2021 IEEE International Conference on Robotics and Automation (ICRA)最新文献_第4页

Efficient Online Calibration for Autonomous Vehicle’s Longitudinal Dynamical System: A Gaussian Model Approach 自动驾驶汽车纵向动力系统的有效在线标定:高斯模型方法

2021 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2021-05-30 DOI: 10.1109/ICRA48506.2021.9560912

Shihao Wang, Canqiang Deng, Q. Qi

{"title":"Efficient Online Calibration for Autonomous Vehicle’s Longitudinal Dynamical System: A Gaussian Model Approach","authors":"Shihao Wang, Canqiang Deng, Q. Qi","doi":"10.1109/ICRA48506.2021.9560912","DOIUrl":"https://doi.org/10.1109/ICRA48506.2021.9560912","url":null,"abstract":"In this paper, we present an efficient online calibration system for longitudinal vehicle dynamics of driverless cars. Instead of modeling vehicle’s longitudinal dynamical system analytically, we employ a data-driven method to generate an \"end-to-end\" numerical model with a look-up table which saves vehicle’s velocity, control command, and acceleration. This reference table should be calibrated to account for variations of vehicle’s hardware status over time. To reduce the expensive labor in calibration process, we propose an effective algorithm to update this reference look-up table with a Gaussian model approach. We introduce a 2-D Gaussian distribution to model acceleration error between interpolated one from look-up table and actual one from vehicle sensors. We estimate model’s standard deviations with a \"three-sigma rule\" heuristic and calculate its height with a backtracking method such that monotonicity constraint between acceleration and control command is strictly satisfied in the updated table. The effectiveness of our proposed system is verified in realworld road tests with Lincoln MKZ.","PeriodicalId":108312,"journal":{"name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114601816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Long-term Multiple Time-Constant Model of a Spring Roll Dielectric Elastomer Actuator under Dynamic Loading* 动态载荷下弹簧卷介质弹性体作动器的长期多时间常数模型*

2021 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2021-05-30 DOI: 10.1109/ICRA48506.2021.9561167

S. Jeong, Ki-Uk Kyung

{"title":"Long-term Multiple Time-Constant Model of a Spring Roll Dielectric Elastomer Actuator under Dynamic Loading*","authors":"S. Jeong, Ki-Uk Kyung","doi":"10.1109/ICRA48506.2021.9561167","DOIUrl":"https://doi.org/10.1109/ICRA48506.2021.9561167","url":null,"abstract":"Dielectric elastomers are electro-mechanically coupled transducers that display a nonlinear viscoelastic stress-strain relationship. Modeling and controlling such nonlinear materials and actuators are of great challenge. A spring roll dielectric elastomer actuator is a linear actuator composed of a spring and sheets of wrapped dielectric elastomers. Since its shape and actuation performance resemble a human muscle, its application as an artificial muscle is investigated. To verify its applicability, the actuator’s controllability and time-dependent actuation behavior are examined. In this paper, we derive a multiple time-constant model specifying the response of a long-term dynamic loading of the spring roll dielectric elastomer actuator. Our modeling approach is based on multiple viscoelastic elements, having different time responses, superposed into one rheological model. In addition to viscoelasticity, the model includes the effects of the spring core, external mechanical load, the internal stress of the elastomer, and the applied dynamic voltage signal, so that it can be applied in various working conditions. Experiments and simulations are conducted to confirm the applicability and accuracy of the proposed long-term multiple time-constant model.","PeriodicalId":108312,"journal":{"name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122040419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Human Initiated Grasp Space Exploration Algorithm for an Underactuated Robot Gripper Using Variational Autoencoder 基于变分自编码器的欠驱动机器人手爪人主动抓取空间探索算法

2021 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2021-05-30 DOI: 10.1109/ICRA48506.2021.9561765

Clément Rolinat, M. Grossard, Saifeddine Aloui, C. Godin

引用次数: 3

π-LSAM: LiDAR Smoothing and Mapping With Planes π-LSAM:激光雷达平滑与平面映射

2021 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2021-05-30 DOI: 10.1109/ICRA48506.2021.9561933

Lipu Zhou, Shengze Wang, M. Kaess

{"title":"π-LSAM: LiDAR Smoothing and Mapping With Planes","authors":"Lipu Zhou, Shengze Wang, M. Kaess","doi":"10.1109/ICRA48506.2021.9561933","DOIUrl":"https://doi.org/10.1109/ICRA48506.2021.9561933","url":null,"abstract":"This paper introduces a real-time dense planar LiDAR SLAM system, named π-LSAM, for the indoor environment. The widely used LiDAR odometry and mapping (LOAM) framework [1] does not include bundle adjustment (BA) and generates a low fidelity tracking pose. This paper seeks to overcome these drawbacks for the indoor environment. Specifically, we use the plane as the landmark, and introduce plane adjustment (PA) as our back-end to jointly optimize planes and keyframe poses. We present the π-factor to significantly reduce the computational complexity of PA. In addition, we introduce an efficient loop detection algorithm based on the RANSAC framework using planes. In the front-end, our algorithm performs global registration in real time. To achieve this performance, we maintain the local-to-global point-to-plane correspondences scan by scan, so that we only need a small local KD-tree to establish the data association between a LiDAR scan and the global planes, rather than a large global KD-tree used in previous works. With this local-to-global data association, our algorithm directly identifies planes in a LiDAR scan, and yields an accurate and globally consistent pose. Experimental results show that our algorithm significantly outperforms the state-of-the-art LOAM variant, LeGO-LOAM [2], and our algorithm achieves real time.","PeriodicalId":108312,"journal":{"name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117047382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 25

