2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)最新文献_第4页

Autonomous 4DOF Robotic Manipulator Prototype for Industrial Environment and Human Cooperation 面向工业环境与人类合作的自主四自由度机械臂原型

2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) Pub Date : 2019-04-01 DOI: 10.1109/ICARSC.2019.8733639

Ines Garcia, Fernando Gonçalves, T. Ribeiro, P. Fernandes, Cesar Rocha, Ricardo Boucinha, G. Lopes, A. Ribeiro

{"title":"Autonomous 4DOF Robotic Manipulator Prototype for Industrial Environment and Human Cooperation","authors":"Ines Garcia, Fernando Gonçalves, T. Ribeiro, P. Fernandes, Cesar Rocha, Ricardo Boucinha, G. Lopes, A. Ribeiro","doi":"10.1109/ICARSC.2019.8733639","DOIUrl":"https://doi.org/10.1109/ICARSC.2019.8733639","url":null,"abstract":"This paper describes the design and development of an autonomous robotic manipulator with four degrees of freedom. The manipulator is named RACHIE - “Robotic Arm for Collaboration with Humans in Industrial Environment”. The idea was to create a smaller version of the industrial manipulators available on the market. The mechanical and electronic components are presented as well as the software algorithms implemented on the robot. The manipulator has as its primary goal the detection and organization of cans by color and defects. The robot can detect a human operator so it can deliver defective cans by collaborating with him/her on an industrial environment. To be able to perform such task, the robot has implemented a machine learning algorithm, a Haar feature-based cascade classifier, on its vision system to detect cans and humans. On the handler motion, direct and inverse kinematics were calculated and implemented, and its equations are described in this paper. This robot presents high reliability and robustness in the task assigned. It is low-cost as it is a small version of commercial ones, making it optimized for smaller tasks.","PeriodicalId":198320,"journal":{"name":"2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133353752","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: 3

Comparing Spatial and Mobile Augmented Reality for Guiding Assembling Procedures with Task Validation 基于任务验证的空间增强现实与移动增强现实指导装配过程的比较

2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) Pub Date : 2019-04-01 DOI: 10.1109/ICARSC.2019.8733642

J. Alves, Bernardo Marques, Miguel Oliveira, Tiago Araújo, Paulo Dias, B. Santos

{"title":"Comparing Spatial and Mobile Augmented Reality for Guiding Assembling Procedures with Task Validation","authors":"J. Alves, Bernardo Marques, Miguel Oliveira, Tiago Araújo, Paulo Dias, B. Santos","doi":"10.1109/ICARSC.2019.8733642","DOIUrl":"https://doi.org/10.1109/ICARSC.2019.8733642","url":null,"abstract":"Assembly tasks are a common situation in many industrial applications. These tasks are often presented on paper or digital manuals containing instructions, photos or diagrams to guide an assembly sequence. While some Augmented Reality (AR) systems have also been proposed to support these processes, only a few track the state of the assembling procedure, validating the process in real-time. In this work, we propose two different AR-based (mobile and spatial AR) methods with real-time validation to provide assistance to users during the execution of an assembly process. The validation process uses computer vision techniques to keep track of the state of the assembly sequence, verifying the completion of each stage and providing information at the end of the assembly. A controlled experiment was used to compare the performance, ease of use, and acceptance of the two AR-based methods proposed. Participants were significantly faster and made fewer errors using the Spatial AR condition. Besides, participants also preferred this condition. In addition, Nasa TLX rating showed that the Spatial AR condition had a slightly lower cognitive load on the participants.","PeriodicalId":198320,"journal":{"name":"2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)","volume":"357 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115848141","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: 33

LIDAR-based people detection and tracking for @home Competitions 基于激光雷达的人员检测和跟踪@home比赛

2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) Pub Date : 2019-04-01 DOI: 10.1109/ICARSC.2019.8733624

C. Álvarez-Aparicio, Ángel Manuel Guerrero Higueras, F. J. Lera, Maria Carmen Calvo Olivera, Vicente Matellán Olivera, Jonatan Ginés Clavero, F. Martín

引用次数: 5

Path Planning approach with the extraction of Topological Maps from Occupancy Grid Maps in steep slope vineyards 陡坡葡萄园占用网格地图拓扑地图提取的路径规划方法

2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) Pub Date : 2019-04-01 DOI: 10.1109/ICARSC.2019.8733630

L. Santos, F. Santos, S. Magalhães, P. Costa, Ricardo Reis

引用次数: 15

Hybrid Approach to Estimate a Collision-Free Velocity for Autonomous Surface Vehicles 自动驾驶地面车辆无碰撞速度估计的混合方法

2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) Pub Date : 2019-04-01 DOI: 10.1109/ICARSC.2019.8733643

