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第42届中国控制会议

作者： Hao-Yu Wang Qing-Hao Meng Xu-Yang Dai Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and SystemSchool of Electrical and Information Engineering Tianjin University

In the last decades, significant progress has been made in the field of active vSLAM（visual simultaneous localization and mapping）. However, the majority of active vSLAM methods suffer from the problem of coupling the camera's viewpoint to the robot's motion, which limits the initiative during the exploration of unknown environments. To address this issue, this study proposes a camera view planning method based on deep reinforcement learning（DRL）, which makes the camera rotate independently. First, feature encoding is performed on the reconstructed navigation map using a multi-layer convolutional neural network（CNN）. Second, the DRL-based camera view planning method is trained through the proximal policy optimization（PPO）algorithm. Last, a significant number of tests is performed on a public dataset of indoor environments. The simulation results show that the proposed camera view planning method improves the exploration coverage by an average of 4%（33.86 m for traditional vs. 35.21 m for the suggested method）. Meanwhile, the kind of semantic information newly observed in each step increases by 21%（2.9 for traditional vs. 3.5 for the proposed method） on average, indicating the improvement in the efficiency of information acquisition.

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The Smart Hospital: Data and AI Challenges

The Smart Hospital: Data and AI Challenges

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2023 IEEE EMBS Special Topic Conference on Data Science and engineering in Healthcare, Medicine and Biology, IEEECONF 2023

作者： Plati, Daphni K. Konstantakopoulos, Fotios S. Kalatzis, Theofanis Manousos, Dimitrios Kassiotis, Thomas Di Luzio, Francesco Scotto Tagliamonte, Nevio Luigi Zollo, Loredana Tsiknakis, Manolis Fotiadis, Dimitrios I. University of Ioannina Unit of Medical Technology and Intelligent Information Systems Materials Science and Engineering Department Greece Forth Biomedical Research Institute IoanninaGR 45110 Greece Forth Institute of Computer Science Crete HeraklionGR 70013 Greece Campus Bio-Medico University Research Unit of Advanced Robotics and Human-Centred Technologies Rome Italy

ISBN: (纸本)9798350383386

Healthcare systems generally constitute a combination of healthcare facilities and providers that collaborate in order to offer a complete range of healthcare services. As the primary providers of healthcare, hospitals hold an essential place in the healthcare system. This study introduces three novel automated Artificial Intelligence (AI) systems by using the robotic platform of the TIAGo robot: (i) an image-based system that monitors the food consumption of the patients and provides information regarding their energy intake to prevent malnutrition;(ii) a rehabilitation system that monitors patients as they perform prescribed exercises to prevent loss of mobility, and (iii) a monitoring system for the correctness of the oxygen therapy in terms of the proper positioning of the oxygen mask to prevent hypoxia complications. A well-designed observational clinical study is planned to evaluate and validate the utility and effectiveness of the proposed AI systems in improving patient stay in the hospital. For the abovementioned systems, three novel datasets were *** Relevance: Through the implementation of AI systems, the proposed research intends to provide specialists with an extra tool to aid in the monitoring of hospitalized patients, thus helping to prepare the way for the Smart Hospital. © 2023 IEEE.

关键词： Hospitals

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Design of a Small-Scale Locust-Inspired Robot Capable of Jump-gliding Locomotion

Design of a Small-Scale Locust-Inspired Robot Capable of Jum...

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IEEE International Conference on robotics and Biomimetics

作者： Weitao Zhang Zisen Wei Yi Xu Liang Peng Changwen Dong Yanzhou Jin Qing Shi Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Ministry of Education Beijing China Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China

Small-scale robots are widely used in real-world rescue missions, but their mobility and movement range are still limited. One solution to improve their adaptability to complex environments is to introduce jumping and gliding strategies into the robot design. In this paper, we developed a small-scale locust-inspired robot capable of active (propeller-driven) gliding after launching from the ground, which had a body length of 19.1 cm and a weight of 97 g. On the basis of the locust’s musculoskeletal model, the jumping system was designed by a six-bar mechanism which can amplify the power. To improve the lift in gliding phase while reducing the draft in jumping phase, the gliding system with a folding wing and a front propeller was proposed corresponding to the fixed-wing principle. The results obtained through a series of experimental tests reveal that the robot achieves a jumping height of 0.15 m and a passive gliding distance of 1.5 m, which has a glide ratio of 1.13. Remarkably, actuating by a propeller, the robot can jump up to a height of 0.20 m, covering a gliding distance of 2.9 m. It is worth noting that the glide ratio of the robot improves by 91.2% in the propeller-driven jump-gliding mode.

