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ASME international Design Engineering Technical conferences / Computers and Information in Engineering conference (IDETC-CIE) / 49th Design automation conference (DAC)

作者： Short, Ada-Rhodes Univ Nebraska Omaha Omaha NE 68182 USA

ISBN: (纸本)9780791887318

In the past year there have been paradigm shifting developments in the feasibility and availability of machine learning tools for the creation of visual and textual works. Two of the most prominent examples of this has been Large-Language models like chatGPT and methods like stable diffusion for generating art from text prompts. Both visual and language arts are often thought of as human activities, so exploring the possibilities and limitations of these tools is important for both understanding automation and improving our understanding of human cognition. In this paper I use a Large-Language Model and stable diffusion in tandem to develop an understanding of what new possibilities exist in computational cognition and design automation through their application. While no single model can recreate the complexities of a biological brain at this time, they can be thought of as analogous to individual neurological structures. For example, a Large-Language Model that is able to reason out and communicate the solutions to simple logic puzzles could recreate some of the functionality of the frontal lobe of the cerebrum. Additionally approaches like stable diffusion can recreate some of the functions of the occipital and parietal lobes. By combining them more complex behaviors and capabilities can be achieved than are possible from the individual parts. This work is in its early stages but is foundational for later developments in design automation, robotics, and computational cognition.

关键词： Diffusion

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A User-customized Automatic Music Composition System 39

A User-customized Automatic Music Composition System

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IEEE international conference on robotics and automation (ICRA)

作者： Mo, Fan Ji, Xiaoqiang Qian, Huihuan Xu, Yangsheng Chinese Univ Hong Kong Sch Sci & Engn Shenzhen Guangdong Peoples R China Chinese Univ Hong Kong Shenzhen Inst Artificial Intelligence & Robot Soc Shenzhen Guangdong Peoples R China

ISBN: (纸本)9781728196817

This paper introduces an intelligent system which composes music following the users' instructions. Current automatic music generation models are lack of stability. Meanwhile, they cannot satisfy the preference of different people. To overcome these challenges, we train a Transformer-based neural network to generate short music segments using a dataset. A user can compose music pieces by interacting with a well-trained generator. Our system collects the user's feedback during the interactions, and fine-tunes the neural network to optimize the generator. After a large number of interactions, our system can learn the musical taste of the user and customize a personal automatic music composer for him or her. Our work enhances the application value of generative models significantly, which enables people to compose music with the assistance of artificial intelligence.

关键词： automation Neural networks Music Entertainment industry Transformers Generators Stability analysis

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Multimodal Strain Sensing System for Shape Recognition of Tensegrity Structures by Combining Traditional Regression and Deep Learning Approaches

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IEEE robotics AND automation LETTERS 2024年第11期9卷 10050-10056页

作者： Mao, Zebing Kobayashi, Ryota Nabae, Hiroyuki Suzumori, Koichi Yamaguchi Univ Fac Engn Yamaguchi 7558611 Japan Tokyo Inst Technol Dept Mech Engn Tokyo 1528552 Japan

A tensegrity-based system is a promising approach for dynamic exploration of uneven, unpredictable, and confined environments. However, implementing such systems presents challenges in state recognition. In this study, we introduce a 6-strut tensegrity structure integrated with 24 multimodal strain sensors, employing a deep learning model to achieve smart tensegrity. By using conductive flexible tendons and leveraging a long short-term memory (LSTM) model, the system accomplishes self-shape reconstruction without the need for external sensors. The sensors operate in two modes, and we applied both a curve fitting model and an LSTM model to establish the relationship between length change and resistance change in the sensors. Our key findings demonstrate that the intelligent tensegrity system can accurately self-detect and adapt its shape. Furthermore, a human pressing process allows users to monitor and understand the tensegrity's shape changes based on the integrated models. This intelligent tensegrity-based system with self-sensing tendons showcases significant potential for future exploration, making it a versatile tool for real-world applications.

关键词： Sensors Strain Mathematical models Bending Shape Robot sensing systems Resistance Long short term memory Capacitive sensors Tendons Tensegrity soft sensors and actuators deep learning methods vision and sensor-based control

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Autonomous Exploration Development Environment and the Planning Algorithms 39

Autonomous Exploration Development Environment and the Plann...

