Time-varying feedback stabilization of car-like wheeled mobile robots
International Journal of Robotics Research
Tracking-error model-based predictive control for mobile robots in real time
Robotics and Autonomous Systems
A neuro-fuzzy controller for mobile robot navigation and multirobotconvoying
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part III
Journal of Intelligent and Robotic Systems
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In this paper a case study of a new, cooperative, collision-avoidance method for multiple, nonholonomic robots based on Bernstein---Bézier curves is given. In the presented examples the velocities and accelerations of the mobile robots are constrained and the start and the goal velocity are defined for each robot. This means that the proposed method can be used as a subroutine in a huge path-planning problem in real time, in a way to split the whole path into smaller partial paths. The reference path of each robot, from the start pose to the goal pose, is obtained by minimizing the penalty function, which takes into account the sum of all the path lengths subjected to the distances between the robots, which should be bigger than the minimum distance defined as the safety distance, and subjected to the velocities and accelerations which should be lower than the maximum allowed for each robot. When the reference paths are defined the model-predictive trajectory tracking is used to define the control. The prediction model derived from the linearized tracking-error dynamics is used to predict future system behavior. The control law is derived from a quadratic cost function consisting of the system tracking error and the control effort. The proposed method was tested with a simulation and with a real-time experiment in which four robots were used.