Grasp Detection for Robot to Human Handovers Using Capacitive Sensors 基于电容传感器的机器人人机切换抓取检测

2021 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2021-05-30 DOI: 10.1109/ICRA48506.2021.9560970

I. Mamaev, David Kretsch, H. Alagi, B. Hein

引用次数: 4

An MR Safe Rotary Encoder Based on Eccentric Sheave and FBG Sensors 基于偏心轮和光纤光栅传感器的磁流变安全旋转编码器

2021 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2021-05-30 DOI: 10.1109/ICRA48506.2021.9561227

Shaoping Huang, Anzhu Gao, Zicong Wu, Chuqian Lou, Yanjun Wang, Guang-Zhong Yang

{"title":"An MR Safe Rotary Encoder Based on Eccentric Sheave and FBG Sensors","authors":"Shaoping Huang, Anzhu Gao, Zicong Wu, Chuqian Lou, Yanjun Wang, Guang-Zhong Yang","doi":"10.1109/ICRA48506.2021.9561227","DOIUrl":"https://doi.org/10.1109/ICRA48506.2021.9561227","url":null,"abstract":"MRI-guided robotic systems are emerging platforms for minimally invasive intervention because of high positioning accuracy and excellent tissue contrast. MR safe encoders are critical components for closed-loop robotic control. This paper develops an MR safe absolute rotary encoder based on eccentric sheave and FBG sensors. The eccentric sheave transforms the rotational motion of the shaft to the bending deflection of the beam on which FBG sensors are integrated. A model is built by establishing the relationship of the kinematics of the sheave, the mechanical properties of the beam with unknown length, and the strain model of two Fiber Bragg Grating (FBG) sensors. A Pseudo-Rigid Body (PRB) 3R model is used to solve a set of constrained equations for accurate rotary encoding. A prototype is built to calibrate the parameters and validate the accuracy of the encoder and its MR compatibility. Results show that the maximum angular error is 1.6°, and the RMS error is 0.46°. MRI shows that no noticeable artifacts are observed, and the Signal to Noise Ratio (SNR) is not affected. The results demonstrate the potential of the proposed method for it to be integrated with MR safe robots with easy fabrication, compact structures, and continuous measurement.","PeriodicalId":108312,"journal":{"name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117284300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A Soft Robotic Gripper with Anti-Freezing Ionic Hydrogel-Based Sensors for Learning-Based Object Recognition 基于学习的物体识别的防冻离子水凝胶传感器软性机器人抓手

2021 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2021-05-30 DOI: 10.1109/ICRA48506.2021.9561287

Runze Zuo, Zhanfeng Zhou, Binbin Ying, Xinyu Liu

{"title":"A Soft Robotic Gripper with Anti-Freezing Ionic Hydrogel-Based Sensors for Learning-Based Object Recognition","authors":"Runze Zuo, Zhanfeng Zhou, Binbin Ying, Xinyu Liu","doi":"10.1109/ICRA48506.2021.9561287","DOIUrl":"https://doi.org/10.1109/ICRA48506.2021.9561287","url":null,"abstract":"Soft robotic grippers possess high structural compliance and adaptability for grasping objects with unknown and irregular shapes and sizes. To enable more dexterous manipulation, soft sensors with similar mechanical properties to common elastomer materials are desired to be integrated into soft grippers. In this paper, we develop ionic hydrogel-based strain and tactile sensors and integrate these sensors into a three-finger soft gripper for learning-based object recognition. Such hydrogel-based sensors have excellent conductivity, high stretchability and toughness, good ambient stability, and unique anti-freezing property, and can be readily attached to a soft gripper at desired locations for strain and tactile sensing. Based on a deep-learning model, we demonstrate the capability of the sensory soft gripper for object grasping and recognition at both room and freezing temperatures, and achieve high recognition accuracy close to 100% for 10 typical objects. With these abilities, our gripper can find interesting applications such as sorting food or chemicals in low temperature storage and cold chain transportation, or manipulating equipment in polar area.","PeriodicalId":108312,"journal":{"name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129590922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

A Novel Torsional Actuator Augmenting Twisting Skeleton and Artificial Muscle for Robots in Extreme Environments 一种用于极端环境下机器人的增强扭曲骨架和人造肌肉的新型扭转驱动器

2021 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2021-05-30 DOI: 10.1109/ICRA48506.2021.9561957