R. Silva, P. Leite, D. Campos, A. Pinto

{"title":"Hybrid Approach to Estimate a Collision-Free Velocity for Autonomous Surface Vehicles","authors":"R. Silva, P. Leite, D. Campos, A. Pinto","doi":"10.1109/ICARSC.2019.8733643","DOIUrl":"https://doi.org/10.1109/ICARSC.2019.8733643","url":null,"abstract":"Shipping transportation mode needs to be even more efficient, profitable and secure as more than 80 % of the world's trade is done by sea. Autonomous ships will provide the possibility to eliminate the likelihood of human error, reduce unnecessary crew costs and increase the efficiency of the cargo spaces. Although a significant work is being made, and new algorithms are arising, they are still a mirage and still have some problems regarding safety, autonomy and reliability. This paper proposes an online obstacle avoidance algorithm for Autonomous Surfaces Vehicles (ASVs) introducing the reachability with the protective zone concepts. This method estimates a collision-free velocity based on inner and outer constraints such as, current velocity, direction, maximum speed and turning radius of the vehicle, position and dimensions of the surround obstacles as well as a movement prediction in a close future. A non-restrictive estimative for the speed and direction of the ASV is calculated by mapping a conflict zone, determined by the course of the vehicle and the distance to obstacles that is used to avoid imminent dangerous situations. A set of simulations demonstrates the ability of this method to safely circumvent obstacles in several scenarios with different weather conditions.","PeriodicalId":198320,"journal":{"name":"2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124951521","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: 7

Development of a Navigator with Artificial Intelligence Applied to Smoothing and Execution of Paths in a Dynamic Two-Dimensional Environment 应用于动态二维环境中路径平滑和执行的人工智能导航器的开发

2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) Pub Date : 2019-04-01 DOI: 10.1109/ICARSC.2019.8733645

Franklin Oliveira, A. Dias

引用次数: 0

A performance comparison of bio-inspired behaviours for odour source localisation 气味源定位的生物启发行为的性能比较

2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) Pub Date : 2019-04-01 DOI: 10.1109/ICARSC.2019.8733627

João Macedo, Lino Marques, E. Costa

引用次数: 2

A GSPN Software Framework to Model and Analyze Robot Tasks 机器人任务建模与分析的GSPN软件框架

2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) Pub Date : 2019-04-01 DOI: 10.1109/ICARSC.2019.8733634

Carlos Azevedo, P. Lima

引用次数: 0

Hardware-in-the-loop simulation approach for the Robot at Factory Lite competition proposal 机器人在工厂生活竞赛提案的硬件在环仿真方法

2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) Pub Date : 2019-04-01 DOI: 10.1109/ICARSC.2019.8733649

José Lima, P. Costa, T. Brito, Luis Piardi

引用次数: 11

Monocular Visual Odometry Benchmarking and Turn Performance Optimization 单目视觉里程计基准测试与转弯性能优化

2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) Pub Date : 2019-04-01 DOI: 10.1109/ICARSC.2019.8733633

A. Aguiar, A. Sousa, F. Santos, Miguel Oliveira

{"title":"Monocular Visual Odometry Benchmarking and Turn Performance Optimization","authors":"A. Aguiar, A. Sousa, F. Santos, Miguel Oliveira","doi":"10.1109/ICARSC.2019.8733633","DOIUrl":"https://doi.org/10.1109/ICARSC.2019.8733633","url":null,"abstract":"Developing ground robots for crop monitoring and harvesting in steep slope vineyards is a complex challenge due to two main reasons: harsh condition of the terrain and unstable localization accuracy obtained with Global Navigation Satellite System. In this context, a reliable localization system requires an accurate and redundant information to Global Navigation Satellite System and wheel odometry based system. To pursue this goal we benchmark 3 well known Visual Odometry methods with 2 datasets. Two of these are feature-based Visual Odometry algorithms: Libviso2 and SVO 2.0. The third is an appearance-based Visual Odometry algorithm called DSO. In monocular Visual Odometry, two main problems appear: pure rotations and scale estimation. In this paper, we focus on the first issue. To do so, we propose a Kalman Filter to fuse a single gyroscope with the output pose of monocular Visual Odometry, while estimating gyroscope's bias continuously. In this approach we propose a non-linear noise variation that ensures that bias estimation is not affected by Visual Odometry resultant rotations. We compare and discuss the three unchanged methods and the three methods with the proposed additional Kalman Filter. For tests, two public datasets are used: the Kitti dataset and another built in-house. Results show that our additional Kalman Filter highly improves Visual Odometry performance in rotation movements.","PeriodicalId":198320,"journal":{"name":"2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122653458","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