12 accepted papers
Collision avoidance is essential for robotic systems. This paper presents a method for designing directional projection control barrier functions (CBFs) based on differentiable optimization for second-order robotic systems. The approach reduces high-order CBFs to first-order ones and estimates colli…
Recent 3D Gaussian Splatting (3DGS) techniques for visual Simultaneous Localization and Mapping (SLAM) have significantly progressed in tracking and high-fidelity mapping. However, their sequential optimization framework and sensitivity to dynamic objects limit real-time performance and robustness i…
Nonlinear compliant actuators are being increasingly used in human-robot interaction scenarios due to their inherent flexibility. However, a limitation is that nonlinear hysteresis exists, which will degrade the force/torque tracking performance if the hysteresis is not modeled accurately. Moreover,
Lately, the practice of utilizing task-specific fine-tuning has been implemented to improve the performance of large language models (LLM) in subsequent tasks. Through the integration of diverse LLMs, the overall competency of LLMs is significantly boosted. Nevertheless, traditional ensemble methods…
The emergence of 3D Gaussian Splatting (3DGS) has recently ignited a renewed wave of research in dense visual SLAM. However, existing approaches encounter challenges, including sensitivity to artifacts and noise, suboptimal selection of training viewpoints, and the absence of global optimization. In
Gait phase detection is crucial to realize personalized assistive functions of lower limb exoskeletons. A common method in gait phase estimation is the adaptive oscillator, which performs well in periodic gaits. However, these types of methods fail in gait phase estimation under aperiodic gait cycle
Accurate object pose estimation is crucial for embodied intelligence tasks such as manipulation, grasping, and human-robot interaction. However, due to the inherent characteristics of articulated objects, such as kinematic constraints and self-occlusion, pose estimation for articulated objects has r…
Human life is populated with articulated objects. Pose estimation for category-level articulated objects is a significant challenge due to their inherent complexity and diverse kinematic structures. Current methods for this task usually meet the problems of insufficient consideration of kinematic co…
3D scene reconstruction from 2D images has been a long-standing task. Instead of estimating per-frame depth maps and fusing them in 3D, recent researches leverage the neural implicit surface as a global representation for 3D reconstruction. Equipped with data-driven pre-trained geometric cues, these…
Large Language Models (LLMs), such as LLaMA and T5, have shown exceptional performance across various tasks through fine-tuning. Although low-rank adaption (LoRA) has emerged to cheaply fine-tune these LLMs on downstream tasks, their deployment is still hindered by the vast model scale and computati…
One-shot Neural architecture search (One-shot NAS) has been proposed as a time-efficient approach to obtain optimal subnet architectures and weights under different complexity cases by training only once. However, the subnet performance obtained by weight sharing is often inferior to the performance…