Papers by Mohamed A. Kamel
Recently, cooperative control of multiple unmanned vehicles has attracted a great deal of attenti... more Recently, cooperative control of multiple unmanned vehicles has attracted a great deal of attention from scientific, industrial, and military aspects. Groups of unmanned ground, aerial, or marine vehicles working cooperatively lead to many advantages in a variety of applications such as: surveillance, search and exploration, cooperative reconnaissance, environmental monitoring, and cooperative manipulation, respectively. During mission execution, unmanned systems should travel autonomously between different locations, maintain a pre-defined formation shape, avoid collisions of obstacles and also other team members, and accommodate occurred faults and mitigate their negative effect on mission execution.
Intelligent Service Robotics
This paper presents an online path planning approach for an autonomous tracked vehicle in a clutt... more This paper presents an online path planning approach for an autonomous tracked vehicle in a cluttered environment based on teaching–learning-based optimization (TLBO), considering the path smoothness, and the potential collision with the surrounding obstacles. In order to plan an efficient path that allows the vehicle to be autonomously navigated in cluttered environments, the path planning problem is solved as a multi-objective optimization problem. First, the vehicle perception is fully achieved by means of inertial measurement unit (IMU), wheels odometry, and light detection and ranging (LiDAR). In order to compensate the sensors drift to achieve more reliable data and improve the localization estimation and corrections, data fusion between the outputs of wheels odometry, LiDAR, and IMU is made through extended Kalman filter (EKF). Then, TLBO is proposed and applied to determine the optimum online path, where the objectives are to find the shortest path to reach the target destin...
2020 12th International Conference on Electrical Engineering (ICEENG), 2020
This paper presents a global trajectory generation and tracking control algorithms for a tracked ... more This paper presents a global trajectory generation and tracking control algorithms for a tracked unmanned ground vehicle (UGV) in cluttered environment. First, it is assumed that the surrendering environment is fully known. Then, the UGV path is planned based on a modified artificial potential field (APF), for the vehicle to move from the start location to the desired destination while avoiding the collision with the surrounding obstacles. Next, an optimized back-stepping controller is developed to achieve the trajectory tracking control. In order to find the optimum controller’s gains, the trajectory tracking problem is solved as an optimization problem where the objective is to minimize the error between the UGV actual and desired positions. The optimization problem is formulated as a sequential quadratic problem (SQP) considering the UGV kinematic and dynamic constraints. Finally, numerical simulations are conducted in order to show the effectiveness of the proposed algorithms.
Communications - Scientific letters of the University of Zilina, 2022
This study provides a teaching-learning-based optimization (TLBO) path planning method for an aut... more This study provides a teaching-learning-based optimization (TLBO) path planning method for an autonomous vehicle in a cluttered environment, which takes into account path smoothness and the possibility of collision with nearby obstacles. The path planning problem is tackled as a multiobjective optimization in order to plan an efficient path that allows the vehicle to travel autonomously in crowded settings. The TLBO algorithm is used to find the ideal path, with the goals of finding the shortest path to the target site and maximizing path smoothness, while avoiding obstacles and taking into account the vehicle's dynamic and algebraic properties.
2015 IEEE International Conference on Information and Automation, 2015
This paper investigates the formation control of multiple differentially driven wheeled mobile ro... more This paper investigates the formation control of multiple differentially driven wheeled mobile robots (WMRs) based on the kinematic model and the leader-follower approach. A combination of linear model predictive control and input-output feedback linearization is implemented on a team of WMRs in order to accomplish a formation task. The linear model of each robot with nonlinear dynamics is found through feedback linearization, while model predictive control is applied to the linear model to perform the formation control. Stability analysis is proven, and simulation results are presented in order to demonstrate the performance of the proposed algorithm.
2017 International Conference on Unmanned Aircraft Systems (ICUAS), 2017
This paper investigates the problems of task assignment and trajectory planning for teams of coop... more This paper investigates the problems of task assignment and trajectory planning for teams of cooperative unmanned aerial vehicles (UAVs). A novel approach of hierarchical fuzzy logic controller (HFLC) and particle swarm optimization is proposed. Initially, teams of UAVs are moving in a pre-determined formation covering a specified area. When one or more targets are detected, the teams send a package of information to the ground station (GS) including the target's degree of threat, degree of importance, and the separating distance between each team and each detected target. First, the ground station assigns the teams to the targets based on the gathered information. HFLC is implemented in the GS to solve the assignment problem ensuring that each team is assigned to a unique target. Then, each team plans its own path by formulating the path planning problem as an optimization problem, while the objective is to minimize the time to reach their destination considering the UAVs dynamic constraints and the collision avoidance between teams. A hybrid approach of control parametrization and time discretization (CPTD) and PSO is proposed to solve the optimization problem. Finally, numerical simulations demonstrate the effectiveness of the proposed algorithm.
