8 May 2012 A layered control architecture for single-operator control of heterogeneous unmanned system teams
Author Affiliations +
Proceedings Volume 8387, Unmanned Systems Technology XIV; 838702 (2012); doi: 10.1117/12.919122
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States
The widespread adoption of aerial, ground and sea-borne unmanned systems (UMS) for national security applications provides many advantages; however, effectively controlling large numbers of UMS in complex environments with modest manpower is a significant challenge. A control architecture and associated control methods are under development to allow a single user to control a team of multiple heterogeneous UMS as they conduct multi-faceted (i.e. multi-objective) missions in real time. The control architecture is hierarchical, modular and layered and enables operator interaction at each layer, ensuring the human operator is in close control of the unmanned team at all times. The architecture and key data structures are introduced. Two approaches to distributed collaborative control of heterogeneous unmanned systems are described, including an extension of homogeneous swarm control and a novel application of distributed model predictive control. Initial results are presented, demonstrating heterogeneous UMS teams conducting collaborative missions. Future work will focus on interacting with dynamic targets, integrating alternative control layers, and enabling a deeper and more intimate level of real-time operator control.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stephen P. Buerger, Jason Neely, Charles Little, Wendy Amai, Rommy Joyce, Joshua A. Love, "A layered control architecture for single-operator control of heterogeneous unmanned system teams", Proc. SPIE 8387, Unmanned Systems Technology XIV, 838702 (8 May 2012); doi: 10.1117/12.919122; https://doi.org/10.1117/12.919122

Control systems


3D modeling

Unmanned systems

Data modeling

Optimization (mathematics)


Back to Top