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

Finite-Time Consensus on the Median Value by Discontinuous Control

In this paper we propose a novel protocol to solve the consensus on the median value problem, i.e., the decentralized agreement problem for networked multi-agent systems where the quantity of interest is the median value as opposed to the average value of the agents' states. The median value is a statistical measure particularly robust to the existence of outlier agents which are a significant issue in large scale averaging networks. The proposed protocol achieves consensus on the median value in finite time by exploiting a discontinuous local interaction rule

Advancements in Adversarially-Resilient Consensus and Safety-Critical Control for Multi-Agent Networks

The capabilities of and demand for complex autonomous multi-agent systems, including networks of unmanned aerial vehicles and mobile robots, are rapidly increasing in both research and industry settings. As the size and complexity of these systems increase, dealing with faults and failures becomes a crucial element that must be accounted for when performing control design. In addition, the last decade has witnessed an ever-accelerating proliferation of adversarial attacks on cyber-physical systems across the globe. In response to these challenges, recent years have seen an increased focus on resilience of multi-agent systems to faults and adversarial attacks. Broadly speaking, resilience refers to the ability of a system to accomplish control or performance objectives despite the presence of faults or attacks. Ensuring the resilience of cyber-physical systems is an interdisciplinary endeavor that can be tackled using a variety of methodologies. This dissertation approaches the resilience of such systems from a control-theoretic viewpoint and presents several novel advancements in resilient control methodologies. First, advancements in resilient consensus techniques are presented that allow normally-behaving agents to achieve state agreement in the presence of adversarial misinformation. Second, graph theoretic tools for constructing and analyzing the resilience of multi-agent networks are derived. Third, a method for resilient broadcasting vector-valued information from a set of leaders to a set of followers in the presence of adversarial misinformation is presented, and these results are applied to the problem of propagating entire knowledge of time-varying Bezier-curve-based trajectories from leaders to followers. Finally, novel results are presented for guaranteeing safety preservation of heterogeneous control-affine multi-agent systems with sampled-data dynamics in the presence of adversarial agents.PHDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168102/1/usevitch_1.pd