无需力传感器的遥操作框架，让操作者在重载机械臂上获得沉浸感与高透明度控制。

In human-in-the-loop systems such as teleoperation, especially those involving heavy-duty manipulators, achieving high task performance requires both robust control and strong human engagement. This paper presents a bilateral teleoperation framework for beyond-human-scale robotic systems that enhances the transparency and the operator's sense of embodiment (SoE), specifically, the senses of agency and self-location, through an immersive virtual reality interface and distributed haptic feedback. To support this embodiment and establish high level of motion and force transparency, we develop a force-sensorless, robust control architecture that tackles input nonlinearities, master-surrogate asymmetries, unknown uncertainties, and arbitrary time delays. A human-robot augmented dynamic model is integrated into the control loop to enhance human-adaptability of the controller. Theoretical analysis confirms semi-global uniform ultimate boundedness of the closed-loop system, guaranteeing the robustness to the real-world uncertainties. Extensive real-world experiments demonstrate high accuracy tracking under up to 1:13 motion scaling and 1:1000 force scaling, showcasing the significance of the results. Additionally, the stability-transparency tradeoff for motion tracking and force reflection and tracking is established up to 150 ms of one-way fix and time-varying communication delays. The results of user study with 10 participants (9 male and 1 female) demonstrate that the system can imply a good level of SoE (76.4%), at the same time is very user friendly with no gender limitation. These results are significant given the scale and weight of the heavy-duty manipulators.