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842 results on '"Chen, Xiangsheng"'

5. Enhancing Grasping Performance of Novel Objects through an Improved Fine-Tuning Process

Author

Hu, Xiao and Chen, Xiangsheng

Subjects
Computer Science - Robotics
Abstract

Grasping algorithms have evolved from planar depth grasping to utilizing point cloud information, allowing for application in a wider range of scenarios. However, data-driven grasps based on models trained on basic open-source datasets may not perform well on novel objects, which are often required in different scenarios, necessitating fine-tuning using new objects. The data driving these algorithms essentially corresponds to the closing region of the hand in 6D pose, and due to the uniqueness of 6D pose, synthetic annotation or real-machine annotation methods are typically employed. Acquiring large amounts of data with real-machine annotation is challenging, making synthetic annotation a common practice. However, obtaining annotated 6D pose data using conventional methods is extremely time-consuming. Therefore, we propose a method to quickly acquire data for novel objects, enabling more efficient fine-tuning. Our method primarily samples grasp orientations to generate and annotate grasps. Experimental results demonstrate that our fine-tuning process for a new object is 400 \% faster than other methods. Furthermore, we propose an optimized grasp annotation framework that accounts for the effects of the gripper closing, making the annotations more reasonable. Upon acceptance of this paper, we will release our algorithm as open-source.

Published
2023

8. ONE PIECE: One Patchwork In Effectively Combined Extraction for grasp

Author

Hu, Xiao, Mo, HangJie, Chen, XiangSheng, Chen, JinLiang, and Chen, Xiangyu

Subjects
Computer Science - Robotics
Abstract

For grasp network algorithms, generating grasp datasets for a large number of 3D objects is a crucial task. However, generating grasp datasets for hundreds of objects can be very slow and consume a lot of storage resources, which hinders algorithm iteration and promotion. For point cloud grasp network algorithms, the network input is essentially the internal point cloud of the grasp area that intersects with the object in the gripper coordinate system. Due to the existence of a large number of completely consistent gripper area point clouds based on the gripper coordinate system in the grasp dataset generated for hundreds of objects, it is possible to remove the consistent gripper area point clouds from many objects and assemble them into a single object to generate the grasp dataset, thus replacing the enormous workload of generating grasp datasets for hundreds of objects. We propose a new approach to map the repetitive features of a large number of objects onto a finite set.To this end, we propose a method for extracting the gripper area point cloud that intersects with the object from the simulator and design a gripper feature filter to remove the shape-repeated gripper space area point clouds, and then assemble them into a single object. The experimental results show that the time required to generate the new object grasp dataset is greatly reduced compared to generating the grasp dataset for hundreds of objects, and it performs well in real machine grasping experiments. We will release the data and tools after the paper is accepted., Comment: Submitted to IROS2023

Published
2023

31. Countermeasures for Low-Carbon Transformation of Construction Industry in China Toward the Carbon Peaking and Carbon Neutrality Goals

Author

Wu Zezhou, Huang Haoquan, Chen Xiangsheng, Li Jianjun, He Qiufeng, Li Ao, Huang Jun, Lin Yuhan, Liu Xingyu, and Wang Jiahao

Subjects
carbon peaking and carbon neutrality goals, construction industry, carbon emissions, low-carbon transformation, Engineering (General). Civil engineering (General), TA1-2040
Abstract

Carbon emission reduction in the construction industry is crucial for promoting low-carbon transformation of the industry and for realizing the carbon peaking and carbon neutrality goals. This study analyzes the current status of carbon emissions in Chinese construction industry. It identifies that the production of building materials and the operation of buildings are the primary sources of carbon emissions in the overall construction process. Moreover, the growth rate of carbon emissions from the construction industry in China is decelerating, and the spatial characteristics of carbon emissions demonstrate an increase from the south to the north and from the west to the east. We have identified six key challenges that must be addressed to achieve carbon peaking and carbon neutrality in the construction industry of China: policy and standards framework, energy-efficient and carbon-reducing technologies, reduction of carbon emissions from existing buildings, carbon emission data collection and monitoring systems, economic incentives, and increased awareness of carbon reduction. Staged goals for the low-carbon development of the construction industry are also proposed. Furthermore, we suggest improving related policies and standards system, optimizing the use of energy-saving technologies, reducing carbon emissions in existing buildings, developing green finance, improving the ability to monitor carbon emissions, and enhancing the awareness of energy conservation and carbon reduction, so as to provide references for the low-carbon transformation and high-quality development of China’s construction industry.

Published
2023
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