2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR)最新文献_第4页

Speed-invariant terrain roughness classification and control based on inertial sensors 基于惯性传感器的速度不变地形粗糙度分类与控制

2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR) Pub Date : 2017-11-01 DOI: 10.1109/SBR-LARS-R.2017.8215332

Felipe G. Oliveira, Elerson R. S. Santos, A. A. Neto, M. Campos, D. Macharet

{"title":"Speed-invariant terrain roughness classification and control based on inertial sensors","authors":"Felipe G. Oliveira, Elerson R. S. Santos, A. A. Neto, M. Campos, D. Macharet","doi":"10.1109/SBR-LARS-R.2017.8215332","DOIUrl":"https://doi.org/10.1109/SBR-LARS-R.2017.8215332","url":null,"abstract":"Nowadays, it is notorious the increasing use of autonomous vehicles in different outdoor field applications such as agriculture, the mining industry, environmental monitoring, among others. In this context, the determination of the traversability level of a terrain is a fundamental task for safe and efficient navigation of Autonomous Ground Vehicles (AGVs) in unstructured unknown outdoor environments. Information like roughness of the ground is important when velocity control and other dynamic issues are concerned. However, most of the techniques in the literature use camera or lidar sensors to evaluate the ground around the robot, leading to complex and high cost systems. More simpler methods use only inertial sensors to estimate the roughness properties of the terrain, however they can be very sensitive to the robot's speed. In this paper, we propose a novel classifier capable of cluster different terrains based only on acceleration data provided by an Inertial Measurement Unit (IMU). We demonstrate with real-world experiments that, for different forward velocities, the mean accuracy of the classification exceeds 80 %. Our method also incorporates a controller to regulate the speed according to the terrain identified by the robot in order to avoid abrupt movements over terrain changes.","PeriodicalId":435860,"journal":{"name":"2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125574785","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: 10

Proposal and comparison of trajectory tracking strategies for mobile robots 移动机器人轨迹跟踪策略的提出与比较

2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR) Pub Date : 2017-11-01 DOI: 10.1109/SBR-LARS-R.2017.8215311

Valentim Ernandes Neto, R. M. Fonseca, A. Brandão

引用次数: 1

Experimental measurement of parameters for modeling a differentia drive soccer robot 差分驱动足球机器人建模参数的实验测量

2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR) Pub Date : 2017-11-01 DOI: 10.1109/SBR-LARS-R.2017.8215329

Bernardo P. Veronese, I. F. Okuyama, F. C. R. Pinheiro, M. Maximo, L. C. S. Goes

引用次数: 0

Robotic swarms coordination strategies for minimizing group target congestion 最小化群体目标拥塞的机器人群体协调策略

2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR) Pub Date : 2017-11-01 DOI: 10.1109/SBR-LARS-R.2017.8215286

Gustavo P. M. Oliveira, Fabrício R. Inácio, D. Macharet

{"title":"Robotic swarms coordination strategies for minimizing group target congestion","authors":"Gustavo P. M. Oliveira, Fabrício R. Inácio, D. Macharet","doi":"10.1109/SBR-LARS-R.2017.8215286","DOIUrl":"https://doi.org/10.1109/SBR-LARS-R.2017.8215286","url":null,"abstract":"The use of Multi-Robot Systems presents several advantages like increased robustness and, in most cases, time reduction to accomplish a task. In this context, Robotic Swarms is generally related to very large groups of robots. The congestion problem within the mobile robotics field is a well-known field of research. The problem occurs when a large number of autonomous robots tries to reach a common target in the environment at the same time. This paper addresses the congestion problem considering a robotic swarm formed by distinct groups of agents, and we aim to minimize the period of time agents of the same group take to reach the target. We propose two different approaches to optimize the navigation process of the entire group, however, prioritizing members of the same group. The first strategy gives to each group a priority based on the average distance between its members and the target. This team priority will define which robots will move into the target first. The second one states which robots will move based on a randomized group priority. The proposed methodology was evaluated through several experiments in a simulated environment, providing statistical insight on the performance.","PeriodicalId":435860,"journal":{"name":"2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR)","volume":"471 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116790142","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

Embedded mosaic generation using aerial images 嵌入镶嵌生成使用航空图像

2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR) Pub Date : 2017-11-01 DOI: 10.1109/SBR-LARS-R.2017.8215272

V. Guizilini, D. Sales, M. Lahoud, L. Jorge

引用次数: 4

Stability analysis for mobile robots with different time-scales based on unsupervised competitive neural networks 基于无监督竞争神经网络的不同时标移动机器人稳定性分析

2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR) Pub Date : 2017-11-01 DOI: 10.1109/SBR-LARS-R.2017.8215270

C. P. Fernandez, Jés Jesus Fiais Cerqueira

{"title":"Stability analysis for mobile robots with different time-scales based on unsupervised competitive neural networks","authors":"C. P. Fernandez, Jés Jesus Fiais Cerqueira","doi":"10.1109/SBR-LARS-R.2017.8215270","DOIUrl":"https://doi.org/10.1109/SBR-LARS-R.2017.8215270","url":null,"abstract":"The dynamics of complex neural networks modelling self-organized process in cortical maps, like unsupervised competitive neural networks (UCNN), are based on the standard competitive learning law to determine the best-matching representant among all neurons for a given input. However, UCNNs include aspects of long and short-term memory, which are characterized by an equation of neural activity as fast part and an equation of neural synaptic modification as a slow part. For close-loop systems of mobile robots with different time-scales UCNNs can be used to represent the violation of kinematic constraints (like neural activity) and generalized coordinates (like synaptic modifications). Furthermore, UCNNs can act as powerful preprocessors of other neural networks with supervised learning because the unsupervised learning part usually has low computational effort. In this way, the overall computational effort will be considerably reduced. The present work uses the mutual interference between neuron and unsupervised learning of an UCNN in order to analyse the local and global asymptotic stability of mobile robots that not exactly satisfying kinematic constraints. To validate the proposed analysis the equilibrium point of UCNN model will be mathematically analysed by using quadratic-type Lyapunov functions and compared with a model based on a fully supervised learning rule. The results shows that the model based on UCNN converges toward a small ball of the origin with a better performance than the model based on a fully supervised learning rule.","PeriodicalId":435860,"journal":{"name":"2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122457572","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

An unsupervised machine learning algorithm for visual target identification in the context of a robotics competition 机器人竞赛中用于视觉目标识别的无监督机器学习算法

2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR) Pub Date : 2017-11-01 DOI: 10.1109/SBR-LARS-R.2017.8215302

Camila Barbosa, O. Santana, B. Silva

引用次数: 3

Co-occurrence matrices for 3D shape classification 三维形状分类的共现矩阵

2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR) Pub Date : 2017-11-01 DOI: 10.1109/SBR-LARS-R.2017.8215281

Carlos Andre Braile Przewodowski Filho, F. Osório

引用次数: 0

External hybrid force/pose controller for manipulator robots using dual quaternion algebra 基于对偶四元数代数的机械臂外混合力/位姿控制器

2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR) Pub Date : 2017-11-01 DOI: 10.1109/SBR-LARS-R.2017.8215334

Diana Sabina Alban, Bruno Vilhena Adorno

引用次数: 1

Construction, identification and instrumentation of a low cost quadcopter research platform 低成本四轴飞行器研究平台的构建、鉴定与仪器仪表

2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR) Pub Date : 2017-11-01 DOI: 10.1109/SBR-LARS-R.2017.8215299

Said Alvarado, N. Certad, Gerardo Fernández-López, Manuel Gonzalez

引用次数: 2