Planeación de trayectorias por Fuzzy C-means para robots móviles

In this paper presents the development of a trajectory planning algorithm for a simulated work environment, where the Fuzzy C-Means clustering method was used to determine the degree of membership of each space point obstacles presents to robot displacement and to find all possible paths that pass in the middle of them. The algorithm identifies paths for an environment with maximum 6 obstacles, and allows the user to enter the partition coefficient of the fuzzy (m) to define the width of each path according to the requirements of the application.En este artículo se presenta el diseño y ejecución de un algoritmo de planeación de trayectorias - en un ambiente de trabajo simulado - empleando el método de clustering por Fuzzy C-Means, para determinar el grado de pertenencia de cada punto del espacio a los obstáculos presentes en el área de desplazamiento de un robot móvil. Se desarrolló una herramienta en MATLAB® que permite ingresar la cantidad de objetos en dicha área, y así encontrar todos los posibles caminos que pasen en medio de ellos. El algoritmo logra identificar caminos para un ambiente con máximo 6 obstáculos, y le permite al usuario ingresar datos de control del algoritmo -como el coeficiente de partición del difuso (m) empleado para definir el ancho de cada camino según los requerimientos de la aplicación

Online Trajectory Generation for Mobile Robots with Kinodynamic Constraints and Embedded Control Systems

The paper describes trajectory generation and tracking control algorithms, respectively based on nonlinear filtering and dynamic feedback linearization, for mobile robots. A main feature of proposed algorithms is that they are suitable for the implementation on embedded systems with limited computational resources. The trajectory generator is based on nonlinear filters and logic-based management of reference inputs and dynamic constraints, allowing online smoothing of straight-line reference paths. Sparse via-points along a path can be assigned by a global planner based on obstacle avoidance algorithms and can be changed at any time during motion. Moreover, the trajectory generated by the nonlinear filter can be fed into a control loop based on the dynamic model of the robot, so that accurate tracking can be achieved. The paper includes practical remarks for efficient fixed-point implementation of the proposed trajectory generator

Online Trajectory Generation for Mobile Robots with Kinodynamic Constraints and Embedded Control Systems

The paper describes trajectory generation and tracking control algorithms, respectively based on nonlinear filtering and dynamic feedback linearization, for mobile robots. A main feature of proposed algorithms is that they are suitable for the implementation on embedded systems with limited computational resources. The trajectory generator is based on nonlinear filters and logic-based management of reference inputs and dynamic constraints, allowing online smoothing of straight-line reference paths. Sparse via-points along a path can be assigned by a global planner based on obstacle avoidance algorithms and can be changed at any time during motion. Moreover, the trajectory generated by the nonlinear filter can be fed into a control loop based on the dynamic model of the robot, so that accurate tracking can be achieved. The paper includes practical remarks for efficient fixed-point implementation of the proposed trajectory generator