Teaching a Drone to Accompany a Person from Demonstrations using Non-Linear ASFM

机译：使用非线性ASFM教授一个无人机陪伴一个人的示威活动

获取原文

页面导航

摘要
著录项
相似文献
相关主题

摘要

In this paper, we present a new method based on the Aerial Social Force Model (ASFM) to allow human-drone side-by-side social navigation in real environments. To tackle this problem, the present work proposes a new nonlinear-based approach using Neural Networks. To learn and test the rightness of the new approach, we built a new dataset with simulated environments and we recorded motion controls provided by a human expert tele-operating the drone. The recorded data is then used to train a neural network which maps interaction forces to acceleration commands. The system is also reinforced with a human path prediction module to improve the drone's navigation, as well as, a collision detection module to completely avoid possible impacts. Moreover, a performance metric is defined which allows us to numerically evaluate and compare the fulfillment of the different learned policies. The method was validated by a large set of simulations; we also conducted real-life experiments with an autonomous drone to verify the framework described for the navigation process. In addition, a user study has been realized to reveal the social acceptability of the method.

机译：在本文中，我们介绍了一种基于空中社会力量模型（ASFM）的新方法，以允许在真实环境中进行人机并排社会导航。为了解决这个问题，目前的工作提出了一种使用神经网络的新的非线性方法。要学习和测试新方法的正确性，我们建立了一个具有模拟环境的新数据集，我们录制了由人类专家提供的无人机提供的运动控制。然后，记录的数据用于训练一个神经网络，该神经网络映射交互力以加速命令。该系统也用人路径预测模块加强，以改善无人机的导航，以及碰撞检测模块，以完全避免可能的影响。此外，定义了性能度量，其允许我们在数值上评估和比较不同学习策略的实现。该方法由一大集模拟验证;我们还通过自主无人机进行了现实实验，以验证导航过程描述的框架。此外，已经实现了用户学习，以揭示该方法的社会可接受性。

著录项

来源
《IEEE/RSJ International Conference on Intelligent Robots and Systems》|2019年|p798-1626|共7页
会议地点
作者
Anais Garrell; Carles Coll; Rene Alquezar; Alberto Sanfeliu;
展开▼
作者单位

展开▼
会议组织
原文格式 PDF
正文语种
中图分类 TB904.1-53;
关键词

相似文献

外文文献
中文文献
专利

1. Demonstration and application of diffusive and ballistic wave propagation for drone-to-ground and drone-to-drone wireless communications [J] . Peter J. Burke Scientific reports. . 2020,第1期

机译：无人机与地面和无人机对无人机无线通信的扩散和弹性波传播的示范与应用
2. Influences on British South Asian women's choice of teaching as a career: “you're either a career person or a family person; teaching kind of fits in the middle” [J] . Graham Butt, Lin MacKenzie, Russell Manning Educational Review . 2010,第1期

机译：对英国南亚女性选择职业教学的影响：“您是职业人士还是家庭人士；讲授适合的中间语言”
3. Person-Centered Employment Planning Teams: A Demonstration Project to Enhance Employment and Training Outcomes for Persons with Disabilities Accessing the One-Stop Career Center System [J] . Robert Gervey Ni Gao Donna Tillman Karen Dickel Jim Kneubuehl Journal of Rehabilitation . 2009,第2期

机译：以人为中心的就业计划团队：一个示范项目，旨在提高残疾人使用一站式职业中心系统的就业和培训成果
4. Teaching a Drone to Accompany a Person from Demonstrations using Non-Linear ASFM [C] . Anais Garrell, Carles Coll, Rene Alquezar, IEEE/RSJ International Conference on Intelligent Robots and Systems . 2019

机译：使用非线性ASFM教授一个无人机陪伴一个人的示威活动
5. DRAMATICALLY NEGATIVE TEACHING TECHNIQUE AS SUPPLEMENTAL TO POSITIVE INSTRUCTION COMPARED WITH TRADITIONAL TEACHING TECHNIQUE IN INDUSTRIAL ARTS DEMONSTRATIONS. [D] . LARUE, JAMES PARKER. 1968

