Papers › Online Trajectory Optimization for Persistent Monitoring Problems in Partitioned Environments
Online Trajectory Optimization for Persistent Monitoring Problems in Partitioned Environments
Jonas Hall, Christos G. Cassandras, Sean B. Andersson
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We consider the problem of using an autonomous agent to persistently monitor a collection of dynamic targets distributed in an environment. We generalize existing work by allowing the agent's dynamics to vary throughout the environment, leading to a hybrid dynamical system. This introduces an additional layer of complexity towards the planning portion of the problem: we must not only identify in which order to visit the points of interest, but also in which order to traverse the regions. We design an offline high-level sequence planner together with an online trajectory optimizer realizing the computed visiting sequence. We provide numerical experiments to illustrate the performance of our approach.
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