在通用机器人研究领域中,grasp detection 任务要求能够在一堆杂乱的物体中识别从未遇到过的物体以及处理物体之间的堆叠问题。作者针对此项任务提出了Volumetric Grasping Network(VGN),以3D场景的Truncated Signed Distance Function(TSDF)表示作为输入,并能够对3D场景中的每一个体积元直接输出机器人抓取质量预测值,以及钩爪...
这是七个维度抓取方法(该方法由Jiang et al提出 )的一种简化,我们没有使用完整的物体3d抓取的位置和方向信息,而是假设一个机器人查看这个场景的视角,假设二维图像的抓取,可以映射回到三维数据上。第二个参考文献等人描述了实现这一方法的过程,并且与此同时,他们并没有直接评估该方法,不过在他们的实验中,他们的方法...
[IROS 2024] Language-driven Grasp Detection with Mask-guided Attention multimodal-learning transformer-attention language-driven-grasp-detection Updated Oct 25, 2024 Python Improve this page Add a description, image, and links to the language-driven-grasp-detection topic page so that developers ...
Real-Time Deep Learning Approach to Visual Servo Control and Grasp Detection for Autonomous Robotic Manipulation (基于视觉的机器人抓取——从物体定位、物体姿态估计到平行抓取器抓取估计:综述) 1 引言 找到理想抓取配置的抓取假设的子集包括:机器人将执行的任务类型、目标物体的特征、关于物体的先验知识类型、机械...
Grasp detection is a visual recognition task where the robot makes use of its sensors to detect graspable objects in its environment. Despite the steady progress in robotic grasping, it is still difficult to achieve both real-time and high accuracy grasping detection. In this paper, we propose ...
论文地址:ASGrasp: Generalizable Transparent Object Reconstruction and 6-DoF Grasp Detection from RGB-D Active Stereo Camera 代码地址:https://github.com/jun7-shi/ASGrasp 目录 1、准备GPU加速环境 2、安装torch和cudatoolkit 3、安装Graspness相关依赖库 ...
End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB code: https://paperswithcode.com/paper/end-to-end-trainable-deep-neural-network-for 摘要:在这项工作中,我们引入了一种新颖的、端到端可训练的基于cnn的架构,以提供适用于并行板夹钳...
Robotic grasping Grasp detection Parallel gripper 6-DOF 1. Introduction In recent years, robots have been widely used in production and life, and play a more and more important role, and grasp as the basic technology of robots also continue to progress, promoting the development of robot technol...
Language-driven Grasp Detection with Mask-guided Attention Installation Checkout the robotic grasping package $ git clone https://github.com/anavuongdin/robotic-grasping.git Create a virtual environment $ conda create -n grasping python=3.9 Activate the virtual environment $ conda activate grasping...
Previous work primarily focused on localizing the object given the query, which requires a separate grasp detection module to grasp it. The cascaded application of two pipelines incurs errors in overlapping multi-object cases due to ambiguity in the individual outputs. This work proposes a model ...