Metodología para la síntesis de autómatas en la planificación de movimientos en sistemas autónomos con múltiples agentes

Objective: To develop a methodology for motion planning in autonomous systems with multiple agents.   Methodology: In the first place, a parametric definition of the behavior of a team of autonomous navigation systems is established. Then, the control policies are interpreted by a synthesis algorithm by converting the task description into LTL formulas and therefore generating a model that allows for automatic abstractions.  Starting from configurations of generic solutions, we derive the case of multiple robots with a unique task, assuming an environment with stationary obstacles. The methodology is validated in all the aforementioned scenarios, and results are then analyzed and discussed.   Results: Our proposed methodology, for motion planning in autonomous systems with multiple agents, combines two state-of-the-art techniques, mitigating the combinatorial explosion of states in traditional approaches.   Conclusions: Our proposed methodology solves the automaton synthesis for multiple agents with high-level control, and even with task changes during the execution. The problem of combinatorial explosion of states is mitigated. The solution is optimized vis-a-vis the number of transactions performed by the team members.   Financing: Universidad Tecnológica de Pereira  Objetivo: Presentar una metodología para la planificación de movimientos de sistemas autónomos con múltiples agentes.   Metodología: Se define y parametriza el comportamiento físico de un equipo de sistemas de navegación autónoma, luego se describe e implementa un algoritmo de síntesis de políticas de control que interpreta estas descripciones convertidas a fórmulas LTL y se genera un modelo que permite hacer abstracciones automáticas. A partir de configuraciones genéricas de solución, se deriva en el caso de múltiples robots con una única tarea en un entorno con obstáculos fijos. La metodología se valida en diferentes escenarios y se analizan los resultados.   Resultados: La metodología propuesta para planificación de movimientos en sistemas con múltiples agentes, combina dos técnicas del estado del arte, permitiendo mitigar la explosión combinacional de estados presente en los enfoques tradicionales.   Conclusiones: La metodología que se presenta resuelve el problema de síntesis de autómatas para el control de alto nivel, con cambio de tareas durante la ejecución. Bajo ciertos criterios, se mitiga el problema de explosión combinacional de estados asociado a estos sistemas. La solución es óptima respecto al número de transiciones seguidas por los miembros del equipo.   Financiamiento: Universidad Tecnológica de Pereira

Path planning of multirobot systems using Petri net models. Results and open problems

[EN] This paper presents a trajectory planning approach in multirobot systems based on Petri net models. This type of models is very useful for high-level specifications since, in this case, the classical planning methods (potential functions, RRT algorithms, RRT*) cannot be used being dicult to determine a priori the sequence of configurations for each robot. This work presents the formal definition of the Robot Motion Petri net t hat i s obtained from a partition of the environment in cells. Using the s tructure of the Petri net, in case of specifications defined as Boolean or Linear Temporal Logic (LTL) formulas, dierent optimization problems are presented that can be used to obtain trajectories for robots. The main advantage of models based on Petri nets is their scalability with respect to the number of robots. This makes it possible to reciently solve planning problems with a large number of robots. In the second part of the paper, some extensions and new results for distributed planning in unknown environments and with partial communications between robots are presented.[ES] Este trabajo presenta una estrategia de planificacón de trayectorias en equipos de robots moviles basada en el uso de modelos definidos con redes de Petri. Estos tipos de modelos son muy útiles para especificaciones de alto nivel ya que, en este caso, los métodos clásicos de planificación (funciones potenciales, algoritmos RRT, RRT*) no se pueden utilizar, siendo difícil determinar a priori la secuencia de configuraciones para cada robot. Este trabajo presenta la definición formal de la Red de Petri de Movimiento de Robots que se obtiene a partir de una partición del entorno en celdas. Utilizando la estructura de la red de Petri, en caso de especificaciones definidas como fórmulas Booleanas o fórmulas en lógica temporal lineal (LTL), se presentan diferentes problemas de optimización que se pueden utilizar para obtener trayectorias para los robots. La principal ventaja de los modelos basados en redes de Petri es su escalabilidad con respecto al número de robots. Ello permite resolver con eficiencia problemas de planificación de equipos con un número grande de robots. En la segunda parte del trabajo, se presentan algunas extensiones y resultados nuevos para la planificación distribuida en entornos desconocidos y con comunicaciones parciales entre los robots.Los resultados de esta línea de investigación son fruto de la participación de varios compañeros, investigadores de la Universidad de Zaragoza y de otras Universidades extranjeras. 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