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A Novel Way for Microvascular Network Pattern Formation Based on a Pre-Pattern Guidance Mechanism

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SSRN 2024年

作者： Fu, Ying Sun, Mingzhu Zhao, Xin Guo, Shan Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin300350 China China Institute of Robotics and Automatic Information Systems Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin300350 China Nankai University Eye Institute Nankai University Tianjin300350 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China

The microvascular network is an important tissue structure in animals, and its high spatial utilization of reticular pattern structure is an important guarantee for material exchange and nutrient transmission, which is crucial for tissue development, maintenance of metabolism and other life activities. However, the formation process of microvascular network pattern completion is still unclear. In this paper, based on the Turing reaction diffusion theory, we propose a network pattern formation method in the matrix environment, which is guided by morpholino pre-patterns to form the microvascular network structure by cell differentiation, and realize the morpholino network pattern at the molecular level, the differentiated cell network pattern at the cell level, and the formation of vascular network pattern under the influence of matrix environment at the tissue level, respectively, so as to establish a complete process of the formation of the microvascular network from the molecule to cells and to tissues, and explore the process of microvascular network formation. The complete process of microvascular network formation from molecules to cells to tissues was established, and the parameter conditions suitable for the formation of microvascular network patterns were explored. The network pattern formation method proposed in this paper provides a new research perspective for the study of reticular biological pattern development and pathology in the biomedical field. © 2024, The Authors. All rights reserved.

关键词： Molecules

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Optimization of Cylindrical Blades for Wind Turbine Based on Magnus Effect

Optimization of Cylindrical Blades for Wind Turbine Based on...

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International Conference on Electromechanical and Power systems (SIELMEN)

作者： Aleksandr Lukin Galina Demidova Dmitry Lukichev Nikolai Poliakov Alecksey Anuchin Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russia Electric Drives Department Moscow Power Engineering Institute Moscow Russia

Wind turbines based on the Magnus effect open new prospects in terms of energy generation for areas with low average wind speeds. The main feature of these turbines is rotating cylinders which are used to create lift instead of blades. Due to this unconventional design, different parameters of the cylinder, such as mass and moment of inertia, can greatly affect the dynamic characteristics of such energy systems. The goal of this paper was to present an approach to structural optimization of a cylinder flange of the experimental Magnus effect-based wind turbine. The proposed approach, presented as an algorithm, allows us to determine input data for the preferred structural optimization software and achieve lightweight, low-inertia parts. Control simulation has shown that optimized parts ensure a high enough factor of safety while also significantly reducing the moment of inertia.

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Integrating ROS and Android for Rescuers in a Cloud robotics Architecture: Application to a Casualty Evacuation Exercise

Integrating ROS and Android for Rescuers in a Cloud Robotics...

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IEEE International Workshop on Safety, Security, and Rescue robotics (SSRR)

作者： Manuel Toscano-Moreno Juan Bravo-Arrabal Manuel Sánchez-Montero Javier Serón Barba Ricardo Vázquez-Martín J.J. Fernandez-Lozano Anthony Mandow Alfonso Garcia-Cerezo Robotics and Mechatronics Group Institute of Mechatronics Engineering and Cyber-physical Systems University of Malaga Spain

ISBN: (纸本)9781665456814

Cloud robotics and the Internet of robotic things (IoRT) can boost the performance of human-robot cooperative teams in demanding environments (e.g., disaster response, mining, demolition, and nuclear sites) by allowing timely information sharing between agents on the field (both human and robotic) and the mission control center. In previous works, we defined an Edge/Cloud-based IoRT and communications architecture for heterogeneous multi-agent systems that was applied to search and rescue missions (SAR-IoCA). In this paper, we address the integration of a remote mission control center, which performs path planning, teleoperation and mission supervision, into a ROS network. Furthermore, we present the UMA-ROS-Android app, which allows publishing smartphone sensor data, including audio and high definition images from the rear camera, and can be used by responders for requesting a robot to the control center from a geolocalized field position. The app works up to API 32 and has been shared for the ROS community. The paper offers a case study where the proposed framework was applied to a cooperative casualty evacuation mission with professional responders and an unmanned rover with two detachable stretchers in a high-fidelity exercise performed in Malaga (Spain) in June 2022.

关键词： Cloud computing Publishing Geology Robot vision systems Cameras Path planning Safety

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Fault Detection in Electric Drives Based on LSTM Autoencoder Model Machine Learning Approach

Fault Detection in Electric Drives Based on LSTM Autoencoder...

