5 accepted papers
Control barrier functions (CBFs) have proven to be effective for obstacle avoidance in robot teleoperation systems. However, for classical CBF, model uncertainties and external disturbances can significantly degrade the robustness of safety control. Moreover, the fixed safety boundary lacks adaptabi…
High-order control barrier functions (HOCBFs) that can achieve strict safety guarantees are widely used in robot safety control. However, robot obstacle avoidance in narrow environments with curved surfaces, as represented by aircraft blade detection, is still a challenge. Considering the narrow spa…
For direct teleoperation tasks, the follower robot accomplishes tasks by strictly executing the inputs from the operator. However, the operator's physiological tremor seriously reduces the smoothness of the trajectory, especially in tasks relying on operator’s experience such as gluing, while the ra
Existing models for diverse generative reasoning still struggle to generate multiple unique and plausible results. Through an in-depth examination, we argue that it is critical to leverage a mixture of experts as prefixes to enhance the diversity of generated results and make task-oriented adaptatio…
Automated Machine Learning (AutoML) is an active area on the design of deep neural networks for specific tasks and datasets. Given the complexity of discovering new network designs, methods for speeding up the search procedure are becoming important. This paper presents a so-called transferable Auto…