2020 IEEE International Conference on Robotics and Automation (ICRA)最新文献_第7页

Deep Visual Heuristics: Learning Feasibility of Mixed-Integer Programs for Manipulation Planning 深度视觉启发式:操作规划混合整数方案的学习可行性

2020 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2020-05-01 DOI: 10.1109/ICRA40945.2020.9197291

Danny Driess, Ozgur S. Oguz, Jung-Su Ha, M. Toussaint

引用次数: 47

Towards Noise Resilient SLAM 抗噪音SLAM

2020 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2020-05-01 DOI: 10.1109/ICRA40945.2020.9196745

Anirud Thyagharajan, O. J. Omer, D. Mandal, S. Subramoney

{"title":"Towards Noise Resilient SLAM","authors":"Anirud Thyagharajan, O. J. Omer, D. Mandal, S. Subramoney","doi":"10.1109/ICRA40945.2020.9196745","DOIUrl":"https://doi.org/10.1109/ICRA40945.2020.9196745","url":null,"abstract":"Sparse-indirect SLAM systems have been dominantly popular due to their computational efficiency and photometric invariance properties. Depth sensors are critical to SLAM frameworks for providing scale information to the 3D world, yet known to be plagued by a wide variety of noise sources, possessing lateral and axial components. In this work, we demonstrate the detrimental impact of these depth noise components on the performance of the state-of-the-art sparse-indirect SLAM system (ORB-SLAM2). We propose (i) Map-Point Consensus based Outlier Rejection (MC-OR) to counter lateral noise, and (ii) Adaptive Virtual Camera (AVC) to combat axial noise accurately. MC-OR utilizes consensus information between multiple sightings of the same landmark to disambiguate noisy depth and filter it out before pose optimization. In AVC, we introduce an error vector as an accurate representation of the axial depth error. We additionally propose an adaptive algorithm to find the virtual camera location for projecting the error used in the objective function of the pose optimization. Our techniques work equally well for stereo image pairs and RGB-D input directly used by sparse-indirect SLAM systems. Our methods were tested on the TUM (RGB-D) and EuRoC (stereo) datasets and we show that they outperform existing state-of-the-art ORB-SLAM2 by 2-3x, especially in sequences critically affected by depth noise.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"54 1","pages":"72-79"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80607052","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

Fast Adaptation of Deep Reinforcement Learning-Based Navigation Skills to Human Preference 基于深度强化学习的导航技能对人类偏好的快速适应

2020 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2020-05-01 DOI: 10.1109/ICRA40945.2020.9197159

Jinyoung Choi, C. Dance, Jung-Eun Kim, Kyungsik Park, Jaehun Han, Joonho Seo, Minsu Kim

引用次数: 15

An Actuation Fault Tolerance Approach to Reconfiguration Planning of Modular Self-folding Robots 模块化自折叠机器人重构规划的驱动容错方法

2020 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2020-05-01 DOI: 10.1109/ICRA40945.2020.9196574

Meibao Yao, Xueming Xiao, Yang Tian, Hutao Cui, J. Paik

{"title":"An Actuation Fault Tolerance Approach to Reconfiguration Planning of Modular Self-folding Robots","authors":"Meibao Yao, Xueming Xiao, Yang Tian, Hutao Cui, J. Paik","doi":"10.1109/ICRA40945.2020.9196574","DOIUrl":"https://doi.org/10.1109/ICRA40945.2020.9196574","url":null,"abstract":"This paper presents a novel approach to fault tolerant reconfiguration of modular self-folding robots. Among various types of faults that probably occur in the modular system, we focus on the tolerance of complete actuation failure of active modules that might cause imprecise robotic motion and even reconfiguration failure. Our approach is to utilize the reconfigurability of modular self-folding robots and investigate intra-module connection to determine initial patterns that are inherently fault tolerant. We exploit the redundancy of actuation and distribute active modules in both layout-based and target-based scenarios, such that reconfiguration schemes with user-specified fault tolerant capability can be generated for an arbitrary input initial pattern or 3D configuration. Our methods are demonstrated in computer-aided simulation on the robotic platform of Mori, a modular origami robot. The simulation results validate that the proposed algorithms yield fault tolerant initial patterns and distribution schemes of active modules for several 2D and 3D configurations with Mori, while retaining generalizability for a large number of modular self-folding robots.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"45 1","pages":"8274-8280"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80667277","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

The Tiercel: A novel autonomous micro aerial vehicle that can map the environment by flying into obstacles Tiercel:一种新型的自主微型飞行器，可以通过飞入障碍物来绘制环境地图

2020 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2020-05-01 DOI: 10.1109/ICRA40945.2020.9197269

Yash Mulgaonkar, Wenxin Liu, Dinesh Thakur, Kostas Daniilidis, C. J. Taylor, Vijay R. Kumar

