prove the global asymptotic stability of the followers which in turn allows the local asymptotic stability of the entire formation. A novel approach is taken in the development of the dynamical controller such that the torque control inputs for the follower robots include the dynamics of the follower robot as well as the dynamics of its leader, and two cases are considered--the case when the robot dynamics are known and the case when they are unknown. In the first case, a robust adaptive control term is utilized to account for unmodeled dynamics. For the latter, a robust adaptive term is augmented with a NN control law to achieve asymptotic tracking performance in contrast with most NN controllers where a bounded tracking error result is shown. Additionally, the NN approximation error is assumed to be a function of tracking errors instead of a constant upper bound, which is commonly found in the literature. The stability of the follower robots as well as the entire formation is demonstrated in each case using Lyapunov methods and numerical results are provided.

Leader–follower formation control of nonholonomic mobile robots with input constraints

The paper deals with leader–follower formations of nonholonomic mobile robots, introducing a formation control strategy alternative to those existing in the literature. Robots’ control inputs are forced to satisfy suitable constraints that restrict the set of leader possible paths and admissible positions of the follower with respect to the leader. A peculiar characteristic of the proposed strategy is that the follower position is not rigidly fixed with respect to the leader but varies in proper circle arcs centered in the leader reference frame.

ENHANCED MOTION PLANNING FOR DYNAMIC FORMATIONS OF NONHOLONOMIC MOBILE ROBOTS

This paper presents an enhanced motion planning approach for formations of nonholonomic mobile robots which generates continuous speed and curvature profiles for all vehicles of the group. The formation is maintained in curvelinear coordinates during the motion which may be planned in realtime. Controlled modifications of the formation's shape can be executed as long as the nonholonomic constraints of the robots are not violated. The newly derived kinematic equations have been validated in simulations of various scenarios.

Modeling and control of formations of nonholonomic mobile robots

This paper addresses the control of a team of nonholonomic mobile robots navigating in a terrain with obstacles while maintaining a desired formation and changing formations when required, using graph theory. We model the team as a triple, (g, r, H), consisting of a group element g that describes the gross position of the lead robot, a set of shape variables r that describe the relative positions of robots, and a control graph H that describes the behaviors of the robots in the formation. Our framework enables the representation and enumeration of possible control graphs and the coordination of transitions between any two formations.