11 accepted papers
Accurate 3D reconstruction in surgical scenarios is essential for visualizing dynamic tissues with complex anatomical geometries. While 3D Gaussian Splatting (3D-GS) has been explored as an efficient approach to scene modeling, occlusion-induced voids and suboptimal detail optimization have limited
Telemedicine is promising in digital healthcare management, such as supporting the coronavirus disease 2019 (COVID-19) pandemic. Three-dimensional (3D) ultrasound reconstruction and new view image synthesis, which can assist in diagnosis and reexamine, have significant potential in teleultrasound, e
The multi-agent pickup and delivery problem is central to coordinating multiple agents in real-world applications such as warehouse automation, urban logistics, and robotic delivery networks, where efficient task assignment and pathfinding are vital for maximizing production efficiency. However, exi
Accurately modeling the interactions between deformable linear objects (DLOs) and their environments is crucial for active deformation control by robot manipulators. Graph Neural Networks (GNNs) have shown immense potential in the particle-based dynamics of DLOs. However, most existing studies propa
2D-to-3D human pose lifting is fundamental for 3D human pose estimation (HPE), for which graph convolutional networks (GCNs) have proven inherently suitable for modeling the human skeletal topology. However, the current GCN-based 3D HPE methods update the node features by aggregating their neighbors…
Continuum manipulators with structural compliance can be utilized to steer a laser beam in constrained environments. However, the flexibility and nonlinear characteristics of continuum manipulators bring difficulty in precision manipulation. This study proposes a model-free control approach with vis
Knowledge representation learning (KRL) has been used in plenty of knowledge-driven tasks. Despite fruitfully progress, existing methods still suffer from the immaturity on tackling potentially-imperfect knowledge graphs and highly-imbalanced positive-negative instances during training, both of whic…
Inherent compliance plays an enabling role in soft robots, which rely on it to mechanically conform to the environment. However, it also limits the payload of the robots. Various variable stiffness approaches have been adopted to limit compliance and provide structural stability, but most of them ca…
Advanced motor skills are essential for robots to physically coexist with humans. Much research on robot dynamics and control has achieved success on hyper robot motor capabilities, but mostly through heavily case-specific engineering. Meanwhile, in terms of robot acquiring skills in a ubiquitous ma…
Flexible continuum robots have exhibited unique advantages in working in an unstructured environment. Many applications require robots to actively control the deformation of soft objects, such as soft tissues in surgery. Thus, this study presents a robust model-predictive deformation control of a so…
Electromagnetically actuated microparticles can be widely applied in the field of biomedicine, for its advantages of minimally invasive feature and approachability to complex microenvironments. In this paper, we propose a robust feedback control approach for precise 3D manipulation of a microparticl…