publications

2026

1. ICRA2026

   Distributed Virtual Model Control for Scalable Human-Robot Interaction in Shared Workspace

   Zhang, Yi, Faris, Omar, Sirithunge, Chapa, Chu, Kai-Fung, Iida, Fumiya, and Forni, Fulvio

   In IEEE International Conference on Robotics and Automation 2026

   Abs arXiv HTML

   We present a decentralized, agent agnostic, and safety-aware control framework for human–robot collaboration based on Virtual Model Control (VMC). In our approach, both humans and robots are embedded in the same virtualcomponent-shaped workspace, where motion is the result of the interaction with virtual springs and dampers rather than explicit trajectory planning. A decentralized, force-based stall detector identifies deadlocks, which are resolved through negotiation. This reduces the probability of robots getting stuck in the block placement task from up to 61.2% to zero in our experiments. The framework scales without structural changes thanks to the distributed implementation: in experiments we demonstrate safe collaboration with up to two robots and two humans, and in simulation up to four robots, maintaining inter-agent separation at around 20 cm. Results show that the method shapes robot behavior intuitively by adjusting control parameters and achieves deadlock-free operation across team sizes in all tested scenarios.

2. under review

   Passive iFIR filters for data-driven velocity control in robotics

   Zhang, Yi, Wang, Zixing, and Forni, Fulvio

   Under review for RA-L 2026

   Abs HTML

   We present a passive, data-driven velocity control method for nonlinear robotic manipulators that achieves better tracking performance than optimized PID with comparable design complexity. Using only three minutes of probing data, a VRFT-based design identifies passive iFIR controllers that (i) preserve closed-loop stability via passivity constraints and (ii) outperform a VRFT-tuned PID baseline on the Franka Research 3 robot in both joint-space and Cartesian-space velocity control, achieving up to a 74.5% reduction in tracking error for the Cartesian velocity tracking experiment with the most demanding reference model. When the robot endeffector dynamics change, the controller can be re-learned from new data, regaining nominal performance. This study bridges learning-based control and stability-guaranteed design: passive iFIR learns from data while retaining passivity-based stability guarantees, unlike many learning-based approaches.

2025

1. EJC2025

   Dissipative iFIR filters for data-driven design

   Wang, Zixing,  Zhang, Yi, and Forni, Fulvio

   European Journal of Control 2025

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   We tackle the problem of providing closed-loop stability guarantees with a scalable data-driven design. We combine virtual reference feedback tuning with dissipativity constraints on the controller for closed-loop stability. The constraints are formulated as a set of linear inequalities in the frequency domain. This leads to a convex problem that is scalable with respect to the length of the data and the complexity of the controller. An extension of virtual reference feedback tuning to include disturbance dynamics is also discussed. The proposed data-driven control design is illustrated by a soft gripper impedance control example.

2. under review

   Periodic robust robotic rock chop via virtual model control

   Zhang, Yi, Iida, Fumiya, and Forni, Fulvio

   Under review for IJRR 2025

   Abs arXiv HTML

   Robotic cutting is a challenging contact-rich manipulation task where the robot must simultaneously negotiate unknown object mechanics, large contact forces, and precise motion requirements. We introduce a new active virtual-model control scheme that enables knife rocking motion for robot manipulators, without pre-planned trajectories or precise information of the environment. Motion is generated and controlled through switching virtual coupling with virtual mechanisms, given by virtual springs, dampers, and masses arranged in a suitable way. Through analysis and experiments, we demonstrate that the controlled robot behavior settles into a periodic motion. Experiments with a Franka manipulator demonstrate robust cuts with five different vegetables, and sub-millimeter slice accuracy from 1 mm to 6 mm at nearly one cut per second. The same controller survives changes in knife shape and cutting board height, and adaptation to a different humanoid manipulator, demonstrating robustness and platform independence.

