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International Conference on Systems and Control (ICSC)

作者： Fethi Demim Abdelghani Boucheloukh Abdelkrim Nemra Kahina Louadj Mustapha Hamerlain Abdelouahab Bazoula Zakaria Mehal Ecole Militaire Polytechnique Laboratory Robotics and Automation Algiers Algeria Department of Automation National Polytechnic School ENP El Harrach Algiers Algeria LIMPAF University of Bouira Algeria CDTA Center for Development of Advanced Technologies Algiers Algeria

ISBN: (纸本)9781509039616

This paper aims at presenting a solution to the Simultaneous Localization and Mapping (SLAM) problem of Unmanned Ground Vehicles (UGV) by combining information given by an odometer and a laser range finder. The most popular solutions to the SLAM problem are EKF-SLAM and the FAST-SLAM algorithms. The first one solution, have some important limitations which have need of an accurate process and an observation model, be affected by the linearization problem, the second is not suitable for real time implementation. Therefore, a new adaptive approach based on the Smooth Variable Structure Filter (ASVSF) is proposed to solve the UGV SLAM problem. Hence, the adaptive SVSF-SLAM algorithm is proposed with an original formulation. The main contribution of this paper is to introduce a covariance matrix to assess the estimated uncertainty of the SVSF. This new robust algorithm is validated, compared to EKF/SVSF-SLAMalgorithms and the satisfactory values of the UGV position error are obtained. Simulation results demonstrated that the proposed adaptive SVSF-SLAM algorithm is very robust face modeling uncertainties and noises and it has significantly improved the performance of the estimation process.

关键词： Simultaneous localization and mapping Service robots Estimation Uncertainty Adaptation models Covariance matrices

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A unified leader-follower scheme for mobile robots with uncalibrated on-board camera

A unified leader-follower scheme for mobile robots with unca...

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2017 IEEE International Conference on robotics and automation, ICRA 2017

作者： Guo, Dejun Wang, Hesheng Chen, Weidong Liu, Ming Xia, Zeyang Leang, Kam K. Lab University of Utah Robotics Center Salt Lake CityUT84112 United States Department of Automation Shanghai Jiao Tong University Shanghai200240 China Department of Electronics and Computer Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong Institute of Biomedical and Health Engineering Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9781509046331

This paper studies the problem of image-based leader-follower formation control for mobile robots, where the controller is designed independently of the leader's motion. An adaptive control scheme, which is suitable for both omnidirectional and perspective cameras, is proposed. The proposed approach avoids the need for accurate calibration of the extrinsic parameters of the omnidirectional camera as well as the intrinsic and extrinsic parameters of perspective camera. Additionally, the coefficients of the plane where the feature point moves relative to the camera frame can be uncertain. These uncertain constant parameters are estimated using an adaptive estimator. Uniform Semi-global Practical Asymptotic Stability (USPAS) of the system is shown using the Lyapunov approach. Experimental results are presented to demonstrate the effectiveness of the proposed control scheme. © 2017 IEEE.

关键词： Mobile robots

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A vision based system for underwater docking

arXiv

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arXiv 2017年

作者： Liu, Shuang Ozay, Mete Okatani, Takayuki Xu, Hongli Sun, Kai Lin, Yang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Graduate School of Information Sciences Tohoku University Sendai Miyagi Japan RIKEN Center for Advanced Intelligence Project Tokyo Japan

Autonomous underwater vehicles (AUVs) have been deployed for underwater exploration. However, its potential is confined by its limited on-board battery energy and data storage capacity. This problem has been addressed using docking systems by underwater recharging and data transfer for AUVs. In this work, we propose a vision based framework for underwater docking following these systems. The proposed framework comprises two modules;(i) a detection module which provides location information on underwater docking stations in 2D images captured by an on-board camera, and (ii) a pose estimation module which recovers the relative 3D position and orientation between docking stations and AUVs from the 2D images. For robust and credible detection of docking stations, we propose a convolutional neural network called Docking Neural Network (DoNN). For accurate pose estimation, a perspective-npoint algorithm is integrated into our framework. In order to examine our framework in underwater docking tasks, we collected a dataset of 2D images, named Underwater Docking Images Dataset (UDID), in an experimental water pool. To the best of our knowledge, UDID is the first publicly available underwater docking dataset. In the experiments, we first evaluate performance of the proposed detection module on UDID and its deformed variations. Next, we assess the accuracy of the pose estimation module by ground experiments, since it is not feasible to obtain true relative position and orientation between docking stations and AUVs under water. Then, we examine the pose estimation module by underwater experiments in our experimental water pool. Experimental results show that the proposed framework can be used to detect docking stations and estimate their relative pose efficiently and successfully, compared to the state-of-the-art baseline systems. Copyright © 2017, The Authors. All rights reserved.