Recently, unmanned vehicles have attracted a great deal of attentionin academic, civilian and mil... more Recently, unmanned vehicles have attracted a great deal of attentionin academic, civilian and military communities as prospectivesolutions to a wide variety of applications. With this growinginterest, there has been a great development of unmanned systemscontrol techniques. One of the promising approaches in the field ofunmanned systems is model predictive control (MPC) due to itsability to handle the multi-variable constrained systems. Therefore,the goal of this paper is to present a comprehensive literature ofapplying MPC for motion control of both unmanned groundvehicles (UGVs) and unmanned aerial vehicles (UAVs). First, anoverview of motion control principles is presented. Next, anoverview of MPC including its concept, formulation, types, and itsstability is provided. Then, a comprehensive literature review ofapplying MPC to both UGVs and UAVs is introduced, including thebasic motion tasks such as path planning, point stabilization, andtrajectory tracking. Finally, open problems...
Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 2021
This article presents a complete kinematic and dynamic modeling and trajectory tracking control o... more This article presents a complete kinematic and dynamic modeling and trajectory tracking control of an autonomous tracked vehicle. First, based on the vehicle’s kinematics, the reference linear and angular velocities are evaluated. The kinematic controller is proposed as an integrated backstepping controller. Then, based on vehicle dynamics and slipping characteristics, an integral sliding mode control is utilized to get the desired vehicle drive torques and converge its trajectory to the desired one. Whereas the controller gains are optimally calculated. Furthermore, based on the Lyapunov stability, the proof of stability for proposed controllers is presented. Finally, simulation results are conducted to validate the effectiveness of the proposed control algorithm compared with a hybrid backstepping-modified proportional–integral–derivative dynamic controller and a nonlinear feedback acceleration controller.
2016 American Control Conference (ACC), 2016
This paper investigates new fault-tolerant cooperative control (FTCC) strategies for multiple whe... more This paper investigates new fault-tolerant cooperative control (FTCC) strategies for multiple wheeled mobile robots (WMRs) in the presence of actuator faults. When actuator faults occur in one of the robots of the team, two cases are considered: 1) the faulty robot cannot complete its assigned task due to a severe fault occurrence, and it has to get out from the formation mission. As a result, the FTCC strategy is designed to re-assign the mission to the remaining healthy robots; and 2) the faulty robot can continue the mission with degraded performance, then the other team members reconfigure their controllers considering the remaining capability of faulty robot. Thus, the FTCC strategy is developed to re-coordinate the motion of each robot in the team. A fault detection and diagnosis (FDD) scheme using a two-stage Kalman filter is presented. Simulation results are presented to demonstrate the performance of the team in different fault scenarios.
2016 3rd Conference on Control and Fault-Tolerant Systems (SysTol), 2016
This paper investigates fault-tolerant cooperative control (FTCC) of multiple wheeled mobile robo... more This paper investigates fault-tolerant cooperative control (FTCC) of multiple wheeled mobile robots (WMRs) in the presence of severe actuator faults. Initially, a team of robots is moving in pre-defined formation configuration. When actuator faults occur in one or more robots, and the faulty robot(s) cannot complete the mission, the rest of robots start reconfiguring the formation to compensate the fault effect on the whole mission. First, the new formation reconfiguration is generated by solving an optimal assignment problem where each healthy robot should be assigned to a unique place. Then, the new formation can be reconfigured by recasting the reconfiguration problem as an optimization problem, while the objective is to minimize the time to achieve the new formation reconfiguration within the constraints of the robots' dynamics and collision avoidance. A hybrid approach of control parametrization and time discretization (CPTD) and particle swarm optimization (PSO) is proposed to solve the optimization problem. The results of the numerical simulations demonstrate the effectiveness of the proposed algorithm.