2024

1. IROS2024

   Virtual Model Control for Compliant Reaching under Uncertainties

   Zhang, Yi, Larby, Daniel, Iida, Fumiya, and Forni, Fulvio

   In IEEE/RSJ International Conference on Intelligent Robots and Systems 2024

   Abs HTML

   Virtual Model Control (VMC) is an approach to design a controller for force-controlled robots in complex uncertain environments. While this method was primarily investigated for legged robot locomotion in the past, it can be more generally applicable to other types of robotic systems. This paper investigates the VMC framework for reaching tasks in a force-controlled robotic arm. We propose six different approaches to designing virtual models in order to achieve reaching tasks in environments with obstacles and uncertainties. A force-controlled 8 degree-of-freedom humanoid robot was used to validate the proposed approach in the real world. We conducted three experiments to test the performance of VMC controllers in terms of predictability, sensitivity to external force, and adaptability against known and unknown obstacles. Experimental analyses show that, even though the proposed approach needs to sacrifice accuracy and trajectory optimality, it enables us to design complex reaching motions under uncertainties, in an intuitive and extendable manner.

2022

1. Osaka University

   柔軟触覚センサを搭載した物体搬送ロボット群：COOP-FLEETSの開発

   Zhang, Yi

   2022

   Abs

   本研究論文では，様々なサイズ，さらには関節を有する物体の協調搬送にどのようなマルチロボットシステムが必要なのか議論する．そのために，リーダ・フォロワ型を採用し，さらに人の協調搬送をヒントに，力覚情報を用いて搬送行動を制御する方法を提案する．これまでも力覚情報を利用した搬送行動は提案されているが，硬い力覚センサを採用しており，本研究では接触部に柔軟素材を用い，力覚情報を取得することで，搬送対象に無理な力をかけずに搬送できることがたいされる．また，従来の研究では搬送される物体として，剛体がほとんどであり，多関節物体物体に関する研究はまだ少ない．本論文では，3軸方向の力を物体との接触面において計測できる柔軟な接触センサを用いた協調搬送を提案した．また，移動ロボット上に装着した柔軟な接触センサにおいて，信頼性のある力覚情報を取得できることを確認した．さらに，剛体だけでなく，剛体を柔軟な棒でつなげた多関節物体の運搬における協調搬送システムの妥当性を検証した．最後に，柔軟な表面をもつ人体模型の搬送を試み，人間のような柔軟かつ多関節な物体を群ロボットで，不整地の多い災害現場において搬送するにあたって，システムやロボットの構造に求められる改善を指摘した．

2. DARS2022

   A Decentralized Approach to Cooperative Object Transportation with Robots Equipped with Flexible Tactile Sensors

   Zhang, Yi, Sueoka, Yuichiro, Ishihara, Hisashi, Kawasetsu, Takumi, and Osuka, Koichi

   In 16th International Symposium on Distributed Autonomous Robotic Systems 2022

   Abs HTML

   Cooperative transportation of objects by a group of small mobile robots is expected to work in disaster sites. In this study, we aim to transport fragile objects including humans which may move during the transport, with as little burden as possible. We propose the adoption of a flexible tri-axis tactile sensor with thickness at the top of the robot on which the object is mounted for safe support and state monitoring. We improved the leader-follower based control by adding force feedback into the leader’s control law to prevent excessive force on the object, which is the disadvantage of the typical leader-follower method. We verified the robots can transport a rigid body gently with the proposed control law by converging their speeds to the same value in a dynamical simulation and actual experiments. Additionally, we found that multijoint objects also can be transported with the proposed method, whereas the stable support of the object by each robot is reserved for future works.

2021

1. RSJ2021

   A Decentralized Approach to Cooperative Object Transportation with Robots Equipped with Flexible Tactile Sensors

   Zhang, Yi, SUEOKA, Yuichiro, ISHIHARA, Hisashi, KAWASETSU, Takumi, and OSUKA, Koichi

   2021