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IEEE international conference on robotics and automation (ICRA)

作者： Cao, Chao Zhu, Hongbiao Yang, Fan Xia, Yukun Choset, Howie Oh, Jean Zhang, Ji Carnegie Mellon Univ Robot Inst Pittsburgh PA 15213 USA

ISBN: (纸本)9781728196817

Autonomous Exploration Development Environment is an open-source repository released to facilitate development of high-level planning algorithms and integration of complete autonomous navigation systems. The repository contains representative simulation environment models, fundamental navigation modules, e.g., local planner, terrain traversability analysis, waypoint following, and visualization tools. Together with two of our high-level planner releases - TARE planner for exploration and FAR planner for route planning, we detail usage of the three open-source repositories and share experiences in integration of autonomous navigation systems. We use DARPA Subterranean Challenge as a use case where the repositories together form the main navigation system of the CMU-OSU Team. In the end, we discuss a few potential use cases in extended applications.

关键词： Analytical models Visualization automation Navigation Planning Open source software Autonomous robots

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Research on the Calculation Model of the Influence Function Method for the Complete Roll System of a 20-High Rolling Mill

Research on the Calculation Model of the Influence Function ...

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2024 lEEE international conference on Advanced Information, Mechanical Engineering, robotics and automation, AIMERA 2024

作者： Zhao, Yang Liu, Xuming Bai, Jinlan Wang, Junsheng Sun, Jie Wang, Guodong Ansteel Beijing Research Institute Co. Ltd. Beijing102209 China Shenyang Aerospace University School of Mechatronics Engineering Shenyang110034 China Northeastern University State Key Laboratory of Rolling and Automation Shenyang110004 China

ISBN: (纸本)9798350343335

This study presents the development of a novel calculation model for the influence function method, specifically tailored for the complete roll system of a 20-high rolling mill, a critical component in strip shape control. The research incorporates a hybrid approach, leveraging both simply supported beam and cantilever beam models, to accurately determine the elastic bending influence function for the segmented support rolls characteristic of 20-high rolling mills. The proposed method achieves a notable enhancement in calculation precision, with a validated error rate of less than 3% using real-world data from Ansteel's 20-high rolling mill. This advancement is expected to facilitate the optimization of the rolling process, thereby improving product quality and boosting production efficiency. © 2024 IEEE.

关键词： Rolls (machine components)

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Shape Control of Deformable Linear Objects with Offline and Online Learning of Local Linear Deformation models 39

Shape Control of Deformable Linear Objects with Offline and ...

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IEEE international conference on robotics and automation (ICRA)

作者： Yu, Mingrui Zhong, Hanzhong Li, Xiang Tsinghua Univ Dept Automat Beijing Peoples R China Tsinghua Univ Sch Aerosp Engn Beijing Peoples R China

ISBN: (纸本)9781728196817

The shape control of deformable linear objects (DLOs) is challenging, since it is difficult to obtain the deformation models. Previous studies often approximate the models in purely offline or online ways. In this paper, we propose a scheme for the shape control of DLOs, where the unknown model is estimated with both offline and online learning. The model is formulated in a local linear format, and approximated by a neural network (NN). First, the NN is trained offline to provide a good initial estimation of the model, which can directly migrate to the online phase. Then, an adaptive controller is proposed to achieve the shape control tasks, in which the NN is further updated online to compensate for any errors in the offline model caused by insufficient training or changes of DLO properties. The simulation and real-world experiments show that the proposed method can precisely and efficiently accomplish the DLO shape control tasks, and adapt well to new and untrained DLOs.

关键词： Deformable models Training Adaptation models Shape control Three-dimensional displays Robot vision systems Estimation

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2023 3rd international conference on robotics, automation and Artificial Intelligence, RAAI 2023

2023 3rd International Conference on Robotics, Automation an...

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3rd international conference on robotics, automation and Artificial Intelligence, RAAI 2023

ISBN: (纸本)9798350307566

The proceedings contain 53 papers. The topics discussed include: three-dimensional trajectory planning for multi-robot collaboration in complex components with heterogeneous materials;innovative approaches to tourism demand prediction: a genetic algorithm perspective;a fuzzy inference system-based hybrid assignment method for cobot assignment problem;cylinder-wheel coupled robot with buttocks-support mechanism for lower-limb rehabilitation training;area coverage maximization of multi UAVs using multi-agent reinforcement learning;design of a drone that applies multisensor information for the early detection of forest fires;and research on dataset generation in the development of large language models for digital textbooks.

