Grasp detectionKey point estimationSqueeze-and-excitation blockAnchor-freeCornell Grasp DatasetGrasping is an important general ability for robots to work in aerospace and other fields. An accurate grasping detection result is the premise and key step for robots to complete grasping. To reduce the ...
A novel robotic grasp detection method based on region proposal networks The well-known Cornell grasp dataset and Jacquard dataset are used to test the performance of the proposed method. Experimental results show that the ... Y Song,L Gao,X Li,... - Robotics and Computer-Integrated Manufactur...
A Real-time Robotic Grasp Approach with Oriented Anchor Box 该论文的主要思想为:Grasp detection network with oriented anchor boxes as detection priors. 即使用Orientation Anchor Box Mechanism 来回归抓取角度。 在每个cell设置一些有方向的先验矩形框来作为最终抓取的参考。(prior boxes) 本文的目标是修正和区...
a robotic grasp detection algorithm named ROI-GD is proposed to provide a feasible solution to this problem based on Region of Interest (ROI), which is the region proposal
To train the network, we contribute a much bigger multi-object grasp dataset than Cornell Grasp Dataset, which is based on Visual Manipulation Relationship Dataset. Experimental results demonstrate that our algorithm achieves 24.9% miss rate at 1FPPI and 68.2% mAP with grasp on our dataset. ...
The well-known Cornell grasp dataset and Jacquard dataset are used to test the performance of the proposed method. Experimental results show that the proposed method can achieve higher grasp detection accuracy compared with other methods in the literature....
If you use our method or dataset extension for your research, please cite: @InProceedings{ainetter2021end,title={End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB},author={Ainetter, Stefan and Fraundorfer, Friedrich},booktitle={IEEE Internation...
Robotic grasp detection lags far behind human performance. We focus on the problem of ?nding a good grasp given an RGB-D view of the object. We evaluate on the Cornell Grasp Detection Dataset, an extensive dataset with numerous objects and ground-truth labelled grasps (see Figure 1). ...
gg = self.collision_detection(gg, np.array(cloud.points)) if show: self.vis_grasps(gg, cloud) return gg, cloud else: return gg,cloud if __name__=='__main__': grasper=Grasper() gg,cloud=grasper.demo(inputpic=True,color=1,depth=1) ...
...Chu等人和Zhou等人 还探讨了在现实世界的多物体场景中训练的Cornell Grasp Dataset深度抓取检测网络的性能,物体之间没有重叠。...度量标准 我们的算法侧重于检测对象重叠场景中的目标和掌握。因此,仅评估Cornell Grasp Dataset等检测结果的准确性是不够的。