Zobrazeno 1 - 10
of 2 368
pro vyhledávání: '"An, Haoying"'
Autor:
Allison, Christopher John, Zhou, Haoying, Munawar, Adnan, Kazanzides, Peter, Barragan, Juan Antonio
Interactive dynamic simulators are an accelerator for developing novel robotic control algorithms and complex systems involving humans and robots. In user training and synthetic data generation applications, a high-fidelity visualization of the simul
Externí odkaz:
http://arxiv.org/abs/2410.05095
Haptic feedback to the surgeon during robotic surgery would enable safer and more immersive surgeries but estimating tissue interaction forces at the tips of robotically controlled surgical instruments has proven challenging. Few existing surgical ro
Externí odkaz:
http://arxiv.org/abs/2409.19970
Cooperative localization and target tracking are essential for multi-robot systems to implement high-level tasks. To this end, we propose a distributed invariant Kalman filter based on covariance intersection for effective multi-robot pose estimation
Externí odkaz:
http://arxiv.org/abs/2409.09410
This paper presents a novel approach to distributed pose estimation in the multi-agent system based on an invariant Kalman filter with covariance intersection. Our method models uncertainties using Lie algebra and applies object-level observations wi
Externí odkaz:
http://arxiv.org/abs/2409.07933
Autor:
Lin, Fangzhou, Liu, Haotian, Zhou, Haoying, Hou, Songlin, Yamada, Kazunori D, Fischer, Gregory S., Li, Yanhua, Zhang, Haichong K., Zhang, Ziming
3D point clouds enhanced the robot's ability to perceive the geometrical information of the environments, making it possible for many downstream tasks such as grasp pose detection and scene understanding. The performance of these tasks, though, heavi
Externí odkaz:
http://arxiv.org/abs/2409.06171
Despite advancements in robotic-assisted surgery, automating complex tasks like suturing remain challenging due to the need for adaptability and precision. Learning-based approaches, particularly reinforcement learning (RL) and imitation learning (IL
Externí odkaz:
http://arxiv.org/abs/2406.13865
Publikováno v:
2024 IEEE International Conference on Robotics and Automation (ICRA)
Automation in surgical robotics has the potential to improve patient safety and surgical efficiency, but it is difficult to achieve due to the need for robust perception algorithms. In particular, 6D pose estimation of surgical instruments is critica
Externí odkaz:
http://arxiv.org/abs/2406.07328
Autor:
Zhou, Haoying, Jiang, Yiwei, Gao, Shang, Wang, Shiyue, Kazanzides, Peter, Fischer, Gregory S.
Publikováno v:
2024 International Symposium on Medical Robotics (ISMR) IEEE
In this work, we develop an open-source surgical simulation environment that includes a realistic model obtained by MRI-scanning a physical phantom, for the purpose of training and evaluating a Learning from Demonstration (LfD) algorithm for autonomo
Externí odkaz:
http://arxiv.org/abs/2403.00956
Autor:
Li, Xinghan, Li, Haoying, Zeng, Guangyang, Zeng, Qingcheng, Ren, Xiaoqiang, Yang, Chao, Wu, Junfeng
A filter for inertial-based odometry is a recursive method used to estimate the pose from measurements of ego-motion and relative pose. Currently, there is no known filter that guarantees the computation of a globally optimal solution for the non-lin
Externí odkaz:
http://arxiv.org/abs/2402.05003
Autor:
Yan, Shengjun, Mao, Wei, Sun, Wenjie, Li, Yueying, Sun, Haoying, Yang, Jiangfeng, Hao, Bo, Guo, Wei, Nian, Leyan, Gu, Zhengbin, Wang, Peng, Nie, Yuefeng
The observation of superconductivity in infinite-layer nickelates has attracted significant attention due to its potential as a new platform for exploring high $ \mathrm{\textit{T}}_{c} $ superconductivity. However, thus far, superconductivity has on
Externí odkaz:
http://arxiv.org/abs/2401.15980