Vibration Suppression in Collaborative Flexible Payload Manipulation Using Passive Force Control
Authors: Alaa Abderrahim, Antonio Rosales, Ferdinando Milella, Markku Suomalainen, Shuai Li
Organizations: VTT Technical Research Centre of Finland Ltd, Oulu, Finland · RP Technical University of Kaiserslautern, Germany · UK Atomic Energy Authority, Oxfordshire, England, United Kingdom · Faculty of Information Technology and Electrical Engineering, University of Oulu, Finland
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 demonstrate its effectiveness.
Figures & tables
Fig. 1: (a) Model simulation of the breeding blanket in the conceptual DEMOnstration power plant, and (b) its removal process.
Fig. 2: Two-robot collaborative system
Fig. 3: Block diagram of collaborative scheme. x˙d∗ is the leader’s velocity command, x˙2 is the follower’s velocity command, and the estimated interaction force is Fest
Fig. 4: Mass-spring damper system representation of the follower-payload system with force applied from the leader robot
Fig. 5: Block diagram of input-shaping.
Fig. 6: Experimental setup
Case
Control type
Highest amp. [mm]
Settling time [s]
Amp. red. [%]
Simulation
None
28.8
4.65
–
Admittance
15.6
3.57
45.8
Input-shaping
16.5
3.57
42.7
Adm. + IS
5.8
1.26
79.9
Experiment
None
26.3
2.38
–
Admittance
11.4
1.37
56.7
TABLE I: Comparison of control strategies in simulation and experiment.
Fig. 7: Simulation results of the vibrations of the flexible beam over time with different control methods
Fig. 8: Experimental results of the vibrations of the flexible beam over time with different control methods
Flexible robotic manipulators (FRMs) offer advantages in lightweight design and large workspace, but their structural flexibility induces vibrations, accelerates fatigue, degrades tracking performance, and limits operational speed. These challenges are further amplified in multi-link serial manipulators, where increased overall length leads to greater structural flexibility. This article presents a backstepping output-feedback framework for fast vibration suppression and tip tracking of an n-degree-of-freedom serial flexible manipulator robot (nDSFMR), with a DeepONet-based approximation for practical deployment. Each link-joint is modeled as a Timoshenko beam coupled with an ODE and transformed into a canonical hyperbolic PDE with boundary dynamics. A backstepping-based boundary controller at the joint is developed to equivalently inject distributed damping along the beam, enabling rapid vibration suppression and trajectory tracking, only using available boundary measurements. To enable real-time implementation and scalability, a DeepONet neural operator is introduced to approximate the backstepping kernels, significantly reducing computational cost and facilitating fast controller updates under varying operating conditions. Experiments on a two-link flexible manipulator demonstrate faster vibration suppression and convergence of the end-effector to the desired trajectory, compared with a linear quadratic regulator (LQR) with feedforward control.
Chengyi Wang, Yilong Huang, Ji Wang
School of Aerospace Engineering, Xiamen University, Xiamen 361102, P. R. China
Cooperative payload transportation using multiple Unmanned Aerial Vehicles (UAVs) poses challenges in stability, coordination, and robustness, especially under external disturbances and unmodeled dynamics. This work proposes a dual-UAV payload transportation framework supported by a compact, custom-designed force sensor measuring the interaction force at the UAV cable anchor point. The sensor design and mathematical model are presented, and its performance is characterized through static and dynamic tests evaluating linearity, hysteresis, repeatability, and crossload. The control architecture follows a cascade structure: fast inner loops handle vehicle stabilization, while outer loops are designed to compensate for the measured forces. The approach is validated through simulations and indoor experiments under position uncertainty. Payload-drop and constrained-space tests assess the proposed sensing and control architecture against literature-based distributed references, showing improved stabilization, coordination, and disturbance rejection. A video of the experiments is available at: https://youtu.be/rIw9-fvV8Qw.
Andrea Delbene, Giorgio Cannata, Giorgio Carlini +2
Department of Informatics, Bioengineering, Robotics and Systems Engineering, Università degli Studi di Genova, Via all’Opera Pia 13, 16145, Genoa, Italy
Unknown payloads can strongly affect compliant robotic manipulation, especially when the payload center of mass is not aligned with the tool center point. In this case, the payload generates an offset wrench at the robot wrist. During motion, this wrench is not only related to payload weight, but also to payload inertia. If it is not modeled, the compliant controller can interpret it as an external interaction wrench, which causes unintended compliant motion, larger tracking error, and reduced transport accuracy. This paper presents a wrench-aware admittance control framework for unknown-payload pick-and-place using a UR5e robot. The method uses force-torque measurements in two different roles. First, a three-axis translational excitation term is used to reduce payload-induced force effects during transport without making the robot excessively stiff. Second, after grasping, the controller first estimates payload mass for transport compensation and then estimates the payload CoM offset relative to the TCP using wrist force-torque measurements collected during the subsequent translational motion. This helps improve object placement and stacking behavior. Experimental results show improved transport and placement performance compared with uncorrected placement while preserving compliant motion.
Hossein Gholampour, Logan E. Beaver
Department of Mechanical & Aerospace Engineering, Old Dominion University, Norfolk, VA 23529, USA