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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Galina Demidova Daniil Privalov Denis Semenov Dmitry Lukichev Zhitao Liu Alecksey Anuchin Faculty of Control System and Robotics ITMO University Saint-Petersburg Russia Institute of Cyber-Systems & Control Zhejiang University Hangzhou China Department of Electric Drives Moscow Power Engineering Institute Moscow Russia

ISBN: (数字)9798350389234

ISBN: (纸本)9798350353051

Fault detection in electric drives is crucial for ensuring operational reliability and minimizing downtime. This paper provides a brief overview of the methods based on machine learning used for fault detection in electric drives. Additional this research presents a machine learning approach that utilizes the Long Short-Term Memory Autoencoder model for fault detection deal with bearing faults. A flowchart illustrating the implementation steps of the Long Short-Term Memory Autoencoder algorithm is included. Additionally, a case study on bearing faults in an electric drive system is presented to demonstrate the advantage of the proposed approach. By training the Long Short-Term Memory Autoencoder on operational data, accurate prediction of bearing faults is achieved, enabling timely maintenance interventions. It is shown that in the 7th epoch of training, the model achieved a notably high accuracy more than $\mathbf{9 9 \%}$. The results highlight the potential of Long Short-Term Memory Autoencoder models as a valuable tool for fault detection in electric drives, thereby improving system reliability and performance.

关键词： Training Vibrations Fault diagnosis Machine learning algorithms Fault detection Machine learning Prediction algorithms

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Motion Capture and Gait Analysis of Ants with Leg Injuries

Motion Capture and Gait Analysis of Ants with Leg Injuries

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第42届中国控制会议

作者： Ming Zeng Yuanhao Li Chang Meng Shutong Zhong Zhijing Wang Feng Zhao Institute of Robotics and Automation Systems Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin University

Many insects in nature, such as ants, recover quickly after sustaining leg injuries. If this capability could be imparted to multi-legged robots, it would drastically enhance their ability to resist destruction and adapt to the environment. In this paper, the Camponotus Japonicus is used as the research object, and its locomotive patterns are studied under different leg-loss *** facilitate this, a high-speed acquisition system, with a dual-view(bottom view and side view) setup, is designed to analyze the ant's linear gaits. Subsequently, the pivotal gait characteristics of the injured ants are extracted by keyframe annotation technology, including the gait phase diagram, duty factor, angle before support, angle before swing, and leg swing range. Lastly,according to the obtained gait characteristics, the general and specific laws of gait adjustment in the absence of one or two legs are systematically analyzed, which provides the basis for parametric settings and strategy optimization of robotic injured gait self-adjustment.

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Automated Leaf-Level Inspection of Crops Combining UAV and UGV Robots 16th

Automated Leaf-Level Inspection of Crops Combining UAV and...

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16th European robotics Forum, ERF 2025

作者： Esser, Felix Marks, Elias Magistri, Federico Weyler, Jan Bultmann, Simon Zaenker, Tobias Ahmadi, Alireza Schreiber, Michael Kuhlmann, Heiner McCool, Chris Popović, Marija Stachniss, Cyrill Behnke, Sven Bennewitz, Maren Klingbeil, Lasse Institute of Geodesy and Geoinformation University of Bonn Bonn Germany Autonomous Intelligent Systems University of Bonn Bonn Germany Humanoid Robots Lab University of Bonn Bonn Germany Agricultural Robotics and Engineering University of Bonn Bonn Germany Center for Robotics University of Bonn Bonn Germany

ISBN: (纸本)9783031894701

Using areal and ground-based robotics systems is one possible component on the way to more sustainable crop production. In this work, we show, how a combination of a UAV and ground robot can be used to automate the process of single plant and even leaf-level inspection of crops in the field, as the farmer usually does manually by physically going to the plants. The work integrates UAV-based plant and weed mapping, UGV path planning and execution, viewpoint planning and control of a robot-mounted arm with a multi-camera head, as well as high-resolution 3D reconstruction. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Crops

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Energy-Consumption Optimization Control for Lunar Rover's Travel with Torque-Distribution-strategy in Rear Wheels

Energy-Consumption Optimization Control for Lunar Rover's Tr...

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IEEE International Conference on Control Science and systems engineering (CCSSE)

作者： Delun Li Jianfei Cao Yiliang Chen Zongwu Xie State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering Beijing China

ISBN: (数字)9798331517199

ISBN: (纸本)9798331517205

In anticipation of future extensive lunar surface operations, lunar rovers are required to advance towards higher speeds and improved energy conservation. When traveling at high speeds on the lunar surface, the vehicle's energy expenditure is greatly amplified by the influence of the terrain, particularly in conditions where driving and steering are coupled. This paper proposes an energy-saving control strategy for lunar rovers that employs dynamic rear-axle torque distribution, with the goal of optimizing transient energy consumption during travel. To tackle the challenge of non-differentiable functions within the optimization objectives, we suggest using a zeroth-order gradient optimization method for resolution, dynamically constraining the range of control parameters to fulfill the dynamic torque distribution objectives as needed for the task. The energy-saving control effectiveness of the algorithm has been confirmed through simulation, demonstrating a minimum energy-saving ratio of at least 4%, which increases to over 11% as the speed level rises, offering a valuable technical solution for the energy optimization of lunar rovers.

关键词： Space vehicles Energy consumption Torque Distribution strategy Moon Wheels Optimization methods systems engineering and theory Vehicle dynamics Transient analysis

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