A Cooperation Control Framework Based on Admittance Control and Time-Varying Passive Velocity Field Control for Human-Robot Co-Carrying Tasks

Human–robot co-carrying tasks reveal their poten- tial in both industrial and everyday applications by leveraging the strengths of both parties. Effective control of robots in these tasks requires managing the energy level in the closed-loop systems to prevent potential dangers while also minimizing motion errors to complete the shared tasks. The collaborative tasks pose numerous challenges due to varied human intentions in adapting to workspace characteristics, leading to human–robot conflicts. In this paper, we develop a cooperation control framework for human–robot co-carrying tasks constructed by utilizing reference generator and low-level controller to aim to achieve safe inter- action and synchronized human–robot movement. Firstly, the human motion predictions are corrected in the event of prediction errors based on the conflicts measured by the interaction forces through admittance control, thereby mitigating conflict levels. Low-level controller using an energy-compensation passive veloc- ity field control approach allows encoding the corrected motion to produce control torques for the robot. In this manner, the closed- loop robotic system is passive when the energy level exceeds the predetermined threshold, and otherwise. Furthermore, the proposed control approach ensures that the system’s kinetic energy is compensated within a finite time interval. The passivity, stability, convergence rate of energy, and power flow regulation are analyzed from theoretical viewpoints. Human-in-the-loop experiments involving 18 participants have demonstrated that the proposed method significantly enhances task performance and reduces human workload, as evidenced by both objective metrics and subjective evaluations, with improvements confirmed by statistical tests (p < 0.05) relative to baseline methods. Note to Practitioners—This paper is motivated by the challenge of developing a cooperation control framework for human–robot co-carrying tasks in achieving safe interaction and completing the shared tasks, especially in scenarios where human intentions vary due to changes in the environment or task demands. To this end, a reference motion generator, using motion prediction model and admittance model, is first applied to provide human motion intention for the robot in real-time. Subsequently, an energy- compensation passive velocity field control approach is proposed, which utilizes the output of the motion generator to regulate robot behaviors during physical interaction with the human. In this manner, the proposed approach enables the regulation of both the energy level and power flow within the collaborative system, while guiding the robot motion to converge toward the human intention, thereby ensuring safe and synchronized human–robot The authors are with the Graduate School of Science and Technol- ogy, Nara Institute of Science and Technology, Ikoma, Nara, 630-0192, Japan (e-mail: van trong.dang.ve6@naist.ac.jp, kotake.hiroki.kf8@is.naist.jp, honji.sumitaka@naist.ac.jp, and t.wada@is.naist.jp). Manuscript received May 31, 2025; revised September 16, 2025; accepted October 28, 2025. movement. Through theoretical analysis, the proposed method provides well-defined conditions of control parameters, allowing practitioners to intuitively fine-tune the robot system for specific engineering applications. Furthermore, the proposed method can be extended to other human–robot collaboration tasks, such as object handover, collaborative assembly, and co-sawing, owing to their common features and requirements in physical interaction with the human.