关键词： Autonomous underwater vehicles

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A novel extended potential field controller for use on aerial robots

A novel extended potential field controller for use on aeria...

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2016 IEEE International Conference on automation Science and Engineering, CASE 2016

作者： Woods, Alexander C. Lay, Hung M. Ha, Quang P. Advanced Robotics and Automation Laboratory Department of Computer Science and Engineering University of Nevada RenoNV89557 United States School of Electrical Mechanical and Mechatronic Systems University of Technology Sydney Australia

ISBN: (纸本)9781509024094

Unmanned Aerial Vehicles (UAV), commonly known as drones, have many potential uses in real world applications. Drones require advanced planning and navigation algorithms to enable them to safely move through and interact with the world around them. This paper presents an extended potential field controller (ePFC) which enables an aerial robot, or drone, to safely track a dynamic target location while simultaneously avoiding any obstacles in its path. The ePFC outperforms a traditional potential field controller (PFC) with smoother tracking paths and shorter settling times. The proposed ePFC's stability is evaluated by Lyapunov approach, and its performance is simulated in a Matlab environment. Finally, the controller is implemented on an experimental platform in a laboratory environment which demonstrates the effectiveness of the controller. © 2016 IEEE.

关键词： Controllers

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Miniature Bioreactors: On-Demand Coalescence and Splitting of Liquid Marbles and Their Bioapplications (Adv. Sci. 10/2019)

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advanced Science 2019年第10期6卷 1970061-1970061页

作者： Ben Wang Kai Fung Chan Fengtong Ji Qianqian Wang Philip Wai Yan Chiu Zhiguang Guo Li Zhang Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong China Department of Biomedical Engineering The Chinese University of Hong Kong Hong Kong China Chow Yuk Ho Technology Centre for Innovative Medicine The Chinese University of Hong Kong Hong Kong China Department of Surgery The Chinese University of Hong Kong Hong Kong China State Key Laboratory of Solid Lubrication Lanzhou Institute of Chemical Physics Chinese Academy of Science Lanzhou 730000 China Hubei Collaborative Innovation Centre for Advanced Organic Chemical Materials and Ministry of Education Key Laboratory for the Green Preparation and Application of Functional Materials Hubei University Wuhan 430062 China T Stone Robotics Institute The Chinese University of Hong Kong Hong Kong China

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Cooperative load transport based on fuzzy logic controllers

Cooperative load transport based on fuzzy logic controllers

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IEEE/IAS International Conference on Industry Applications (INDUSCON)

作者： Marco Antonio Teixeira Higor Barbosa Santos Andre Schneider de Oliveira João Alberto Fabro Lucia Valeria Ramos de Arruda Flavio Neves-Jr Federal University of Technology — Parana Curitiba Parana Brazil Automation and Advanced Control System Laboratory (LASCA) Advanced Laboratory of Embedded Systems and Robotics (LASER)

This work presents the use of multiple mobile robots to perform a common transportation task. The main objective is to perform a navigation with a shared cargo, which allows the transport of objects with high payload or high sizes. Two robots are virtually linked through two Fuzzy controllers, one to control distance and another for orientation. A depth camera on the trailer's robot is used to measure the distance and orientation of the leader robot. The proposed approach is experimentally validated with two standard Pioneer mobile robots that collaboratively carry a large box.

关键词： Robot kinematics Robot sensing systems Mobile robots Payloads Three-dimensional displays Lasers

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A shared control method for online human-in-the-loop robot learning based on Locally Weighted Regression

A shared control method for online human-in-the-loop robot l...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Luka Peternel Erhan Oztop Jan Babic Advanced Robotics Istituto Italiano di Tecnologia Genoa Italy Robotics Laboratory Ozyegin University Istanbul Turkey Dept. of Automation Biocybernetics and Robotics Jozef Stefan Institute Ljubljana Slovenia

ISBN: (纸本)9781509037636

We propose a novel method that arbitrates the control between the human and the robot actors in a teaching-by-demonstration setting to form synergy between the two and facilitate effective skill synthesis on the robot. We employed the human-in-the-loop teaching paradigm to teleoperate and demonstrate a complex task execution to the robot in real-time. As the human guides the robot to perform the task, the robot obtains the skill online during the demonstration. To encode the robotic skill we employed Locally Weighted Regression that fits local models to specific state region of the task based on the human demonstration. If the robot is in the state region where no local models exist, the control over the robotic mechanism is given to the human to perform the teaching. When local models are gradually obtained in that region, the control is given to the robot so that the human can examine its performance already during the demonstration stage, and take actions accordingly. This enables a co-adaptation between the agents and contributes to a faster and more efficient teaching. As a proof-of-concept, we realised the proposed robot teaching system on a haptic robot with the task of generation of a desired vertical force on a horizontal plane with unknown stiffness properties.

