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IEEE International Conference on robotics and Biomimetics

作者： Yanan Liu Rui Fan Bin Yu M. Junaid Bocus Ming Liu Hepeng Ni Jiahe Fan Shixin Mao Bristol Robotics Laboratory University of Bristol Bristol United Kingdom Hong Kong University of Science and Technology Kowloon HK Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong University of Bristol Bristol Bristol GB Department of Electrical and Electronic Engineering University of Bristol Bristol United Kingdom School of Mechanical Engineering Shandong University Jinan China School of Communication Engineering Jilin University Changchun China Shenzhen Sanhang Industrial Technology Research Institute Shenzhen China

ISBN: (纸本)9781728103785;9781728103778

Mobile robots are becoming increasingly important both for individuals and industries. Mobile robotic technology is not only utilised by experts in this field but is also very popular among amateurs. However, implementing a mobile robot to perform tasks autonomously can be expensive because of the need for various types of sensors and the high price of robot platforms. Hence, in this paper we present a mobile robot localisation and navigation system which uses a LEGO ultrasonic sensor in an indoor map based on the LEGO MINDSTORM NXT. This provides an affordable and ready-to-use option for most robot fans. In this paper, an effective method is proposed to extract useful information from the distorted readings collected by the ultrasonic sensor. Then, the particle filter is used to localise the robot. After robot's position is estimated, a sampling-based path planning method is proposed for the robot navigation. This method reduces the robot accumulative motion error by minimising robot turning times and covering distances. The robot localisation and navigation algorithms are implemented in MATLAB. Simulation results show an average accuracy between 1 and 3 cm for three different indoor map locations. Furthermore, experiments performed in a real setup show the effectiveness of the proposed methods.

关键词： Mobile robot LEGO NXT Localisation and navigation Particle filter Path plan

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Design and Testing of a Recycled 3D Printed and Foldable Unmanned Aerial Vehicle for Remote Sensing

Design and Testing of a Recycled 3D Printed and Foldable Unm...

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International Conference on Unmanned Aircraft Systems

作者： Akif Mosaddek Hrushi K. R. Kommula Felipe Gonzalez Electrical and Aerospace Engineering Queensland University of Technology (QUT) Brisbane Robotics and Autonomous systems at the School of Electrical Engineering and Computer Science (EECS) Queensland University of Technology (QUT) Brisbane

The demand for UAVs (Unmanned Aerial Vehicles) has drastically increased within the past few years, with proven efficiency for remote sensing use. This paper analyses the feasibility of utilizing recycled plastics from bottles such as, Polyethylene Terephthalate (PET) as 3D printing filament, in order to rapidly print foldable UAV airframes for remote sensing use. Previous work has failed to effectively address the process of 3D printing UAVs with a lack of literature pertaining to the ability of 3D printing UAVs with recycled materials and the environmental effects associated with this. To address this issue, this paper presents results analyzing the material properties of commonly used 3D printing filaments with that of the recycled filament, which has proven to be effective in use for this application. This new approach in manufacturing UAVs is expected to significantly benefit the low-cost manufacturing of UAVs, reducing the time taken to obtain UAVs, expanding the operational scope of these systems all whilst reducing the detrimental effects to the environment without any loss of functionality.

关键词： Three-dimensional printing Testing Three-dimensional displays Programmable logic arrays Strain Solid modeling Unmanned aerial vehicles

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Bayesian optimization using domain knowledge on the ATRIAS biped

arXiv

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arXiv 2017年

作者： Rai, Akshara Antonova, Rika Song, Seungmoon Martin, William Geyer, Hartmut Atkeson, Christopher G. Robotics Institute School of Computer Science Carnegie Mellon University United States Robotics Perception and Learning Csc Kth Royal Institute of Technology Stockholm

Controllers in robotics often consist of expert-designed heuristics, which can be hard to tune in higher dimensions. It is typical to use simulation to learn these parameters, but controllers learned in simulation often don't transfer to hardware. This necessitates optimization directly on hardware. However, collecting data on hardware can be expensive. This has led to a recent interest in adapting data-efficient learning techniques to robotics. One popular method is Bayesian Optimization (BO), a sample-efficient black-box optimization scheme, but its performance typically degrades in higher dimensions. We aim to overcome this problem by incorporating domain knowledge to reduce dimensionality in a meaningful way, with a focus on bipedal locomotion. In previous work, we proposed a transformation based on knowledge of human walking that projected a 16-dimensional controller to a 1-dimensional space. In simulation, this showed enhanced sample efficiency when optimizing human-inspired neuromus-cular walking controllers on a humanoid model. In this paper, we present a generalized feature transform applicable to non-humanoid robot morphologies and evaluate it on the ATRIAS bipedal robot - in simulation and on hardware. We present three different walking controllers;two are evaluated on the real robot. Our results show that this feature transform captures important aspects of walking and accelerates learning on hardware and simulation, as compared to traditional BO. Copyright © 2017, The Authors. All rights reserved.

