Team Of Wheeled Mobile Robots Research Articles

A Hybrid Controller for Multi-Agent Collision Avoidance via a Differential Game Formulation

We consider the multi-agent collision avoidance problem for a team of wheeled mobile robots. Recently, a local solution to this problem, based on a game-theoretic formulation, has been provided and validated via numerical simulations. Due to its local nature, the result is not well-suited for online applications. In this article, we propose a novel hybrid implementation of the control inputs that yields a control strategy suited for the online navigation of mobile robots. Moreover, subject to a certain dwell time condition, the resulting trajectories are globally convergent. The control design is demonstrated both via simulations and experiments.

Real-Time Fault-Tolerant Formation Control of Multiple WMRs Based on Hybrid GA–PSO Algorithm

A fault-tolerant formation control (FTFC) strategy is proposed against severe actuator faults, applied to a team of wheeled mobile robots (WMRs). In the beginning, a team of WMRs is operating in a prescribed formation topology. As long as the robot(s) cannot complete the required mission due to severe actuator faults, the formation is reconfigured for the healthy WMRs to eliminate the fault effects. The new reconfiguration is determined by means of an optimal assignment scheme so that each healthy robot can be assigned to a unique position. Subsequently, each robot starts planning its trajectory to reach its new position in the new formation configuration by virtue of a hybrid genetic algorithm and particle swarm optimization (GA–PSO). As metaheuristic optimization techniques, such as GA and PSO, are unable to solve the optimization problem with continuous control inputs, control parameterization and time discretization (CPTD) method is, therefore, adopted to offer an approximate piecewise linearization of the control inputs. Thus, an approach with the integration of CPTD and GA–PSO is developed. This integrated approach enables that the time of achieving the configuration is minimized, while the physical constraints of WMRs and collision avoidance are explicitly considered. Finally, real-time experiments are conducted to validate the effectiveness of the proposed algorithm compared with other optimization techniques, such as GA and PSO. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Cooperative unmanned systems have drawn significant interests in military and civilian applications. During missions’ execution, it is of great importance for cooperative unmanned systems to have fault-tolerance capabilities for achieving the desired mission when faults occur in one or more team members. A challenging problem is how to detect and isolate the fault and how to mitigate the fault effects on the whole mission. This article presents a fault-tolerant formation control strategy in the case of severe actuator fault occurrence in a team of wheeled mobile robots.

Persistification of Robotic Tasks

In this article, we propose a control framework that enables robots to execute tasks persistently, i.e., over time horizons much longer than robots’ battery life. This is achieved by ensuring that the energy stored in the batteries of the robots is never depleted. This condition is framed as a set invariance constraint in an optimization problem whose objective is that to minimize the difference between the robots’ control inputs and nominal control inputs corresponding to the task that is to be executed. We refer to this process as the persistification of a robotic task. Forward invariance of subsets of the state space of the robots is turned into a control input constraint by using control barrier functions. The solution to the formulated optimization problem with energy constraints ensures that the robotic task is persistent. To illustrate the operation of the proposed framework, we consider two tasks whose persistent execution is particularly relevant: environment exploration and environment surveillance. We show the persistification of these two tasks both in simulation and on a team of wheeled mobile robots on the Robotarium.

Distributed active fault tolerant control design against actuator faults for multiple mobile robots

This paper investigates the active fault tolerant cooperative control problem for a team of wheeled mobile robots whose actuators are subjected to partial or severe faults during the team mission. The cooperative robots network only requires the interaction between local neighbors over the undirected graph and does not assume the existence of leaders in the network. We assume that the communication exists all the time during the mission. To avoid the system’s deterioration in the event of a fault, a set of extended Kalman filters (EKFs) are employed to monitor the actuators’ behavior for each robot. Then, based on the online information given by the EKFs, a reconfigurable sliding mode control is proposed to take an appropriate action to accommodate that fault. In this research study, two types of faults are considered. The first type is a partial actuator fault in which the faulty actuator responds to a partial of its control input, but still has the capability to continue the mission when the control law is reconfigured. In addition, the controllers of the remaining healthy robots are reconfigured simultaneously to move within the same capability of the faulty one. The second type is a severe actuator fault in which the faulty actuator is subjected to a large loss of its control input, and that lead the exclusion of that faulty robot from the team formation. Consequently, the remaining healthy robots update their reference trajectories and form a new formation shape to achieve the rest of the team mission.