关键词： Robot Human Control Methods Robot learning Pedagogy Teaching Geographically Weighted Regression Task execution

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Multi-stage feature learning based object recognition and 3D pose estimation with kinect 6

Multi-stage feature learning based object recognition and 3D...

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6th International Conference on Information Science and Technology, ICIST 2016

作者： Zeng, Wei Liang, Guoyuan Guangdong, Can Wang Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China Dept. Mechanical and Automation Engineering Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781509012206

Impressive achievements have been achieved over the years in object recognition and 3D pose estimation while detecting objects and estimating their 3D poses reliably is still a very challenging problem, especially for texture-less objects in heavily cluttered scenes. In this paper, we introduce an improved approach based on multi-stage feature learning to identify object as well as their 3D orientation efficiently. Our approach is motivated by visual neuroscience models. Currently similar architectures have been successfully applied to pedestrian detection, traffic recognition, face representation, etc. We compute the feature descriptors by multi-stage convolutional neural networks (CNNs) which could map the object identity and 3D poses to the Euclidean distance space by evaluating the similarity between descriptors. By contrast with classical approaches, our method relies on fast and approximate Nearest Neighbor (NN) matching to solve the large scale problems instead of one classifier per object or multi-class classifiers whose complexity grows rapidly with the number of objects. The experiments of detecting poorly-textured objects in cluttered scenarios have been carried out to verify the effectiveness and efficacy of the proposed approach. © 2016 IEEE.

关键词： Object recognition

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Rotating soft-Tail millimeter-scaled swimmers with superhydrophilic or superhydrophobic surfaces 6

Rotating soft-Tail millimeter-scaled swimmers with superhydr...

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6th IEEE RAS/EMBS International Conference on Biomedical robotics and Biomechatronics, BioRob 2016

作者： Xu, Tiantian Vong, Chi-Ian Wang, Ben Liu, Lianqing Wu, Xinyu Zhang, Li Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Shatin NT Hong Kong SAR Hong Kong State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Shenzhen Research Institute Chinese University of Hong Kong Shenzhen China Chow Yuk Ho Technology Centre for Innovative Medicine Chinese University of Hong Kong Hong Kong SAR Hong Kong

ISBN: (纸本)9781509032877

Microswimmers capable of propulsion at low Reynolds numbers have great potential for numerous applications. Several kinds of artificial microswimmers, actuated by magnetic fields, with rigid helical tails have been developed. In previous works, we demonstrated that a magnetic swimmer with a soft tail could form a helical shape during rotation to propel itself at low Reynolds numbers. The advantage of compliant structures is that the high softness makes swimmers more adaptive in confined or complex environments. The interfacial friction drags are reduced by using superhydrophobic surfaces. Therefore, this paper aims to study the influence of surface and interface properties, particularly the hydrophilicity and hydrophobicity of the soft tail surface, on the swimming performance. For this, we compared the swimming performance of two millimeter-scaled swimmers with a superhydrophilic soft tail and a superhydrophobic soft tail, respectively, in viscous liquids. The two swimmers exhibit different dynamic morphologies and swimming performance with the same input parameters. The swimmer with a superhydrophobic soft tail shows higher swimming velocity than that with a superhydrophilic soft tail, except in pure glycerol. The present work provides useful informations for selecting surface coating of swimmers with soft tails at low Reynolds numbers. © 2016 IEEE.

关键词： Propulsion

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A Novel Extended Potential Field Controller for Use on Aerial Robots

A Novel Extended Potential Field Controller for Use on Aeria...

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IEEE International Conference on automation Science and Engineering

作者： Alexander C. Woods Hung M. La Quang P. Ha Advanced Robotics and Automation Laboratory Department of Computer Science and Engineering University of Nevada Reno 89557 USA School of Electrical Mechanical and Mechatronic Systems University of Technology Sydney Australia

ISBN: (纸本)9781509024100

关键词： Drones Navigation Robot sensing systems Target tracking Stability analysis

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