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The Design of Future Robotic Construction Lab

The Design of Future Robotic Construction Lab

引用

ASCE international conference on Computing in Civil Engineering (i3CE)

作者： Yang, C. H. Wu, T. H. Kang, S. C. Univ Alberta Dept Civil & Environm Engn 116 St & 85 Ave Edmonton AB T6G 2R3 Canada Natl Taiwan Univ Dept Civil Engn 1Sec 4Roosevelt Rd Taipei 10617 Taiwan

ISBN: (纸本)9780784482438

The increasing labor shortage issue and the working safety awareness cause the urgent of the development of new construction methods. A new type of lab for new construction processes is required to expedite the innovation cycle. This paper presents an ongoing work of building a construction lab at University of Alberta. The goal of the construction lab is to provide a sandbox for developing new construction processes and machines. We designed the lab with four major systems: (1) sensors: to collect data from construction site for operation assistants and virtual reconstruction;(2) manipulators: to excavate the path planning algorithms and to develop the cooperation approaches between human and machines;(3) visualizers: to construct the digital twin of a real construction site for revealing the simulated results in virtual environment;(4) computers: to run machine learning algorithms for recognizing and tracking objects in construction environments. This laboratory allows the researchers in the construction engineering test and develop their tools in a controlled environment. Such scaled tests in the lab can bring significant benefits in finance, efficiency, and safety. Technical Area: robotics, automation, and control. Application Context: Project design, construction, planning, and management.

关键词： automation control robotics

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Drift-Free Latent Space Representation for Soft Strain Sensors

Drift-Free Latent Space Representation for Soft Strain Senso...

引用

IEEE international conference on Soft robotics (RoboSoft)

作者： Thomas George Thuruthel Kieran Gilday Fumiya Iida Bio-Inspired Robotics Lab University of Cambridge UK

ISBN: (数字)9781728165707

ISBN: (纸本)9781728165714

Soft strain sensors are becoming increasingly popular for obtaining tactile information in soft robotic applications. Diverse technological solutions are being investigated to design these sensors. Simultaneously, new methods for modeling these sensor are being proposed due to their highly nonlinear, time varying properties. Among them, machine learning based approaches, particularly using dynamic recurrent neural networks look the most promising. However, these complex networks have large number of free parameters to be tuned, making it difficult to apply them for real-world applications. This paper introduces the concept of transfer learning for modelling soft strain sensors, which allows us to utilize information learned in one task to be applied to another task. We demonstrate this technique on a passive anthropomorphic finger with embedded strain sensors used for two regression tasks. We show how the transfer learning approach can drastically reduce the number of free parameters to be tuned for learning new skills. This work is an important step towards scaling of sensor networks (algorithm-wise) and for using soft sensor data for high-level control tasks.

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Deep learning-based detection of overlapping cells 3

Deep learning-based detection of overlapping cells

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3rd international conference on Advances in Artificial Intelligence, ICAAI 2019

作者： Paulauskaite-Taraseviciene, Agne Sutiene, Kristina Valotka, Justas Raudonis, Vidas Iesmantas, Tomas Department of Applied Informatics Kaunas University of Technology Studentu 50-214 Kaunas Lithuania Department of Mathematical Modelling Kaunas University of Technology Studentu 50-141 Kaunas Lithuania Faculty of Informatics Kaunas University of Technology Studentu 50-411 Kaunas Lithuania Department of Automation Kaunas University of Technology Studentu 48-325a Kaunas Lithuania Department of Applied Mathematics Kaunas University of Technology Studentu 50-319 Kaunas Lithuania

ISBN: (纸本)9781450372534

Detection and quantification of cells in general is one of the key challenges in many clinical trials for disease diagnosis and monitoring. automation of this task enables quantitative analysis of digital images with a high processing rate, which is a support to pathologist at various kind of analyses. Recent studies have already indicated that deep learning usually yield superior accuracy in the field of digital pathology. One of the challenges tackled by the researches is to detect cells in images when cells are highly overlapped, over illuminated or partially occluded with the noise. Therefore, we focused on two conceptually different deep learning models, specifically U-Net and Mask R-CNN, in order to evaluate their capability and performance on the detection of overlapping cells. The dataset used in the study contains different types of images, possible observed under different lighting conditions, and the amount of target cells may range from tens to thousands, therefore the algorithm is required to be flexible enough. © 2019 ACM.

关键词： Cells

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Nonlinearity Compensation in A Multi-DoF Shoulder Sensing Exosuit For Real-Time Teleoperation

Nonlinearity Compensation in A Multi-DoF Shoulder Sensing Ex...