High-Gain Observer-Based Neural Adaptive Feedback Linearizing Control of a Team of Wheeled Mobile Robots

SummaryThis paper addresses the neural network (NN) output feedback formation tracking control of nonholonomic wheeled mobile robots (WMRs) with limited voltage input. A desired formation is achieved based on the leader–follower strategy utilizing hyperbolic tangent saturation functions to reduce the risk of actuator saturation. The controller is developed by incorporating the high-gain observer and radial basis function (RBF) NNs using the inverse dynamics control technique. The high-gain observer is introduced to estimate velocities of the followers. The RBF NN preserves the robustness of the proposed controller against uncertain nonlinearities. The adaptive laws are also combined by a robust control term to estimate the weights of RBF NN, approximation errors, and bounds of unknown time-variant environmental disturbances. A Lyapunov-based stability analysis proves that all signals of the closed-loop system are bounded, and tracking errors are uniformly ultimately bounded. Finally, some simulations are carried out to show the effectiveness of the proposed controller for a number of WMRs.

Collision-Free Formation Control with Decentralized Connectivity Preservation for Nonholonomic-Wheeled Mobile Robots

The preservation of connectivity in mobile robot networks is critical to the success of most existing algorithms designed to achieve various goals. The most basic method to preserve connectivity is to have each agent preserve its set of neighbors for all time. More advanced methods preserve a (minimum) spanning tree in the network. Other methods are based on increasing the algebraic graph connectivity, which is given by the second smallest eigenvalue λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> (L) of the graph Laplacian λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> (L) that represents the network. These methods typically result in a monotonic increase in connectivity until the network is completely connected. In previous work by the authors, a continuous feedback control method had been proposed which allows the connectivity to decrease, that is, edges in the network may be broken. This method requires agents to have knowledge of the entire network. In this paper, we modify the controller to use only local information. The connectivity controller is based on maximization of λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> (L) and artificial potential functions and can be used in conjunction with artificial potential-based formation controllers. The controllers are extended for implementation on nonholonomic-wheeled mobile robots, and the performance is demonstrated in an experiment on a team of wheeled mobile robots.

Fault-Tolerant Cooperative Control of Multiple Wheeled Mobile Robots Under Actuator Faults

This paper investigates fault-tolerant cooperative control (FTCC) strategies for multiple autonomous differentially-driven wheeled mobile robots (WMRs) in the presence of actuator faults during formation operation. Initially, an integrated approach with a decentralized linear model predictive control (MPC) and an input-output feedback linearization is designed and implemented on a team of WMRs in order to accomplish a formation task under normal conditions (i.e., fault-free cases). The linear model of each robot with nonlinear dynamics is found through feedback linearization, while MPC is subsequently applied to the linear model of each robot to perform the formation control. When actuator faults occur in one of the robots of the team, the faulty robot is not able to complete its assigned task anymore due to the fault, and the faulty robot has to get out from the formation mission. An FTCC strategy is designed with the tasks of the WMRs team are re-assigned to the remaining healthy vehicles to still complete the mission but with graceful performance degradation. Formation operation of the robot team is based on a leader-follower approach, while the control algorithm is implemented in a decentralized manner. Simulation results are presented to demonstrate the performance of the designed algorithm in several fault scenarios.

Coverage with a Team of Wheeled Mobile Robots

This article presents a control system enabling coverage of a prescribed ground area by a team of wheeled mobile robots. The control system relies on equal balancing of the costs among the wheeled robots. Cost balancing leverages the intuition that a healthy neighbor could help a degraded robot to carry out its monitoring task simply by moving slightly towards the degraded robot. This feature allows the control system to support situations where vehicles have varying sensor characteristics. The article focuses on the design of the system and the results of experiments obtained with a small number of networked ground robots. The coverage control system is decentralized. Hence, no element of the system is a single point of failure, and the computations can be distributed. The experiments show (1) the satisfactory, yet suboptimal, performance of the coverage control system under healthy conditions, and the adaptation of the vehicles in case a team member is subject to a degraded condition of operation, and (2) the feasibility of the integration of the coverage control system with low-cost commercial wheeled mobile robot systems.