Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Neural Network Control of Robot Manipulators and Nonlinear Systems
Neural Network Control of Robot Manipulators and Nonlinear Systems
International Journal of Robotics Research
Queues and Artificial Potential Trenches for Multirobot Formations
IEEE Transactions on Robotics
Control of a nonholonomic mobile robot using neural networks
IEEE Transactions on Neural Networks
Asymptotic Adaptive Neural Network Tracking Control of Nonholonomic Mobile Robot Formations
Journal of Intelligent and Robotic Systems
A method for obstacle avoidance in role reassignment of robot formation control
WSEAS TRANSACTIONS on SYSTEMS
Neural network output feedback control of robot formations
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Information Sciences: an International Journal
Fuzzy Neural Network Control for Robot Manipulator Directly Driven by Switched Reluctance Motor
International Journal of Cognitive Informatics and Natural Intelligence
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In this paper, an asymptotically stable (AS) combined kinematic/torque control law is developed for leader-follower-based formation control using backstepping in order to accommodate the complete dynamics of the robots and the formation, and a neural network (NN) is introduced along with robust integral of the sign of the error feedback to approximate the dynamics of the follower as well as its leader using online weight tuning. It is shown using Lyapunov theory that the errors for the entire formation are AS and that the NN weights are bounded as opposed to uniformly ultimately bounded stability which is typical with most NN controllers. Additionally, the stability of the formation in the presence of obstacles is examined using Lyapunov methods, and by treating other robots in the formation as obstacles, collisions within the formation do not occur. The asymptotic stability of the follower robots as well as the entire formation during an obstacle avoidance maneuver is demonstrated using Lyapunov methods, and numerical results are provided to verify the theoretical conjectures.