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IEEE international conference on Soft robotics (RoboSoft)

作者： Rejin John Varghese Anh Nguyen Etienne Burdet Guang-Zhong Yang Benny P L Lo The Hamlyn Centre Institute for Global Health Innovation Imperial College London UK Department of Bioengineering Imperial College London UK Institute of Medical Robotics Shanghai Jiao Tong University China

ISBN: (数字)9781728165707

ISBN: (纸本)9781728165714

The compliant nature of soft wearable robots makes them ideal for complex multiple degrees of freedom (DoF) joints, but also introduce additional structural nonlinearities. Intuitive control of these wearable robots requires robust sensing to overcome the inherent nonlinearities. This paper presents a joint kinematics estimator for a bio-inspired multi- DoF shoulder exosuit capable of compensating the encountered nonlinearities. To overcome the nonlinearities and hysteresis inherent to the soft and compliant nature of the suit, we developed a deep learning-based method to map the sensor data to the joint space. The experimental results show that the new learning-based framework outperforms recent state-of-the-art methods by a large margin while achieving 12ms inference time using only a GPU-based edge-computing device. The effectiveness of our combined exosuit and learning framework is demonstrated through real-time teleoperation with a simulated NAO humanoid robot.

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Closing the Loop with Liquid-Metal Sensing Skin for Autonomous Soft Robot Gripping

Closing the Loop with Liquid-Metal Sensing Skin for Autonomo...

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IEEE international conference on Soft robotics (RoboSoft)

作者： Jessica Yin Tess Hellebrekers Carmel Majidi Department of Mechanical Engineering Carnegie Mellon University Pittsburgh PA School of Computer Science Robotics Institute Carnegie Mellon University Pittsburgh PA USA

ISBN: (数字)9781728165707

ISBN: (纸本)9781728165714

Soft robots are often limited in high-level decision making and feedback control due to a lack of multimodal sensing capabilities and material architectures that tightly integrate sensing and actuation. However, the recent development of elastic multimodal sensing skins has created the opportunity for closing the loop in soft robotic systems. In this work, we present a sensor-based finite state machine for a soft sensorized gripper mounted to a 4-degree-of-freedom robot arm. The soft gripper actuates between binary open and close states by activating shape-memory alloy springs, and contains proximity, pressure, and orientation sensors. The closed-loop control is demonstrated through scanning, grasping, and sorting tasks driven by sensor feedback. Using a time-of-flight distance sensor, the system can calculate the length, width, height, and center of mass of an object within a 60 mm x 25 mm workspace. With the time-of-flight distance sensor, pressure sensors, and inertial measurement unit, the system can detect and respond to external perturbations that interfere with the grasp, release, and transport of the object. The control strategy demonstrated in this paper can be expanded in the future to integrate basic autonomy in other soft robot systems.

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Reducing Computational Cost of Pair-Polar Coordinate-based Cancelable Fingerprint Template Matching

Reducing Computational Cost of Pair-Polar Coordinate-based C...

引用

international conference of Computer and informatics Engineering (IC2IE)

作者： Lucas Susanto Tohari Ahmad Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9781728182476

ISBN: (纸本)9781728182483

Since a long time ago, biometrics has become a popular authentication method to verify users easily. Despite this advantage, the user's biometric data must be stored securely because those data cannot be replaced once it has been compromised. It is because humans cannot alter parts of his or her body. Many methods can be used to secure biometric data. One of them is the cancelable fingerprint template. However, its matching computation process is quite expensive, as many minutia points need to compare. In this paper, we optimize the number of minutia points in its selection process using a new threshold. It is to reduce the computational cost of pair-polar coordinate-based cancelable fingerprint template's matching. The experiment result shows that the proposed method achieves five times better performance than the previous method.

关键词： Fingerprint recognition Biometrics (access control) Transforms informatics Feature extraction Computational efficiency Authentication

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Design and Implementation of a Lightweight Lower Extremity Exoskeleton

Design and Implementation of a Lightweight Lower Extremity E...

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3rd international conference on Mechanical, System and control Engineering, ICMSC 2019

作者： Mu, Jiamin Jiang, Hongzhou Hua, Yuxiang Zhao, Jie Zhu, Yanhe State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China Department of Fluid Control and Automation Harbin Institute of Technology Harbin150001 China

This paper summarizes the biomechanics simulation and design of a lightweight lower extremity exoskeleton. The biomechanics simulation was carried out using LifeMOD to obtain joint torques of human body in the condition of its applications including walking on flat ground, ascending stairs, sitting down and standing up which provided the design criteria of actuating torques. The anthropomorphically based exoskeleton has 7 degrees of freedom per leg, two of which are powered by brushless DC motors, and the total mass is less than 12 kg due to the use of carbon fiber material and the compact structural design and optimization. controlling and sensing system based on CANopen communication protocol is proposed which can provide high communication efficiency and reliability for the control of the exoskeleton. © The Authors, published by EDP Sciences, 2019.

