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Dominguez, D. C., Iannotta, M., Stork, J. A., Schaffernicht, E. & Stoyanov, T. (2022). A Stack-of-Tasks Approach Combined With Behavior Trees: A New Framework for Robot Control. IEEE Robotics and Automation Letters, 7(4), 12110-12117
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2022 (engelsk)Inngår i: IEEE Robotics and Automation Letters, E-ISSN 2377-3766, Vol. 7, nr 4, s. 12110-12117Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Stack-of-Tasks (SoT) control allows a robot to simultaneously fulfill a number of prioritized goals formulated in terms of (in)equality constraints in error space. Since this approach solves a sequence of Quadratic Programs (QP) at each time-step, without taking into account any temporal state evolution, it is suitable for dealing with local disturbances. However, its limitation lies in the handling of situations that require non-quadratic objectives to achieve a specific goal, as well as situations where countering the control disturbance would require a locally suboptimal action. Recent works address this shortcoming by exploiting Finite State Machines (FSMs) to compose the tasks in such a way that the robot does not get stuck in local minima. Nevertheless, the intrinsic trade-off between reactivity and modularity that characterizes FSMs makes them impractical for defining reactive behaviors in dynamic environments. In this letter, we combine the SoT control strategy with Behavior Trees (BTs), a task switching structure that addresses some of the limitations of the FSMs in terms of reactivity, modularity and re-usability. Experimental results on a Franka Emika Panda 7-DOF manipulator show the robustness of our framework, that allows the robot to benefit from the reactivity of both SoT and BTs.

sted, utgiver, år, opplag, sider
IEEE Press, 2022
Emneord
Behavior-based systems, control architectures and programming
HSV kategori
Identifikatorer
urn:nbn:se:oru:diva-101946 (URN)10.1109/LRA.2022.3211481 (DOI)000868319800006 ()
Forskningsfinansiär
Knut and Alice Wallenberg Foundation
Merknad

Funding agencies:

Industrial Graduate School Collaborative AI & Robotics (CoAIRob)

General Electric Dnr:20190128

Tilgjengelig fra: 2022-10-27 Laget: 2022-10-27 Sist oppdatert: 2024-01-17bibliografisk kontrollert
Iannotta, M., Dominguez, D. C., Stork, J. A., Schaffernicht, E. & Stoyanov, T. (2022). Heterogeneous Full-body Control of a Mobile Manipulator with Behavior Trees. In: IROS 2022 Workshop on Mobile Manipulation and Embodied Intelligence (MOMA): Challenges and  Opportunities: . Paper presented at International Conference on Intelligent Robots and Systems (IROS 2022), Kyoto, Japan, October 23-27, 2022.
Åpne denne publikasjonen i ny fane eller vindu >>Heterogeneous Full-body Control of a Mobile Manipulator with Behavior Trees
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2022 (engelsk)Inngår i: IROS 2022 Workshop on Mobile Manipulation and Embodied Intelligence (MOMA): Challenges and  Opportunities, 2022Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Integrating the heterogeneous controllers of a complex mechanical system, such as a mobile manipulator, within the same structure and in a modular way is still challenging. In this work we extend our framework based on Behavior Trees for the control of a redundant mechanical system to the problem of commanding more complex systems that involve multiple low-level controllers. This allows the integrated systems to achieve non-trivial goals that require coordination among the sub-systems.

HSV kategori
Forskningsprogram
Datavetenskap
Identifikatorer
urn:nbn:se:oru:diva-102984 (URN)10.48550/arXiv.2210.08600 (DOI)
Konferanse
International Conference on Intelligent Robots and Systems (IROS 2022), Kyoto, Japan, October 23-27, 2022
Forskningsfinansiär
Knowledge Foundation
Tilgjengelig fra: 2023-01-09 Laget: 2023-01-09 Sist oppdatert: 2024-01-03bibliografisk kontrollert
Organisasjoner
Identifikatorer
ORCID-id: ORCID iD iconorcid.org/0000-0002-2142-6516