机译：传统技术教学中与传统教学技术相辅相成的戏剧性负教学技术。
6. Evaluation of the teaching recovery techniques community-based intervention for accompanied refugee children experiencing post-traumatic stress symptoms (Accompanied refugeeS In Sweden Trial; ASsIST): study protocol for a cluster randomised controlled trial [O] . Georgina Warner, Natalie Durbeej, Raziye Salari, 2020

机译：评估教学恢复技术的伴随难民儿童的伴随儿童伴随着创伤后应力症状（瑞典审判中的陪同性;协助）：用于集群随机对照试验的研究方案
7. EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed TarekShahriar Abstract—An EMD-chaos based approach is proposed todiscriminate EEG signals corresponding to healthy persons,and epileptic patients during seizure-free intervals and seizureattacks. An electroencephalogram (EEG) is first empiricallydecomposed to intrinsic mode functions (IMFs). The nonlineardynamics of these IMFs are quantified in terms of the largestLyapunov exponent (LLE) and correlation dimension (CD).This chaotic analysis in EMD domain is applied to a large groupof EEG signals corresponding to healthy persons as well asepileptic patients (both with and without seizure attacks). It isshown that the values of the obtained LLE and CD exhibitfeatures by which EEG for seizure attacks can be clearlydistinguished from other EEG signals in the EMD domain.Thus, the proposed approach may aid researchers in developingeffective techniques to predict seizure activities. Index Terms—Electroencephalogram (EEG), empiricalmode decomposition (EMD), largest Lyapunov exponent (LLE),correlation dimension (CD), epileptic seizures. The Authors are with the Electrical and Electronic EngineeringDepartment, Bangladesh University of Engineering and Technology,Dhaka-1000, Bangladesh (e-mail: imamul@eee.buet.ac.bd) PDF Cite: S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed Tarek Shahriar, "EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain," International Journal of Computer and Electrical Engineering vol. 4, no. 3, pp. 326-330, 2012. PREVIOUS PAPER Perception of Emotions Using Constructive Learningthrough Speech NEXT PAPER Physical Layer Impairments Aware OVPN Connection Selection Mechanisms Copyright © 2008-2013. International Association of Computer Science and Information Technology Press (IACSIT Press) [O] . S. M. Shafiul Alam, Syed TarekShahriar 2012

机译：EEG信号在EMD域S. S. Shafiul Alam，S中的非线性动力学使用非线性动力学。 M. Shafiul Alam，Aurangozeb和Syed Tarekshahriar摘要 - 基于EMD Chaos的方法，提出了对应于健康人的EEG信号，癫痫发作期间的癫痫患者和Seizureattacks。脑电图（EEG）首先被凭经上分解为内在模式功能（IMF）。这些IMF的非线性动力学在最大范围的指数（LLE）和相关尺寸（CD）方面是量化的。本域中的混沌分析应用于与健康人相对应的大型脑电图（Asepileptic患者）（两者都有癫痫发作）。因此，所获得的LLE和CD表展的价值可以从EMD领域的其他EEG信号中清晰地区分脑电图的表达展示。本拟议的方法可以帮助研究人员以预测癫痫发作的癫痫发作技术。索引术语 - 脑电图（EEG），仿真态分解（EMD），最大的Lyapunov指数（LLE），相关维度（CD），癫痫发作。作者与电气电子和电子工程公司，孟加拉国工程和技术大学，孟加拉国达卡 - 1000（电子邮件：imamul@eee.buet.ac.bd）pdf cite：s. m. shafiul Alam，s。 M. Shafiul Alam，Aurangozeb和Syed Tarek Shahriar，“EEG信号歧视在EMD领域的非线性动态，”计算机电气工程卷国际杂志。 4，不。 3，pp。326-330,2012，上一篇论文对情绪的看法，使用建设性的学习言论下一篇论文物理层障碍意识到OVPN连接选择机制版权所有©2008-2013。国际计算机科学与信息技术协会出版社（IACSIT Press）

Teaching a Drone to Accompany a Person from Demonstrations using Non-Linear ASFM

摘要

著录项

相似文献

相关主题

期刊订阅