关键词： Biomechanics

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Efficient Bayesian Exploration for Soft Morphology-Action Co-optimization

Efficient Bayesian Exploration for Soft Morphology-Action Co...

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IEEE international conference on Soft robotics (RoboSoft)

作者： Luca Scimeca Perla Maiolino Fumiya Iida Bio-Inspired Robotics Lab Trumpington St Cambridge CB2 1PZ UK Oxford Robotic Institute University of Oxford Oxford OX2 6NN U.K

ISBN: (数字)9781728165707

ISBN: (纸本)9781728165714

Morphology been shown to be a fundamental aspect of tactile sensing in soft robotics, one that can aid, and indeed enable, complex discrimination tasks. For a robot to change its sensor morphology as well as control appropriately, the parametric search over morphology and control parameters is usually slow and unsuited for real-world applications. We develop a framework based on Bayesian Exploration, to allow a robot to co-optimize both changes in tactile sensing morphology and robot action control, to aid in complex tactile object discrimination tasks. We test the framework by performing object discrimination on a set of eight objects, varying three different physical properties: geometry, surface texture, and stiffness. We integrate a capacitive tactile sensor into a flat end-effector and create three soft silicon-based filters with varying morphological properties. We incorporate the end-effector onto a robotic arm and perform repetitive, parameterized touch experiments, on each object. We show morphing is indeed necessary to dissociate amongst different object properties with the sensor at hand. Moreover, we show the proposed framework can consistently achieve optimal morphology-action configurations in approximately half the time than systematic search over parameters. This work marks a step towards the creation of robots capable of using morphology and action control to actively aid in discrimination tasks.

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Research and Application of Laser Projection Technology Used in Spacecraft Assembly 3

Research and Application of Laser Projection Technology Used...

引用

3rd international conference on robotics and automation Engineering (ICRAE)

作者： Zhang, Ning Zhao, Lu Wang, Zhe Beijing Inst Spacecraft Environm Engn Beijing Peoples R China

ISBN: (纸本)9781538695944

During the spacecraft assembly, the assembling information of the equipment is mainly determined by viewing the 3D model and manually measuring the lines. The assembly method is with high workload and low efficiency. To solve the problem that the 3D model cannot effectively guide the assembly, the approach to use the combination of laser projection technology and 3D model can make the assembly information on the 3D model projected to the assembly surface quickly and accurately, thus to obtain assembly information intuitively. This way can improve the efficiency and level of spacecraft assembly.

关键词： laser projection technology 3D model spacecraft assembly

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Robotic Cane as a Soft SuperLimb for Elderly Sit-to-Stand Assistance*

Robotic Cane as a Soft SuperLimb for Elderly Sit-to-Stand As...

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IEEE international conference on Soft robotics (RoboSoft)

作者： Xia Wu Haiyuan Liu Ziqi Liu Mingdong Chen Fang Wan Chenglong Fu Harry Asada Zheng Wang Chaoyang Song Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen Guangdong China Visiting Scholar with the SUSTech Institute of Robotics Southern University of Science and Technology Shenzhen Guangdong China Department of Mechanical Engineering MIT Cambridge MA USA

ISBN: (数字)9781728165707

ISBN: (纸本)9781728165714

Many researchers have identified robotics as a potential solution to the aging population faced by many developed and developing countries. If so, how should we address the cognitive acceptance and ambient control of elderly assistive robots through design? In this paper, we proposed an explorative design of an ambient SuperLimb (Supernumerary Robotic Limb) system that involves a pneumatically-driven robotic cane for at-home motion assistance, an inflatable vest for compliant human-robot interaction, and a depth sensor for ambient intention detection. The proposed system aims at providing active assistance during the sit-to-stand transition for at-home usage by the elderly at the bedside, in the chair, and on the toilet. We proposed a modified biomechanical model with a linear cane robot for closed-loop control implementation. We validated the design feasibility of the proposed ambient SuperLimb system including the biomechanical model, our result showed the advantages in reducing lower limb efforts and elderly fall risks, yet the detection accuracy using depth sensing and adjustments on the model still require further research in the future. Nevertheless, we summarized empirical guidelines to support the ambient design of elderly-assistive SuperLimb systems for lower limb functional augmentation.

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