关键词： Controllers

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Wearable Electronics: Self‐Bondable and Stretchable Conductive Composite Fibers with Spatially Controlled Percolated Ag Nanoparticle Networks: Novel Integration Strategy for Wearable Electronics (Adv. Funct. Mater. 49/2020)

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Advanced Functional Materials 2020年第49期30卷 2070321-2070321页

作者： Chaebeen Kwon Duhwan Seong Jeongdae Ha Dongwon Chun Jee‐Hwan Bae Kukro Yoon Minkyu Lee Janghoon Woo Chihyeong Won Seungmin Lee Yongfeng Mei Kyung‐In Jang Donghee Son Taeyoon Lee Nanobio Device Laboratory School of Electrical and Electronic Engineering Yonsei University 50 Yonsei‐ro Seodaemun‐gu Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering Sungkyunkwan University 2066 Seobu‐ro Jangan‐gu Suwon‐si Gyeonggi‐do 16419 Republic of Korea Department of Robotics Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) 333 Techno Jungang‐daero Hyeonpung‐eup Dalseong‐gun Daegu 42988 Republic of Korea Advanced Analysis Center Korea Institute of Science and Technology (KIST) 5 Hwarang‐ro 14‐gil Seongbuk‐gu Seoul 02792 Republic of Korea Department of Materials Science Fudan University Shanghai 200438 P. R. China

In article number 2005447, Donghee Son, Taeyoon Lee, and co‐workers develop self‐bondable and self‐weavable fibers as novel components for fiber‐based electronic devices. The fibers are both conductive and stretchable, which eliminates the trade‐off associated with the percolation theory. The integration with self‐bondable and self‐weavable interconnects represents a new integration strategy for fiber‐based devices.

关键词： fiber component integration self‐bondable conductive fibers stretchable and flexible interconnects wearable electronics

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Wearable Flexible Hybrid Electronics: Advanced Soft Materials, Sensor Integrations, and Applications of Wearable Flexible Hybrid Electronics in Healthcare, Energy, and Environment (Adv. Mater. 15/2020)

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Advanced Materials 2020年第15期32卷

作者： Hyo‐Ryoung Lim Hee Seok Kim Raza Qazi Young‐Tae Kwon Jae‐Woong Jeong Woon‐Hong Yeo George W. Woodruff School of Mechanical Engineering Institute for Electronics and Nanotechnology Georgia Institute of Technology Atlanta GA 30332 USA Department of Mechanical Engineering University of South Alabama Mobile AL 36608 USA Department of Electrical Computer & Energy Engineering University of Colorado Boulder Boulder CO 80309 USA School of Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon 34141 South Korea George W. Woodruff School of Mechanical Engineering Wallace H. Coulter Department of Biomedical Engineering Institute for Electronics and Nanotechnology Parker H. Petit Institute for Bioengineering and Biosciences Center for Flexible and Wearable Electronics Advanced Research Neural Engineering Center Institute for Materials Institute for Robotics and Intelligent Machines Georgia Institute of Technology Atlanta GA 30332 USA

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Deep kernels for optimizing locomotion controllers

arXiv

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arXiv 2017年

作者： Antonova, Rika Rai, Akshara Atkeson, Christopher G. Robotics Perception and Learning CSC KTH Royal Institute of Technology Stockholm Sweden Robotics Institute School of Computer Science Carnegie Mellon University United States

Sample efficiency is important when optimizing parameters of locomotion controllers, since hardware experiments are time consuming and expensive. Bayesian Optimization, a sample-efficient optimization framework, has recently been widely applied to address this problem, but further improvements in sample efficiency are needed for practical applicability to real-world robots and high-dimensional controllers. To address this, prior work has proposed using domain expertise for constructing custom distance metrics for locomotion. In this work we show how to learn such a distance metric automatically. We use a neural network to learn an informed distance metric from data obtained in high-fidelity simulations. We conduct experiments on two different controllers and robot architectures. First, we demonstrate improvement in sample efficiency when optimizing a 5-dimensional controller on the ATRIAS robot hardware. We then conduct simulation experiments to optimize a 16-dimensional controller for a 7-link robot model and obtain significant improvements even when optimizing in perturbed environments. This demonstrates that our approach is able to enhance sample efficiency for two different controllers, hence is a fitting candidate for further experiments on hardware in the future. Copyright © 2017, The Authors. All rights reserved.

关键词： Controllers

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Selective DF Based Multiple Relayed Cooperative System with M-QAM Signalling

Selective DF Based Multiple Relayed Cooperative System with ...

