Abstract
In large and heavy structures, vibrations arise during motion, posing significant challenges for precise manipulation. To accomplish the desired motion, control algorithms must effectively suppress these structural vibrations. In cutting-edge projects, such as remote maintenance of future fusion energy reactors (tokamaks), the manipulation of this type of structure is defined as a crucial task. This paper presents a control strategy to suppress transverse vibrations in flexible payloads during motion using a collaborative payload manipulation approach. Two different industrial robot arms are arranged in a leader-follower configuration for the manipulation strategy. The leader robot guides the motion with shaped velocity commands, while the follower robot ensures compliance with the estimated external forces applied by the leader on the payload through an admittance controller. Unlike existing methods, the proposed approach enables collaborative manipulation of heavier and larger flexible objects, addressing additional challenges such as vibration suppression and heterogeneous robot specifications. The dynamics of the leader-follower-payload system are modeled using an equivalent mass-spring-damper model, and it is shown that, with appropriate admittance parameters, the total energy of the system is passively dissipated. A stability proof is also provided. Numerical simulations validate the proposed method, and experimental results (see online video [1] ) demonstrate its effectiveness.
| Original language | English |
|---|---|
| Title of host publication | 2026 European Control Conference (ECC) |
| Publisher | IEEE Institute of Electrical and Electronic Engineers |
| Pages | 176-181 |
| Number of pages | 6 |
| ISBN (Electronic) | 978-3-907144-13-8 |
| Publication status | Accepted/In press - 2026 |
| MoE publication type | A4 Article in a conference publication |
| Event | 2026 European Control Conference, ECC 2026 - Reykjavík, Iceland Duration: 7 Jul 2026 → 10 Jul 2026 |
Conference
| Conference | 2026 European Control Conference, ECC 2026 |
|---|---|
| Country/Territory | Iceland |
| City | Reykjavík |
| Period | 7/07/26 → 10/07/26 |
Funding
This project has received funding from Research Council of Finland project UNITE: Unifying and optimizing representations in robot learning. This work has been carried out within the framework of the EUROfusion Consortium, funded by the European Union via the Euratom Research and Training Programme (Grant Agreement No 101052200 EUROfusion).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 9 Industry, Innovation, and Infrastructure
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