Overview
As we transition to Urban Air Mobility (UAM) where 500-1,000 drones will operate in dense urban airspaces, the two fundamental safety challenges are with urban air traffic management and airborne collision avoidance. My team has developed Fly-by-Logic, a robustness-maximizing controller for fleets of drones, and it is currently the fastest and most reliable controller of its kind. By describing drone missions in MTL, we can synthesize mission trajectories for hundreds of drones, each with spatial, temporal and reactive guarantees. As weather and mission disturbances are difficult to predict, we maximize MTL robustness, a mathematically rigorous way of measuring the amount of disturbance that the controlled system can withstand without failing its mission, across the fleets. We demonstrated the computational tractability, scalability and guaranteed continuous-time satisfaction of the resulting trajectories on-board real drones and over long-range multi-drone missions. Collision avoidance problems are notoriously complex and often resort to mixed integer linear programming which prevents real-time execution. My team has designed safe and efficient Learning-based decentralized collision avoidance for scalable urban air mobility.
4 UAS Collision Avoidance Simulation
Safe planning and control of multi-rotor drone fleets performing complex missions has been a challenging problem. Methods that offer guarantees on safety and mission satisfaction generally do not scale well. On the other hand, more computationally tractable approaches do not offer any safety guarantees. This project develops methods that overcomes these limitations for a wide variety of missions, e.g. the video below shows a mission where 2 pairs of drones are tasked with patrolling two regions within predefined time intervals, and while avoiding a no-fly zone and collisions with each other.
Publications
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Fly-by-Logic: A Tool for Unmanned Aircraft System Fleet Planning using Temporal Logic
Pant, Quaye, Abbas, Varre, Mangharam
NASA Formal Methods (FM), 2019. -
Fly-by-Logic: Control of Multi-Drone Fleets with Temporal Logic Objectives
Pant, Abbas, Quaye, Mangharam
International Conference on Cyber-Physical Systems (ICCPS), 2018. -
Smooth Operator, Smooth Operator: Control using the Smooth Robustness of Temporal Logic
Pant, Abbas, Mangharam
Conference on Control Technology and Applications (CCTA), 2017.
Contributors
Rodionova, Pant, Jang, Abbas, Mangharam
Citation
@INPROCEEDINGS{8443733,
author={Pant, Yash Vardhan and Abbas, Houssam and Quaye, Rhudii A. and Mangharam, Rahul},
booktitle={2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)},
title={Fly-by-Logic: Control of Multi-Drone Fleets with Temporal Logic Objectives},
year={2018},
volume={},
number={},
pages={186-197},
keywords={Trajectory;Robustness;Drones;Planning;Real-time systems;Optimization;Task analysis;Mulit drone missions;signal temporal logic;predictive control;robustness maximization;crazyflie},
doi={10.1109/ICCPS.2018.00026}}