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TridentNetV2: Lightweight Graphical Global Plan Representations for Dynamic Trajectory Generation 39

TridentNetV2: Lightweight Graphical Global Plan Representati...

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IEEE international conference on robotics and automation (ICRA)

作者： Paz, David Xiang, Hao Liang, Andrew Christensen, Henrik I. Univ Calif San Diego Contextual Robot Inst La Jolla CA 92093 USA

ISBN: (纸本)9781728196817

We present a framework for dynamic trajectory generation for autonomous navigation, which does not rely on HD maps as the underlying representation. High Definition (HD) maps have become a key component in most autonomous driving frameworks, which include complete road network information annotated at a centimeter-level that include traversable waypoints, lane information, and traffic signals. Instead, the presented approach models the distributions of feasible ego-centric trajectories in real-time given a nominal graph-based global plan and a lightweight scene representation. By embedding contextual information, such as crosswalks, stop signs, and traffic signals, our approach achieves low errors across multiple urban navigation datasets that include diverse intersection maneuvers, while maintaining real-time performance and reducing network complexity. Underlying datasets introduced are available online.

关键词： automation Navigation Roads Predictive models Real-time systems Trajectory Complexity theory

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Design Optimization and Data-driven Shallow Learning for Dynamic Modeling of a Smart Segmented Electroadhesive Clutch

Design Optimization and Data-driven Shallow Learning for Dyn...

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IEEE international conference on robotics and automation (ICRA)

作者： Feizi, Navid Bahrami, Zahra Atashzar, S. Farokh Kermani, Mehrdad R. Patel, Rajni V. Canadian Surg Technol & Adv Robot CSTAR Lawson Hlth Res Inst London ON N6A 5A5 Canada Western Univ Sch Biomed Engn London ON N6A 3K7 Canada Univ Erlangen Nurnberg Inst Geog D-91054 Erlangen Germany New York Univ NYU Dept Mech & Aerosp Engn Dept Elect & Comp Engn New York NY 10003 USA New York Univ NYU Dept Biomed Engn New York NY 10003 USA NYU WIRELESS New York NY USA NYU CUSP New York NY USA Western Univ Dept Elect & Comp Engn London ON N6A 5B9 Canada Western Univ Dept Elect & Comp Engn Sch Biomed Engn Dept Surg London ON N6A 5B9 Canada Western Univ Dept Clin Neurol Sci London ON N6A 5B9 Canada

ISBN: (纸本)9798350323658

Electroadhesive clutches have attracted a great deal of interest in the last decade as semi-active actuators for human-robot interaction due to their lightweight, low power consumption, and tunable high-torque output capability. However, because of the complexity of their dynamics, in most cases, they are utilized in an ON/OFF-control strategy. In this regard, the non-autonomous (time-dependent) degradation of electroadhesive behavior is an inherent challenge that injects unpredictability and uncertainty into the behavior of this family of semi-active clutches. We propose a novel approach to preventing degradation of electroadhesion using a segmented electrode design that modulates the electrical field on the dielectric surface while using a direct current signal and securing low power consumption. This paper, for the first time, presents an optimization process based on a novel analytic model of the proposed actuator. It also develops a data-driven model augmentation using a hybrid shallow learning approach composed of a long short-term memory (LSTM) architecture which is combined with the analytical model. The performance of the proposed semi-active clutch and the data-driven hybrid model is experimentally validated in this paper.

关键词： Analytical models

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A Continuum Robot with Antagonistic and Phase-Variable Stiffness

A Continuum Robot with Antagonistic and Phase-Variable Stiff...

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2024 IEEE international conference on robotics and Biomimetics, ROBIO 2024

作者： Zhang, Guotao Bai, Guoqing Sun, Yi Research Institute of USV Engineering School of Mechanical and Electrical Engineering and Automation Shanghai University China Research Institute of USV Engineering Shanghai University China

ISBN: (纸本)9781665481090

In order to meet the practical needs of continuum robots for completing different tasks, this study proposes a new type of continuum robot. A kinematic analysis of this continuum robot is carried out. At the same time, this paper combines the two methods of variable stiffness of phase change materials and wire antagonistic variable stiffness with the existing variable stiffness methods of continuum robots. Experiments have proved that the use of phase change materials will increase the antagonistic stiffness, but the torsion brought about by the antagonism itself will weaken the effect of the phase change materials. © 2024 IEEE.

关键词： Microrobots

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