7 accepted papers
Achieving reliable object manipulation while traversing complex terrains is the missing link between agile quadruped locomotion and practical autonomy. Specifically, using traditional end-to-end reinforcement learning (RL) for dynamic ball manipulation in rugged environments presents two key challen
In real-world scenarios, environment changes caused by human or agent activities make it extremely challenging for robots to perform various long-term tasks. Recent works typically struggle to effectively understand and adapt to dynamic environments due to the inability to update their environment r
Many robotic manipulation tasks require sensing and responding to force signals such as torque to assess whether the task has been successfully completed and to enable closed-loop control. However, current Vision-Language-Action (VLA) models lack the ability to integrate such subtle physical feedbac…
Predicting gaze point on mobile devices without calibration in unconstrained environments has great significance on human computer interaction. Appearance-based gaze estimation methods have been improved due to the recent advance in convolutional neural network (CNN) models and the availability of l…
Evasion attack in multi-label learning systems is an interesting, widely witnessed, yet rarely explored research topic. Characterizing the crucial factors determining the attackability of the multi-label adversarial threat is the key to interpret the origin of the adversarial vulnerability and to un…
Series elastic actuators (SEAs) are growingly important in physical human-robot interaction (HRI) due to their inherent safety and compliance. Cable-driven SEAs also allow flexible installation and remote torque transmission, etc. However, there are still challenges for the impedance control of cabl…