Annual Reviews in Control, 2020
Abstract Recently, multiple unmanned vehicles have attracted a great deal of attention as viable ... more Abstract Recently, multiple unmanned vehicles have attracted a great deal of attention as viable solutions to a wide variety of civilian and military applications. Among many topics in the field of multiple unmanned systems, formation control and coordination is of great importance. This paper presents a comprehensive literature review on the strategies and methodologies applied for formation control of multiple unmanned ground vehicles in both normal and faulty situations. First, the basic definitions of formation control and coordination are provided as well as their classification. Second, a comprehensive literature review of formation control strategies is introduced. Moreover, an overview on fault detection and diagnosis and fault-tolerant cooperative control of UGVs is presented. Finally, open problems, challenges, and future directions are highlighted.
Unmanned Systems, 2018
This paper investigates the problems of cooperative task assignment and trajectory planning for t... more This paper investigates the problems of cooperative task assignment and trajectory planning for teams of cooperative unmanned aerial vehicles (UAVs). A novel approach of hierarchical fuzzy logic controller (HFLC) and particle swarm optimization (PSO) is proposed. Initially, teams of UAVs are moving in a pre-defined formation covering a specified area. When one or more targets are detected, the teams send a package of information to the ground station (GS) including the target’s degree of threat, degree of importance, and the separating distance between each team and each detected target. Based on the gathered information, the ground station assigns the teams to the targets. HFLC is implemented in the GS to solve the assignment problem ensuring that each team is assigned to a unique target. Next, each team plans its own path by formulating the path planning problem as an optimization problem. The objective in this case is to minimize the time to reach their destination considering th...
2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE), 2015
This work investigates the formation control and obstacle avoidance of multiple differentially dr... more This work investigates the formation control and obstacle avoidance of multiple differentially driven wheeled mobile robots (WMRs) based on the kinematic model and the leader-follower approach. A combination of a linear model predictive control and input-output feedback linearization is implemented on a team of WMRs in order to accomplish a formation task. The linear model of each robot with nonlinear dynamics is found through feedback linearization, while model predictive control is applied to the linear model to perform the formation control. An obstacle avoidance algorithm also implemented to each robot in formation. The obstacle avoidance strategy is based on generating a virtual force that is considered to make corrections in the linear and angular velocities of each robot in formation. Simulation results are presented in order to demonstrate the performance of a team of WMRs with two formation mission scenarios.
2015 International Conference on Unmanned Aircraft Systems (ICUAS), 2015
A fault tolerant cooperative control (FTCC) strategy for a team of an unmanned aerial vehicle (UA... more A fault tolerant cooperative control (FTCC) strategy for a team of an unmanned aerial vehicle (UAV) and unmanned ground vehicles (UGVs) in the presence of actuator faults are investigated in this paper. A combination of a linear model predictive control (MPC) and input-output feedback linearization is implemented on each UGV, while a combination of a sliding mode control and linear quadratic regulator (LQR) are applied to the UAV. When a severe actuator fault occurs in one of the robots, it becomes unable to complete its assigned task, and it has to get out from the formation mission. FTCC strategy is designed with the robots' tasks are re-assigned to the remaining healthy robots to complete the mission with graceful degradation. The FTCC problem is solved as an optimal assignment problem, while a Hungarian algorithm which applied to each robot will solve the assignment problem. Formation operation of the robot team is based on a leader-follower approach, and the control algorithm is implemented in a decentralized manner. Finally, simulation results are presented in order to demonstrate the performance of the team in both fault-free case and faulty case.
2016 International Conference on Unmanned Aircraft Systems (ICUAS), 2016
This paper investigates fault-tolerant cooperative control (FTCC) strategy for a team of unmanned... more This paper investigates fault-tolerant cooperative control (FTCC) strategy for a team of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) in the presence of actuator faults. When actuator faults occur in one or more of the UGVs, two cases are considered: 1) the faulty UGV cannot complete its assigned task due to a severe fault occurrence, it has to get out from the formation mission. Then, FTCC strategy is designed to re-assign the mission to the remaining healthy vehicles; and 2) the faulty UGV can continue the mission with degraded performance, then the other team members will reconfigure their controllers considering the capability of faulty UGV. Thus, the FTCC strategy is designed to re-coordinate the motion of each UAV-UGV in the team. FTCC problem is formulated as an optimal assignment problem, where a Hungarian algorithm is applied. Simulation results and real-time experiments are presented in order to demonstrate the effectiveness of the proposed FTCC scheme in different fault scenarios.
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Papers by Mohamed A. Kamel