Fast, Composable Rescue Mission Planning for UAVs using Metric Temporal Logic

TL;DR

This paper introduces a hybrid compositional method for real-time UAV mission planning in search and rescue, utilizing Metric Temporal Logic to ensure safety, efficiency, and scalability in complex environments.

Contribution

It presents a novel approach combining MTL specifications with hybrid dynamical models and MILP optimization for scalable, real-time multi-UAV mission planning.

Findings

Reduces computational complexity enabling real-time implementation

Ensures safety and mission completion within finite time

Scales effectively with multiple UAVs

Abstract

We present a hybrid compositional approach for real-time mission planning for multi-rotor unmanned aerial vehicles (UAVs) in a time critical search and rescue scenario. Starting with a known environment, we specify the mission using Metric Temporal Logic (MTL) and use a hybrid dynamical model to capture the various modes of UAV operation. We then divide the mission into several sub-tasks by exploiting the invariant nature of safety and timing constraints along the way, and the different modes (i.e., dynamics) of the UAV. For each sub-task, we translate the MTL specifications into linear constraints and solve the associated optimal control problem for desired path, using a Mixed Integer Linear Program (MILP) solver. The complete path for the mission is constructed recursively by composing the individual optimal sub-paths. We show by simulations that the resulting suboptimal trajectories satisfy the mission specifications, and the proposed approach leads to significant reduction in computational complexity of the problem, making it possible to implement in real-time. Our proposed method ensures the safety of UAVs at all times and guarantees finite time mission completion. It is also shown that our approach scales up nicely for a large number of UAVs.