13 accepted papers
Comprehensively interpreting human behavior is a core challenge in human-aware artificial intelligence. However, prior works typically focused on body behavior, neglecting the crucial role of eye gaze and its synergy with body motion. We present GazeInterpreter - a novel large language model-based (
A compact reconfigurable terrestrial-aerial robot that is capable of executing seamless transitions between three motion modes—rolling, crawling, and flying—via foldable mechanisms is presented in this letter. The rolling and crawling modes are facilitated by two passive gear-driven, foldable wheel-
Robotic tasks often require multiple manipulators to enhance task efficiency and speed, but this increases complexity in terms of collaboration, collision avoidance, and the expanded state-action space. To address these challenges, we propose a multi-level approach combining Reinforcement Learning (
The task of one-shot face video re-enactment aims at generating target video of faces with the same identity of one source frame and facial deformation of the driving video. To achieve high quality generation, it is essential to precisely disentangle identity-related and identity-independent charac…
Naturalistic driving action recognition is essential for vehicle cabin monitoring systems. However, the complexity of real-world backgrounds presents significant challenges for this task, and previous approaches have struggled with practical implementation due to their limited ability to observe sub…
Robot-assisted surgery has profoundly influenced current forms of minimally invasive surgery. However, in transurethral urological surgical robots, they need to work in a liquid environment. This causes vaporization of the liquid when shearing and heating is performed, resulting in bubble atomizatio
Lane detection is a critical task in autonomous driving, which requires accurately predicting the complex topology of lanes in various scenarios. While previous methods of lane detection have shown success, challenges still exist, especially in scenarios where lane markings are absent. In this paper…
Modern manufacturing requires effective integration of production control and maintenance scheduling to improve productivity and quality. However, there have been few studies on this integrated control due to a lack of a comprehensive manufacturing system model. In response to this challenge, this l
The paradigm of training models on massive data without label through self-supervised learning (SSL) and finetuning on many downstream tasks has become a trend recently. However, due to the high training costs and the unconsciousness of downstream usages, most self-supervised learning methods lack t…
This letter aims at modeling and real-time control of a flexible manufacturing system (FMS) that is operated by multi-skilled mobile robots. By introducing the idea of a unique ideal clean configuration and the effective disruption event, the concepts of Opportunity Window (OW) and Permanent Product
The performance of a smart manufacturing system is affected by not only the constituent processes but also their system-level interactions. However, in most current studies, indi- vidual process modeling and system-level performance evaluation are independent. This can substantially impact productio
Real time production performance evaluation plays a vital role in diagnosing manufacturing system health status and achieving productivity improvements. However, most existing studies on system performance evaluation are based on steady state analysis and focused on the production system with fixed
For a multi-gantry production system, in which several gantries move among the machines and load/unload parts, the assignment of gantries directly impacts the system performance. Gantry scheduling problem is extremely important, involving when and where the gantries are assigned to the machines. Thi