Paper Reading AI Learner

A Passively Bendable, Compliant Tactile Palm with RObotic Modular Endoskeleton Optical Fingers

2024-04-12 03:44:50
Sandra Q. Liu, Edward H. Adelson


Many robotic hands currently rely on extremely dexterous robotic fingers and a thumb joint to envelop themselves around an object. Few hands focus on the palm even though human hands greatly benefit from their central fold and soft surface. As such, we develop a novel structurally compliant soft palm, which enables more surface area contact for the objects that are pressed into it. Moreover, this design, along with the development of a new low-cost, flexible illumination system, is able to incorporate a high-resolution tactile sensing system inspired by the GelSight sensors. Concurrently, we design RObotic Modular Endoskeleton Optical (ROMEO) fingers, which are underactuated two-segment soft fingers that are able to house the new illumination system, and we integrate them into these various palm configurations. The resulting robotic hand is slightly bigger than a baseball and represents one of the first soft robotic hands with actuated fingers and a passively compliant palm, all of which have high-resolution tactile sensing. This design also potentially helps researchers discover and explore more soft-rigid tactile robotic hand designs with greater capabilities in the future. The supplementary video can be found here: this https URL

Abstract (translated)

目前,许多机器人手依赖于极其灵巧的机器人手指和拇指关节来环绕物体。尽管人类手在中央折叠和柔软表面方面受益很大,但很少有手关注手掌。因此,我们开发了一种新型的结构 compliant 的软手掌,这使得贴合在一起的物体具有更多的接触面积。此外,这款设计以及开发低成本、柔韧的照明系统,能够将类似于GelSight传感器的精确触觉感应系统集成其中。同时,我们设计了一种 Robotic Modular Endoskeleton Optical (ROMEO) 手指,这是一种两个可弯曲的软手指,能够容纳新的照明系统,并将它们集成到各种手掌配置中。 resulting robotic hand 比棒球略大,是第一款具有激活手指和被动顺应手掌的软机器人手之一,所有这些都具有高分辨率的手感。这种设计还有可能帮助研究人员发现和探索更多柔软、刚性的触觉机器人手设计,具有更大的潜力。补充视频请点击这里:



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 LLM 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 Robot 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