4.7 Article

AttentionVote: A coarse-to-fine voting network of anchor-free 6D pose estimation on point cloud for robotic bin-picking application

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Computer Science, Interdisciplinary Applications

Instance segmentation based 6D pose estimation of industrial objects using point clouds for robotic bin-picking

Chungang Zhuang et al.

Summary: This article proposes a deep learning-based pose estimation method using point cloud as input, which includes instance segmentation and instance point cloud pose estimation. Experimental results demonstrate that this method can effectively and robustly predict the poses of objects in cluttered and occluded scenes.

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING (2023)

Review Computer Science, Interdisciplinary Applications

A review of robotic assembly strategies for the full operation procedure: planning, execution and evaluation

Yuze Jiang et al.

Summary: In this paper, recent research in the field of robotic assembly is systematically reviewed. Methods and characteristics of target recognition and searching, compliant strategies for fine insertion motion, and fault monitoring are analyzed. A performance evaluation method for assembly strategies is proposed, and the challenges and potential directions for further development are discussed.

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING (2022)

Article Automation & Control Systems

PPR-Net plus plus : Accurate 6-D Pose Estimation in Stacked Scenarios

Long Zeng et al.

Summary: The PPR-Net++ is a pose regression network that improves pose estimation accuracy by transforming each scene point into a point in centroid space and going through clustering and voting processes. It adapts bandwidth between centroid distributions of different domains by obtaining a mapping function between the network's key parameter (clustering algorithm bandwidth) and the compactness of centroid distributions. The network also predicts the confidence of each point based on visibility and pose error, allowing only highly confident points to vote for the final object pose.

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING (2022)

Article Computer Science, Interdisciplinary Applications

Generic development methodology for flexible robotic pick-and-place workcells based on Digital Twin

Bence Tipary et al.

Summary: This paper proposes a generalized development methodology for flexible robotic pick-and-place workcells based on the concept of Digital Twin, aiming to speed up the overall commissioning process and reduce the amount of work in the physical workcell.

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING (2021)

Article Computer Science, Interdisciplinary Applications

Semantic part segmentation method based 3D object pose estimation with RGB-D images for bin-picking

Chungang Zhuang et al.

Summary: This article proposes a Semantic Point Pair Feature (PPF) method for 3D object pose estimation, which combines semantic image segmentation using deep learning with voting-based 3D object pose estimation. The method improves the robustness and efficiency of 3D object pose estimation in cluttered scenes with partial occlusions.

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING (2021)

Article Computer Science, Software Engineering

CMA: Cross-modal attention for 6D object pose estimation

Lu Zou et al.

Summary: This paper proposes a Cross-Modal Attention (CMA) component for 6D object pose estimation, which aggregates features of RGB-D images adaptively through attention mechanism to efficiently extract powerful representations, achieving state-of-the-art performance.

COMPUTERS & GRAPHICS-UK (2021)

Article Computer Science, Artificial Intelligence

Efficient Center Voting for Object Detection and 6D Pose Estimation in 3D Point Cloud

Jianwei Guo et al.

Summary: The paper proposes a novel and efficient approach to estimate 6D object poses in complex scenes using an improved PPF framework. By introducing a new center voting strategy based on the relative geometric relationship, the method is able to generate accurate pose hypotheses and filter out false positives, demonstrating robustness towards challenging scenarios.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2021)

Article Computer Science, Artificial Intelligence

Augmented Autoencoders: Implicit 3D Orientation Learning for 6D Object Detection

Martin Sundermeyer et al.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2020)

Review Computer Science, Artificial Intelligence

A review on object pose recovery: From 3D bounding box detectors to full 6D pose estimators

Caner Sahin et al.

IMAGE AND VISION COMPUTING (2020)

Article Computer Science, Information Systems

3D Object Recognition and Pose Estimation From Point Cloud Using Stably Observed Point Pair Feature

Deping Li et al.

IEEE ACCESS (2020)

Article Computer Science, Artificial Intelligence

Defining the Pose of Any 3D Rigid Object and an Associated Distance

Romain Bregier et al.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2018)

Article Chemistry, Analytical

SECOND: Sparsely Embedded Convolutional Detection

Yan Yan et al.

SENSORS (2018)

Article Computer Science, Interdisciplinary Applications

Addressing perception uncertainty induced failure modes in robotic bin-picking

Krishnanand N. Kaipa et al.

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING (2016)

Article Robotics

Fast object localization and pose estimation in heavy clutter for robotic bin picking

Ming-Yu Liu et al.

INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH (2012)