Paper Reading AI Learner

Rational Linkages: From Poses to 3D-printed Prototypes

2024-03-01 14:33:51
Daniel Huczala, Johannes Siegele, Daren A. Thimm, Martin Pfurner, Hans-Peter Schr\"ocker
     

Abstract

In this paper, a set of tools is introduced that simplifies the synthesis and rapid-prototyping of single-loop rational kinematic chains. It allows the user to perform rational motion interpolation of up to four given poses and yields the design parameters of a linkage that can execute this motion. The package also provides a visualization of the output and performs a self-collision analysis with the possibility to adapt the design parameters. The results can be imported into CAD-systems for fast 3D printing.

Abstract (translated)

在本文中,介绍了一组工具来简化单环形理动链的合成和快速原型制作。使用户能够对给定的四个姿态进行理性运动插值,并得到执行这种运动的链接设计参数。该软件包还提供了输出可视化和自碰撞分析,并具有自适应设计参数的功能。结果可以导入CAD系统进行快速3D打印。

URL

https://arxiv.org/abs/2403.00558

PDF

https://arxiv.org/pdf/2403.00558.pdf


Tags
3D Action Action_Localization Action_Recognition Activity Adversarial Agent Attention Autonomous Bert Boundary_Detection Caption Chat Classification CNN Compressive_Sensing Contour Contrastive_Learning Deep_Learning Denoising Detection Dialog Diffusion Drone Dynamic_Memory_Network Edge_Detection Embedding Embodied Emotion Enhancement Face Face_Detection Face_Recognition Facial_Landmark Few-Shot Gait_Recognition GAN Gaze_Estimation Gesture Gradient_Descent Handwriting Human_Parsing Image_Caption Image_Classification Image_Compression Image_Enhancement Image_Generation Image_Matting Image_Retrieval Inference Inpainting Intelligent_Chip Knowledge Knowledge_Graph Language_Model Matching Medical Memory_Networks Multi_Modal Multi_Task NAS NMT Object_Detection Object_Tracking OCR Ontology Optical_Character Optical_Flow Optimization Person_Re-identification Point_Cloud Portrait_Generation Pose Pose_Estimation Prediction QA Quantitative Quantitative_Finance Quantization Re-identification Recognition Recommendation Reconstruction Regularization Reinforcement_Learning Relation Relation_Extraction Represenation Represenation_Learning Restoration Review RNN Salient Scene_Classification Scene_Generation Scene_Parsing Scene_Text Segmentation Self-Supervised Semantic_Instance_Segmentation Semantic_Segmentation Semi_Global Semi_Supervised Sence_graph Sentiment Sentiment_Classification Sketch SLAM Sparse Speech Speech_Recognition Style_Transfer Summarization Super_Resolution Surveillance Survey Text_Classification Text_Generation Tracking Transfer_Learning Transformer Unsupervised Video_Caption Video_Classification Video_Indexing Video_Prediction Video_Retrieval Visual_Relation VQA Weakly_Supervised Zero-Shot