2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)最新文献_第6页

On statistical analysis for shepherd guidance system 牧童引导系统的统计分析

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324588

Y. Tsunoda, Yuichiro Sueoka, K. Osuka

{"title":"On statistical analysis for shepherd guidance system","authors":"Y. Tsunoda, Yuichiro Sueoka, K. Osuka","doi":"10.1109/ROBIO.2017.8324588","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324588","url":null,"abstract":"This paper is concerned with group navigation which utilizes strong interaction between two types of mobile agents, what we call sheepdog agent (dog agent) and sheep agent. Natural sheepdog system exhibits that one or a small number of sheepdog guides large population of sheep, up to a thousand, to a pre-determined goal position thanks to the characteristics of the sheep; they live in a flock and they hate a dog. From the viewpoint of multi-robots navigation, the sheepdog system will help us to grasp some key tricks for control strategies; sufficient and minimum number of controllers will manipulate many degree of freedoms. After deriving mathematical models of sheep flocks and a shepherd dog, we propose to conduct a statistical approach for understanding the navigation mechanism; we mainly focus on the interaction factor, flocking effect, and the dog performance. Firstly, we dare to run repeated simulations by adding statistical errors in the interaction vector between sheep flocks and the dog. Secondly, we examine the navigation performance by changing the flock characteristics: the size of individual attraction/alignment zone. Finally, we analyze the relation between the speed of dog and the sheepdog-like navigation performance.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116902326","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: 8

Continuous reinforcement learning from human demonstrations with integrated experience replay for autonomous driving 从人类演示中持续强化学习，集成自动驾驶经验回放

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324787

Sixiang Zuo, Zhiyang Wang, Xiaorui Zhu, Y. Ou

{"title":"Continuous reinforcement learning from human demonstrations with integrated experience replay for autonomous driving","authors":"Sixiang Zuo, Zhiyang Wang, Xiaorui Zhu, Y. Ou","doi":"10.1109/ROBIO.2017.8324787","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324787","url":null,"abstract":"As a promising subfield of machine learning, Reinforcement Learning (RL) has drawn increasing attention among the academia as well as the public. However, the practical application of RL is still restricted by a variety of reasons. The two most significant challenges of RL are the large exploration domain and the difficulty to converge. Integrating RL with human expertise is technically an interesting way to accelerate the exploration and increase the stability. In this work, we propose a continuous reinforcement learning method which integrates Deep Deterministic Policy Gradient (DDPG) with human demonstrations. The proposed method uses a combined loss function for updating the actor and critic networks. In addition, the experience replay buffer is also drawn from different transition data samples to make the learning more stable. The proposed method is tested with a popular RL task, i.e. the autonomous driving, by simulations with TORCS environment. Experimental results not only show the effectiveness of our method in improving the learning stability, but also manifest the potential capability of our method in mastering human preferences.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116473795","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

An application of a generalized architecture to an autonomous underwater vehicle 广义结构在自主水下航行器中的应用

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324405

Changlong Lin, Guoliang Zhang, Jing Li, Yan Chen, Yiwen Zhang, Yiping Li

引用次数: 0

Imitating humans: Humanoid gait design based on energy exchange 仿人:基于能量交换的仿人步态设计

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324811

Noel Maalouf, I. Elhajj, Elie A. Shammas, Daniel C. Asmar

引用次数: 0

Learning to detect slip for stable grasping 学习检测滑动以稳定抓握

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324455

Luxuan Li, F. Sun, Bin Fang, Zhudong Huang, Chao Yang, Mingxuan Jing

引用次数: 9

A coordination control for a wearable walking-assist robot 一种可穿戴行走辅助机器人的协调控制

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324654

Xia Zhang, Tianhong Luo, Atsushi Tsukahara, M. Hashimoto

{"title":"A coordination control for a wearable walking-assist robot","authors":"Xia Zhang, Tianhong Luo, Atsushi Tsukahara, M. Hashimoto","doi":"10.1109/ROBIO.2017.8324654","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324654","url":null,"abstract":"The biologically-inspired motion control theory was introduced to ameliorate human-robot interaction flexibility and multi-joint autonomy in walking assist. A new type of human-robot interaction (HRI)-based coordination control method which combined a hip CPG (central pattern generator) control, a knee hierarchical impedance control and a hip-knee linkage control was explored. Firstly, the characteristics of CPGs self-oscillation and external communication were utilized to obtain the ideal master/slave hip joint trajectories, and CPG-units symmetrical inhibition were established to maintain anti-phase of the left and right hip joints. Secondly, according to the requirements of gait, a high and low hierarchical impedance control law was designed, and thus the knee joint torques during support stage and swing stage were obtained respectively. Finally, a hip-knee joints linkage mechanism was built to incorporate the hip joint CPG control with the knee-joint impedance control, and thus natural and relevant hip-knee joints trajectory was realized. The stability of the HRI-based coordination control method was researched by using Lyapunov stability theory. Walking experiments were carried out to certificate that the proposed control method was effective in generating nature hip-knee joints trajectory in walking.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124696181","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

Development of a tendon-driven mechanism with liquid circulation system for improving wear resistance 用于提高耐磨性的带液体循环系统的肌腱驱动机构的研制

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324658

Shouta Miyake, Shunsuke Nagahama, S. Sugano

引用次数: 1

Distributed control of a robotic network for protection of a region from intruders 机器人网络的分布式控制，以保护一个区域免受入侵者的侵害

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324516

A. Savkin, A. Marzoughi

引用次数: 8

Hexapod robot kinematics modeling and tripod gait design based on the foot end trajectory 基于足端轨迹的六足机器人运动学建模及三脚架步态设计

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324813

Jianbo Sun, J. Ren, Yinglian Jin, Binrui Wang, Dijian Chen

引用次数: 10

A method for collision free navigation of non-holonomic 3D robots in unknown tunnel like environments 非完整三维机器人在未知类隧道环境中的无碰撞导航方法

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324537

A. Savkin, Chao Wang

引用次数: 4