The recent developments in robotic manipulation and teleoperation have shown a significant shift towards enhancing efficiency, adaptability, and robustness in various applications. Researchers are increasingly focusing on integrating advanced control strategies, such as impact-aware control and bilateral control-based imitation learning, to improve the performance of robotic systems in complex tasks. These innovations aim to leverage both position and force information, enabling robots to handle a wider range of objects and environments with greater precision and flexibility. Additionally, the use of digital twins and hybrid intelligence in surgical robotics is paving the way for more autonomous and reliable telesurgical procedures, even under challenging communication conditions. The field is also witnessing advancements in bimanual dexterity and asymmetric learning frameworks, which promise to enhance the versatility and efficiency of multi-arm robotic systems. These developments collectively underscore a trend towards more intelligent, adaptable, and human-like robotic systems that can operate in diverse and dynamic real-world scenarios.
Noteworthy papers include:
- 'Impact-Aware Control using Time-Invariant Reference Spreading' for its innovative use of nonsmooth physics engines and interim-impact control modes.
- 'ALPHA-$\alpha$ and Bi-ACT Are All You Need' for its introduction of low-cost, adaptable bimanual robots that leverage both position and force information.
- 'Robotic transcatheter tricuspid valve replacement with hybrid enhanced intelligence' for its comprehensive solution integrating passive stabilizers, robotic drives, and hybrid intelligence for autonomous surgical procedures.