Zhujin Jiang, Ketao Zhang

{"title":"A Novel Torsional Actuator Augmenting Twisting Skeleton and Artificial Muscle for Robots in Extreme Environments","authors":"Zhujin Jiang, Ketao Zhang","doi":"10.1109/ICRA48506.2021.9561957","DOIUrl":"https://doi.org/10.1109/ICRA48506.2021.9561957","url":null,"abstract":"Torsional actuators are a class of artificial muscle technology that generates torque and produces rotary motion in response to various stimuli. This paper presents a novel torsional actuator combining an origami-inspired twisting skeleton and an artificial muscle. The process of torsional actuator design starts from identifying a foldable twisting skeleton which is capable of achieving helical motion thereby translating linear motion to rotational motion. This is followed by the integration of an artificial muscle to drive the twisting skeleton. Kinematics of both the twisting skeleton and artificial muscle are analyzed. Following the design and kinematic analysis, a prototype is developed by bonding 3D printed polylactic acid (PLA) parts and thermoplastic polyurethane (TPU) films to form the twisting skeleton and laminating TPU membranes by using heat sealing tools to form the artificial muscle. A pneumatic control system is built to evaluate the performances of torsional actuator by testing the relationship between twisting angle, air pressure, driving force and output torque. Experimental results show that the relationship between air pressure, driving force and output torque is proportional at a given twisting angle. The novel torsional actuator augmenting an origami-inspired skeleton and soft artificial muscle leads to simplified analytical model and has potential of driving robotic systems in environment where pneumatically actuated systems are preferred over electrical machines and drives.","PeriodicalId":108312,"journal":{"name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128303621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

HyperMap: Compressed 3D Map for Monocular Camera Registration HyperMap:用于单目相机配准的压缩3D地图

2021 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2021-05-30 DOI: 10.1109/ICRA48506.2021.9561864

Ming-Fang Chang, Joshua G. Mangelson, M. Kaess, S. Lucey

{"title":"HyperMap: Compressed 3D Map for Monocular Camera Registration","authors":"Ming-Fang Chang, Joshua G. Mangelson, M. Kaess, S. Lucey","doi":"10.1109/ICRA48506.2021.9561864","DOIUrl":"https://doi.org/10.1109/ICRA48506.2021.9561864","url":null,"abstract":"We address the problem of image registration to a compressed 3D map. While this is most often performed by comparing LiDAR scans to the point cloud based map, it depends on an expensive LiDAR sensor at run time and the large point cloud based map creates overhead in data storage and transmission. Recently, efforts have been underway to replace the expensive LiDAR sensor with cheaper cameras and perform 2D-3D localization. In contrast to the previous work that learns relative pose by comparing projected depth and camera images, we propose HyperMap, a paradigm shift from online depth map feature extraction to offline 3D map feature computation for the 2D-3D camera registration task through end-to-end training. In the proposed pipeline, we first perform offline 3D sparse convolution to extract and compress the voxelwise hypercolumn features for the whole map. Then at run-time, we project and decode the compressed map features to the rough initial camera pose to form a virtual feature image. A Convolutional Neural Network (CNN) is then used to predict the relative pose between the camera image and the virtual feature image. In addition, we propose an efficient occlusion handling layer, specifically designed for large point clouds, to remove occluded points in projection. Our experiments on synthetic and real datasets show that, by moving the feature computation load offline and compressing, we reduced map size by 87−94% while maintaining comparable or better accuracy.","PeriodicalId":108312,"journal":{"name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128791735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Long-Range Hand Gesture Recognition via Attention-based SSD Network 基于注意力的SSD网络远程手势识别

2021 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2021-05-30 DOI: 10.1109/ICRA48506.2021.9561189

Liguang Zhou, Chenping Du, Zhenglong Sun, Tin Lun Lam, Yangsheng Xu

{"title":"Long-Range Hand Gesture Recognition via Attention-based SSD Network","authors":"Liguang Zhou, Chenping Du, Zhenglong Sun, Tin Lun Lam, Yangsheng Xu","doi":"10.1109/ICRA48506.2021.9561189","DOIUrl":"https://doi.org/10.1109/ICRA48506.2021.9561189","url":null,"abstract":"Hand gesture recognition plays an essential role in the human-robot interaction (HRI) field. Most previous research only studies hand gesture recognition in a short distance, which cannot be applied for interaction with mobile robots like unmanned aerial vehicles (UAVs) at a longer and safer distance. Therefore, we investigate the challenging long-range hand gesture recognition problem for the interaction between humans and UAVs. To this end, we propose a novel attention-based single shot multibox detector (SSD) model that incorporates both spatial and channel attention for hand gesture recognition. We notably extend the recognition distance from 1 meter to 7 meters through the proposed model without sacrificing speed. Besides, we present a long-range hand gesture (LRHG) dataset collected by the USB camera mounted on mobile robots. The hand gestures are collected at discrete distance levels from 1 meter to 7 meters, where most of the hand gestures are small and at low resolution. Experiments with the self-built LRHG dataset show our methods reach the surprising performance-boosting over the state-of-the-art method like the SSD network on both short-range (1 meter) and long-range (up to 7 meters) hand gesture recognition tasks.","PeriodicalId":108312,"journal":{"name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128573812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4