Execution control is a critical task of robot architectures which has a deep impact on the quality of the final system. In this study, we describe a general method for execution control, which is a part of the Aerostack software framework for aerial robotics, and present technical challenges for execution control and design decisions to develop the method. The proposed method has an original design combining a distributed approach for execution control of behaviors (such as situation checking and performance monitoring) and centralizes coordination to ensure consistency of the concurrent execution. We conduct experiments to evaluate the method. The experimental results show that the method is general and usable with acceptable development efforts to efficiently work on different types of aerial missions. The method is supported by standards based on a robot operating system (ROS) contributing to its general use, and an open-source project is integrated in the Aerostack framework. Therefore, its technical details are fully accessible to developers and freely available to be used in the development of new aerial robotic systems.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Alami R, Chatila R, Fleury S, et al., 1998. An architecture for autonomy. Int J Robot Res, 17(4):315–337. https://doi.org/10.1177/027836499801700402
Allgeuer P, Behnke S, 2013. Hierarchical and state-based architectures for robot behavior planning and control. Proc 8th Workshop on Humanoid Soccer Robots and 13th IEEE-RAS Int Conf on Humanoid Robots, p.1–6.
Arkin RC, 1998. Behavior-Based Robotics (Intelligent Robotics and Autonomous Agents). MIT Press, Cambridge, USA.
Bavle H, Sanchez-Lopez JL, de la Puente P, et al., 2018. Fast and robust flight altitude estimation of multirotor UAVs in dynamic unstructured environments using 3D point cloud sensors. Aerospace, 5(3):94. https://doi.org/10.3390/aerospace5030094
Bonasso RP, Firby RJ, Gat E, et al., 1997. Experiences with an architecture for intelligent, reactive agents. J Exp Theor Artif Intell, 9(2-3):237–256. https://doi.org/10.1080/095281397147103
Brooks R, 1986. A robust layered control system for a mobile robot. IEEE J Rob Autom, 2(1), 14–23.
Firby RJ, 1989. Adaptive Execution in Complex Dynamic Worlds. PhD Thesis, Yale University, New Haven, USA.
Furrer F, Burri M, Achtelik M, et al., 2016. RotorS—a modular gazebo MAV simulator framework. In: Koubaa A (Ed.), Robot Operating System (ROS). Springer, Cham, p.595–625. https://doi.org/10.1007/978-3-319-26054-9_23
Gat E, 1992. Integrating planning and reacting in a heterogeneous asynchronous architecture for controlling realworld mobile robots. Proc 10th National Conf on Artificial Intelligence, p.809–815.
Gat E, 1996. ESL: a language for supporting robust plan execution in embedded autonomous agents. IEEE Aerospace Conf, p.319–324. https://doi.org/10.1109/AERO.1997.574422
Gat E, 1998. On three-layer architectures. In: Kortenkamp D, Bonnasso RP, Murphy R (Eds.), Artificial Intelligence and Mobile Robots. MIT Press, Cambridge, USA, p.195–210.
Ingrand F, Py F, 2002. An execution control system for autonomous robots. Proc IEEE Int Conf on Robotics and Automation, p.1333–1338. https://doi.org/10.1109/ROBOT.2002.1014728
Kortenkamp D, Simmons R, Brugali D, 2008. Robotic systems architectures and programming. In: Siciliano B, Khatib O (Eds.), Springer Handbook of Robotics. Springer Berlin Heidelberg, p.187–206. https://doi.org/10.1007/978-3-540-30301-5_9
Mittal S, Frayman F, 1989. Towards a generic model of configuration tasks. 11th Int Joint Conf on Artificial Intelligence, p.1395–1401.
Molina M, Suarez-Fernandez RA, Sampedro C, et al., 2017. TML: a language to specify aerial robotic missions for the framework Aerostack. Int J Intell Comput Cybern, 10(4):491–512. https://doi.org/10.1108/IJICC-03-2017-0025
Molina M, Frau P, Maravall D, 2018. A collaborative approach for surface inspection using aerial robots and computer vision. Sensors, 18(3):893. https://doi.org/10.3390/s18030893
Rodriguez-Ramos A, Sampedro C, Bavle H, et al., 2017. Towards fully autonomous landing on moving platforms for rotary unmanned aerial vehicles. Int Conf on Unmanned Aircraft Systems, p.170–178. https://doi.org/10.1109/ICUAS.2017.7991438
Rothenstein AL, 2002. A Mission Plan Specification Language for Behaviour-Based Robots. MS Thesis, University of Toronto, Toronto, Canada.
Rutten E, 2001. A framework for using discrete control synthesis in safe robotic programming and teleoperation. Proc IEEE Int Conf on Robotics and Automation, p.4104–4109. https://doi.org/10.1109/ROBOT.2001.933259
Sampedro C, Bavle H, Sanchez-Lopez JL, et al., 2016. A flexible and dynamic mission planning architecture for UAV swarm coordination. Int Conf on Unmanned Aircraft Systems, p.355–363. https://doi.org/10.1109/ICUAS.2016.7502669
Sampedro C, Rodriguez-Ramos A, Bavle H, et al., 2018. A fully-autonomous aerial robot for search and rescue applications in indoor environments using learning-based techniques. J Intell Robot Syst, p.1–27. https://doi.org/10.1007/s10846-018-0898-1
Sanchez-Lopez JL, Molina M, Bavle H, et al., 2017. A multilayered component-based approach for the development of aerial robotic systems: the aerostack framework. J Intell Robot Syst, 88(2-4):683–709. https://doi.org/10.1007/s10846-017-0551-4
Suárez Fernández RA, Sanchez-Lopez JL, Sampedro C, et al., 2016. Natural user interfaces for human-drone multimodal interaction. Int Conf on Unmanned Aircraft Systems, p.1013–1022. https://doi.org/10.1109/ICUAS.2016.7502665
Verma V, Estlin T, Jónsson A, et al., 2005. Plan execution interchange language (PLEXIL) for executable plans and command sequences. Int Symp on Artificial Intelligence, Robotics and Automation in Space, p.1–8.
Project supported by the European Union’s Horizon 2020 Research and Innovation Program under the Project ROSIN (No. 732287)
About this article
Cite this article
Molina, M., Camporredondo, A., Bavle, H. et al. An execution control method for the Aerostack aerial robotics framework. Frontiers Inf Technol Electronic Eng 20, 60–75 (2019). https://doi.org/10.1631/FITEE.1800552
- Aerial robotics
- Control architecture
- Behavior-based control
- Executive system