@文心快码pointnetgpd: detecting grasp configurations from point sets 文心快码 PointNetGPD是一种轻量级的端到端抓取评估模型,旨在直接从点云中定位机器人的抓取配置。以下是关于PointNetGPD模型及其应用的详细回答: PointNetGPD模型的理解: PointNetGPD通过直接处理位于抓取器内的3D点云来进行抓取评估,解决了从点云...
Compared to recent grasp evaluation metrics that are based on handcrafted depth features and a convolutional neural network (CNN), our proposed PointNetGPD is lightweight and can directly process the 3D point cloud that locates within the gripper for grasp evaluation. Taking the raw point cloud ...
In this paper, we propose an end-to-end grasp evaluation model to address the challenging problem of localizing robot grasp configurations directly from the point cloud. Compared to recent grasp evaluation metrics that are based on handcrafted depth features and a convolutional neural network (CNN)...
To reduce data collection time for deep learning of robust robotic grasp plans, we explore training from a synthetic dataset of 6.7 million point clouds, grasps, and robust analytic grasp metrics generated from thousands of 3D models from Dex-Net 1.0 in randomized poses on a table. We use the...
@inproceedings{liang2019pointnetgpd, title={{PointNetGPD}: Detecting Grasp Configurations from Point Sets}, author={Liang, Hongzhuo and Ma, Xiaojian and Li, Shuang and G{\"o}rner, Michael and Tang, Song and Fang, Bin and Sun, Fuchun and Zhang, Jianwei}, booktitle={IEEE International Con...
@inproceedings{liang2019pointnetgpd, title={{PointNetGPD}: Detecting Grasp Configurations from Point Sets}, author={Liang, Hongzhuo and Ma, Xiaojian and Li, Shuang and G{\"o}rner, Michael and Tang, Song and Fang, Bin and Sun, Fuchun and Zhang, Jianwei}, booktitle={IEEE International Con...