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International Symposium on Personal, Indoor, and Mobile Radio Communications

作者： Sandhya Soni Divyang Rawal Nikhil Sharma Dushantha Nalin K. Jayakody Dept. of Electronics and Communication Engineering LNM Institute of Information Technology Jaipur INDIA School of Computer Science and Robotics National Research Tomsk Polytechnic University RUSSIA

ISBN: (纸本)9781538660102

In this paper, we analyze the error rate performance of selective decode-and-forward (DF) based multiple relayed cooperative system for M-QAM (Quadrature Amplitude Modulation) signalling. The analysis is performed for selective DF based cooperative relaying with single as well as multiple relayed system. In particular, an alternate representation of Q-function is used to derive the closed-form expression of asymptotic symbol error rate probability (ASEP) over Rayleigh faded channels with high SNR approximation. Further, the analytical results are corroborated by Monte Carlo simulations for M-QAM MRC cooperative system.

关键词： Decode and Forward M-QAM Multiple relays Cooperative System

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A decomposition-based approach to reasoning about free space path-connectivity for rigid objects in 2D

arXiv

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arXiv 2017年

作者： Varava, Anastasiia Carvalho, J. Frederico Kragic, Danica Pokorny, Florian T. Robotics Perception and Learning Lab School of Computer Science and Communication KTH The Royal Institute of Technology Stockholm100 44 Sweden

In this paper, we compute a conservative approximation of the path-connected components of the free space of a rigid object in a 2D workspace in order to solve two closely related problems: (i) to determine whether there exists a collision-free path between two given configurations, and (ii) to verify whether an object can escape arbitrarily far from its initial configuration - i.e., whether the object is caged. Furthermore, we consider two quantitative characteristics of the free space: the volume of path-connected components and the width of narrow passages. To address these problems, we decompose the configuration space into a set of two-dimensional slices, approximate them as two-dimensional alpha-complexes, and then study the relations between them. This significantly reduces the computational complexity compared to a direct approximation of the free space. We implement our algorithm and run experiments in a three-dimensional configuration space of a simple object showing runtime of less than 2 seconds. Copyright © 2017, The Authors. All rights reserved.

关键词： Wave functions

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Multiple Model based Unscented Particle Filter Algorithm for a SINS/CNS Integrated Navigation System

Multiple Model based Unscented Particle Filter Algorithm for...

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American Control Conference

作者： Fangfang Zhao Shuzhi Sam Ge Wei He School of Computer Science and Engineering Center for Robotics University of Electronic Science and Technology of China Chengdu 611731 China the Department of Electrical and Computer Engineering National University of Singapore 117576 Singapore and Center for Robotics University of Electronic Science and Technology of China Chengdu 611731 China School of Automation and Electrical Engineering University of Science and Technology of Beijing Beijing 100083 China

ISBN: (纸本)9781509045839

The single model filter has poor adaptability under the uncertain or unknown system parameters, multiple model filters can be used to resolve this problem. This paper investigates the multiple model adaptive estimation (MMAE) algorithm and proposes a multiple model unscented particle filter (MMUPF) algorithm. Forward the traditional MMAE method which uses extend Kalman filter (EKF) or unscented Kalman filter (UKF) as each filter to execute the state estimation process. In this method, we combine MMAE with unscented particle filter (UPF), and replace UKF with UPF which shows higher accuracy than UKF for the nonlinear system. At the same time, this algorithm is applied to the integrated navigation system which combines strap-down inertial navigation with celestial navigation by a ballistic missile. Simulations are provided to demonstrate that MMUPF algorithm has the highest navigation precision, but at the cost of heavier computational burden.

关键词： resolve problem paper Resolve hybrid navigation systems Navigation systems Particle filtering algorithm State estimation Celestial navigation INERTIAL NAVIGATION paper Particle filters Filters multiples Nonlinear systems system parameter

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Minimizing task-space Fréchet error via efficient incremental graph search

arXiv

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arXiv 2017年

作者： Holladay, Rachel Salzman, Oren Srinivasa, Siddhartha Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Robotics Institute Carnegie Mellon University Paul G. Allen School of Computer Science and Engineering University of Washington

We present an anytime algorithm that generates a collision-free configuration-space path that closely follows a desired path in task space, according to the discrete Fréchet distance. By leveraging tools from computational geometry, we approximate the search space using a cross-product graph. We use a variant of Dijkstra's graphsearch algorithm to efficiently search for and iteratively improve the *** compare multiple proposed densification strategies and empirically show that our algorithm outperforms a set of state-of-the-art planners on a range of manipulation problems. Finally, we offer a proof sketch of the asymptotic optimality of our algorithm. Copyright © 2017, The Authors. All rights reserved.

关键词： Computational geometry

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