Talking to Autonomous Drones: Command and Control Based on Hierarchical Task Decomposition

With increasing onboard intelligence and planning capabilities, autonomous unmanned aircraft system (UAS) can execute a wide spectrum of tasks ranging from low-level flight tasks to complex abstract mission tasks. Regardless of their onboard intelligence, most state-of-the-art UAS are commanded with waypoint-based command and control (C2) interfaces. However, waypoint-based interfaces are not well suited to represent mission tasks at different levels of abstraction. In this work, we address the problem of designing a C2 interface for autonomous UAS at a conceptual level. We propose a C2 interface that allows operating UAS at different levels of autonomy using task decomposition and a hierarchical data format for transmission. This interface is designed to enable transparent and consistent communication of mission tasks between the ground control station and the onboard systems. We demonstrate the application of the interface for two different UAS mission scenarios in detail. The proposed interface is designed to supersede waypoint-based C2 interfaces for the next generation of UAS providing high-level autonomy through onboard intelligence.

[1]  Erann Gat,et al.  Experiences with an architecture for intelligent, reactive agents , 1997, J. Exp. Theor. Artif. Intell..

[2]  Christopher D. Wickens,et al.  A model for types and levels of human interaction with automation , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[3]  James S. Albus,et al.  Autonomy Levels For Unmanned Systems (ALFUS) framework, volume II :: framework models version 1.0 , 2007 .

[4]  Charles Pippin Integrated Hardware/Software Architectures to Enable UAVs for Autonomous Flight , 2015 .

[5]  Vincenzo Lippiello,et al.  Aerial service vehicles for industrial inspection: task decomposition and plan execution , 2013, Applied Intelligence.

[6]  Jyi-Shane Liu,et al.  UAV System Integration of Real-time Sensing and Flight Task Control for Autonomous Building Inspection Task , 2019, 2019 International Conference on Technologies and Applications of Artificial Intelligence (TAAI).

[7]  Vincenzo Lippiello,et al.  Mixed-Initiative Planning and Execution for Multiple Drones in Search and Rescue Missions , 2015, ICAPS.

[8]  Petter Ögren,et al.  Increasing Modularity of UAV Control Systems using Computer Game Behavior Trees , 2012 .

[9]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[10]  Alberto Speranzon,et al.  Hierarchical Multi-objective planning: From mission specifications to contingency management , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[11]  Axel Schulte,et al.  Multilateral quality mission planning for solar-powered long-endurance UAV , 2017, 2017 IEEE Aerospace Conference.

[12]  Wen-di Wu,et al.  Multi-UAV Adaptive Path Planning in Complex Environment Based on Behavior Tree , 2021 .

[13]  Bruce T Clough,et al.  Metrics, Schmetrics! How The Heck Do You Determine A UAV's Autonomy Anyway , 2002 .

[14]  Florian-Michael Adolf,et al.  A Sequence Control System for Onboard Mission Management of an Unmanned Helicopter , 2007 .

[15]  Joonhyuk Kang,et al.  Protect Your Sky: A Survey of Counter Unmanned Aerial Vehicle Systems , 2020, IEEE Access.

[16]  François Michaud,et al.  Behavior-Based Systems , 2008, Springer Handbook of Robotics.

[17]  Fredrik Heintz,et al.  HDRC3 - A Distributed Hybrid Deliberative/Reactive Architecture for Unmanned Aircraft Systems , 2014 .

[18]  James A. Hendler,et al.  HTN Planning: Complexity and Expressivity , 1994, AAAI.

[19]  Farid Kendoul,et al.  Survey of advances in guidance, navigation, and control of unmanned rotorcraft systems , 2012, J. Field Robotics.

[20]  N. Mimmo,et al.  A control architecture for multiple drones operated via multimodal interaction in search & rescue mission , 2016, 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR).

[21]  Simon Colton,et al.  Evolving Behaviour Trees for the Commercial Game DEFCON , 2010, EvoApplications.