[HTML][HTML] Robot tool use: A survey
M Qin, J Brawer, B Scassellati - Frontiers in Robotics and AI, 2023 - frontiersin.org
Using human tools can significantly benefit robots in many application domains. Such ability
would allow robots to solve problems that they were unable to without tools. However, robot …
would allow robots to solve problems that they were unable to without tools. However, robot …
Sim-to-real 6d object pose estimation via iterative self-training for robotic bin picking
Abstract 6D object pose estimation is important for robotic bin-picking, and serves as a
prerequisite for many downstream industrial applications. However, it is burdensome to …
prerequisite for many downstream industrial applications. However, it is burdensome to …
MetaGraspNetV2: All-in-one dataset enabling fast and reliable robotic bin picking via object relationship reasoning and dexterous grasping
Grasping unknown objects in unstructured environments is one of the most challenging and
demanding tasks for robotic bin picking systems. Developing a holistic approach is crucial to …
demanding tasks for robotic bin picking systems. Developing a holistic approach is crucial to …
Two-stage grasping: A new bin picking framework for small objects
This paper proposes a novel bin picking framework, two-stage grasping, aiming at precise
grasping of cluttered small objects. Object density estimation and rough grasping are …
grasping of cluttered small objects. Object density estimation and rough grasping are …
Generating synthetic training images to detect split defects in stamped components
AR Singh, T Bashford-Rogers, S Hazra… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Detecting rare and costly defects, such as necks and splits in sheet metal stamping, remains
challenging for deep learning models due to low failure rates entailing few available …
challenging for deep learning models due to low failure rates entailing few available …
Learning efficient policies for picking entangled wire harnesses: An approach to industrial bin picking
X Zhang, Y Domae, W Wan… - IEEE Robotics and …, 2022 - ieeexplore.ieee.org
Wire harnesses are essential connecting components in manufacturing industry but are
challenging to be automated in industrial tasks such as bin picking. They are long, flexible …
challenging to be automated in industrial tasks such as bin picking. They are long, flexible …
Increasing the Robustness of Deep Learning Models for Object Segmentation: A Framework for Blending Automatically Annotated Real and Synthetic Data
Recent problems in robotics can sometimes only be tackled using machine learning
technologies, particularly those that utilize deep learning (DL) with transfer learning …
technologies, particularly those that utilize deep learning (DL) with transfer learning …
Certifiable Object Pose Estimation: Foundations, Learning Models, and Self-Training
In this article, we consider a certifiable object pose estimation problem, where—given a
partial point cloud of an object—the goal is to not only estimate the object pose, but also …
partial point cloud of an object—the goal is to not only estimate the object pose, but also …
Danet: Density adaptive convolutional network with interactive attention for 3d point clouds
Local features and contextual dependencies are crucial for 3D point cloud analysis. Many
works have been devoted to designing better local convolutional kernels that exploit the …
works have been devoted to designing better local convolutional kernels that exploit the …
Deep learning based 6-DoF antipodal grasp planning from point cloud in random bin-picking task using single-view
Random bin picking is a crucial task in logistic centers, which is driven by E-Commerce
growth. In this letter, we present an end-to-end method for 6-DoF antipodal grasps from …
growth. In this letter, we present an end-to-end method for 6-DoF antipodal grasps from …