{"title":"The Tiercel: A novel autonomous micro aerial vehicle that can map the environment by flying into obstacles","authors":"Yash Mulgaonkar, Wenxin Liu, Dinesh Thakur, Kostas Daniilidis, C. J. Taylor, Vijay R. Kumar","doi":"10.1109/ICRA40945.2020.9197269","DOIUrl":"https://doi.org/10.1109/ICRA40945.2020.9197269","url":null,"abstract":"Autonomous flight through unknown environments in the presence of obstacles is a challenging problem for micro aerial vehicles (MAVs). A majority of the current state-of-art research assumes obstacles as opaque objects that can be easily sensed by optical sensors such as cameras or LiDARs. However in indoor environments with glass walls and windows, or scenarios with smoke and dust, robots (even birds) have a difficult time navigating through the unknown space.In this paper, we present the design of a new class of micro aerial vehicles that achieves autonomous navigation and are robust to collisions. In particular, we present the Tiercel MAV: a small, agile, light weight and collision-resilient robot powered by a cellphone grade CPU. Our design exploits contact to infer the presence of transparent or reflective obstacles like glass walls, integrating touch with visual perception for SLAM. The Tiercel is able to localize using visual-inertial odometry (VIO) running on board the robot with a single downward facing fisheye camera and an IMU. We show how our collision detector design and experimental set up enable us to characterize the impact of collisions on VIO. We further develop a planning strategy to enable the Tiercel to fly autonomously in an unknown space, sustaining collisions and creating a 2D map of the environment. Finally we demonstrate a swarm of three autonomous Tiercel robots safely navigating and colliding through an obstacle field to reach their objectives.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"13 1","pages":"7448-7454"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82026179","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: 13

Acoustofluidic Tweezers for the 3D Manipulation of Microparticles 用于微粒子三维操作的声流控镊子

2020 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2020-05-01 DOI: 10.1109/ICRA40945.2020.9197265

Xinyi Guo, Zhichao Ma, R. Goyal, Moonkwang Jeong, W. Pang, P. Fischer, X. Duan, T. Qiu

引用次数: 2

Efficient Communication in Large Multi-robot Networks 大型多机器人网络中的高效通信

2020 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2020-05-01 DOI: 10.1109/ICRA40945.2020.9196672

Ayan Dutta, Anirban Ghosh, Stephen Sisley, O. P. Kreidl

引用次数: 3

Gradient and Log-based Active Learning for Semantic Segmentation of Crop and Weed for Agricultural Robots 基于梯度和日志的农业机器人作物和杂草语义分割主动学习

2020 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2020-05-01 DOI: 10.1109/ICRA40945.2020.9196722

Rasha Sheikh, Andres Milioto, Philipp Lottes, C. Stachniss, Maren Bennewitz, T. Schultz

{"title":"Gradient and Log-based Active Learning for Semantic Segmentation of Crop and Weed for Agricultural Robots","authors":"Rasha Sheikh, Andres Milioto, Philipp Lottes, C. Stachniss, Maren Bennewitz, T. Schultz","doi":"10.1109/ICRA40945.2020.9196722","DOIUrl":"https://doi.org/10.1109/ICRA40945.2020.9196722","url":null,"abstract":"Annotated datasets are essential for supervised learning. However, annotating large datasets is a tedious and time-intensive task. This paper addresses active learning in the context of semantic segmentation with the goal of reducing the human labeling effort. Our application is agricultural robotics and we focus on the task of distinguishing between crop and weed plants from image data. A key challenge in this application is the transfer of an existing semantic segmentation CNN to a new field, in which growth stage, weeds, soil, and weather conditions differ. We propose a novel approach that, given a trained model on one field together with rough foreground segmentation, refines the network on a substantially different field providing an effective method of selecting samples to annotate for supporting the transfer. We evaluated our approach on two challenging datasets from the agricultural robotics domain and show that we achieve a higher accuracy with a smaller number of samples compared to random sampling as well as entropy based sampling, which consequently reduces the required human labeling effort.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"33 1","pages":"1350-1356"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91099625","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: 16

Reactive Control and Metric-Topological Planning for Exploration 勘探中的被动控制和度量拓扑规划

2020 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2020-05-01 DOI: 10.1109/ICRA40945.2020.9197381

Michael T. Ohradzansky, Andrew B. Mills, Eugene R. Rush, Danny G. Riley, E. Frew, J. Humbert

引用次数: 13

Eye-in-Hand 3D Visual Servoing of Helical Swimmers Using Parallel Mobile Coils 利用平行移动线圈的螺旋游泳者眼手三维视觉伺服

2020 IEEE International Conference on Robotics and Automation (ICRA) Pub Date : 2020-05-01 DOI: 10.1109/ICRA40945.2020.9197276

Zhengxin Yang, Lidong Yang, Li Zhang

{"title":"Eye-in-Hand 3D Visual Servoing of Helical Swimmers Using Parallel Mobile Coils","authors":"Zhengxin Yang, Lidong Yang, Li Zhang","doi":"10.1109/ICRA40945.2020.9197276","DOIUrl":"https://doi.org/10.1109/ICRA40945.2020.9197276","url":null,"abstract":"Magnetic helical microswimmers can be propelled by rotating magnetic field and are adept at passing through narrow space. To date, various magnetic actuation systems and control methods have been developed to drive these microswimmers. However, steering their spacial movement in a large workspace is still challenging, which could be significant for potential medical applications. In this regard, this paper designs an eye-in-hand stereo-vision module and corresponding refraction-rectified location algorithm. Combined with the motor module and the coil module, the mobile-coil system is capable of generating dynamic magnetic fields in a large 3D workspace. Based on the system, a robust triple-loop stereo visual servoing strategy is proposed that operates simultaneous tracking, locating, and steering, through which the helical swimmer is able to follow a long-distance 3D path. A scaled-up magnetic helical swimmer is employed in the path following experiment. Our prototype system reaches a cylindrical workspace with a diameter more than 200 mm, and the mean error of path tracking is less than 2 mm.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"3 1","pages":"9223-9229"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89979761","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