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15th International Conference on Electromechanics and robotics Zavalishin’s Readings, ERZR 2020

作者： Mingachev, Eldar Lavrenov, Roman Magid, Evgeni Svinin, Mikhail Intelligent Robotics Department Higher Institute for Information Technology and Intelligent Systems Kazan Federal University Kazan Russia College of Information Science and Engineering Ritsumeikan University Kyoto Japan

ISBN: (纸本)9789811555794

Stable and robust path planning and movement in ground mobile robots require a combination of accuracy and low latency in their state estimation. However, state estimation algorithms must provide these qualities under the computational and power constraints of embedded hardware. Simultaneous localization and mapping (SLAM) algorithms are the best choices for state estimation in these scenarios, in addition to their ability to operate without external localization from motion capture or global positioning systems. Moreover, a single-camera setup is the most common solution for robotic platforms, which reduces our domain of interest to the specific SLAM algorithms type—monocular SLAM. Yet, it is still not clear from the existing literature, which monocular SLAM algorithms perform well under the accuracy, latency, and computational constraints of a ground mobile robot with onboard state estimation. This paper evaluates an array of the most recent publicly available monocular SLAM methods: ORB-SLAM2, DSO, and LDSO. The evaluation considers the pose estimation accuracy (alignment error, absolute trajectory error, and relative pose error) while processing the TUM Mono and EuRoC datasets on the specific hardware platform with a balanced amount of computational resources and power consumption. We present our complete results as a benchmark for the research community. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.

关键词： State estimation

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Deep-Learning-Assisted Underwater 3D Tactile Tensegrity

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Research 2023年第3期2023卷 683-695页

作者： Peng Xu Jiaxi Zheng Jianhua Liu Xiangyu Liu Xinyu Wang Siyuan Wang Tangzhen Guan Xianping Fu Minyi Xu Guangming Xie Zhong Lin Wang Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems Marine Engineering CollegeDalian Maritime UniversityDalian 116026China School of Information Science and Technology Dalian Maritime UniversityDalian 116026China Intelligent Biomimetic Design Lab College of EngineeringPeking UniversityBeijing 100871China Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of SciencesBeijing 100871China School of Materials Science and Engineering Georgia Institute of TechnologyAtlantaGA 30332-0245USA

The growth of underwater robotic applications in ocean exploration and research has created an urgent need for effective tactile ***,we propose an underwater 3-dimensional tactile tensegrity(U3DTT)based on soft self-powered triboelectric nanogenerators and deep-learning-assisted data *** device can measure and distinguish the magnitude,location,and orientation of perturbations in real time from both flow field and interaction with obstacles and provide collision protection for underwater vehicles *** is enabled by the structure that mimics terrestrial animals’musculoskeletal systems composed of both stiff bones and stretchable ***,when successfully integrated with underwater vehicles,the U3DTT shows advantages of multiple degrees of freedom in its shape modes,an ultrahigh sensitivity,and fast response times with a low cost and *** real-time 3-dimensional pose of the U3DTT has been predicted with an average root-mean-square error of 0.76 in a water pool,indicating that this developed U3DTT is a promising technology in vehicles with tactile feedback.

关键词： underwater tile stiff

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DCPI-Depth: Explicitly Infusing Dense Correspondence Prior to Unsupervised Monocular Depth Estimation

arXiv

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arXiv 2024年

作者： Zhang, Mengtan Feng, Yi Chen, Qijun Fan, Rui College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Shanghai Institute of Intelligent Science and Technology The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China

There has been a recent surge of interest in learning to perceive depth from monocular videos in an unsupervised fashion. A key challenge in this field is achieving robust and accurate depth estimation in challenging scenarios, particularly in regions with weak textures or where dynamic objects are present. This study makes three major contributions by delving deeply into dense correspondence priors to provide existing frameworks with explicit geometric constraints. The first novelty is a contextual-geometric depth consistency loss, which employs depth maps triangulated from dense correspondences based on estimated ego-motion to guide the learning of depth perception from contextual information, since explicitly triangulated depth maps capture accurate relative distances among pixels. The second novelty arises from the observation that there exists an explicit, deducible relationship between optical flow divergence and depth gradient. A differential property correlation loss is, therefore, designed to refine depth estimation with a specific emphasis on local variations. The third novelty is a bidirectional stream co-adjustment strategy that enhances the interaction between rigid and optical flows, encouraging the former towards more accurate correspondence and making the latter more adaptable across various scenarios under the static scene hypotheses. DCPI-Depth, a framework that incorporates all these innovative components and couples two bidirectional and collaborative streams, achieves state-of-the-art performance and generalizability across multiple public datasets, outperforming all existing prior arts. Specifically, it demonstrates accurate depth estimation in texture-less and dynamic regions, and shows more reasonable smoothness. Our source code will be publicly available at ***/DCPI-Depth upon publication. Copyright © 2024, The Authors. All rights reserved.

关键词： Optical flows

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Secure-by-Construction Synthesis for Control systems

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IEEE Transactions on Automatic Control 2025年第6期70卷 4170-4177页

作者： Zhong, Bingzhuo Liu, Siyuan Caccamo, Marco Zamani, Majid Thrust of Artificial Intelligence Information Hub The Thrust of Intelligent Transportation System Hub China KTH Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden Technical University of Munich TUM School of Engineering and Design Germany University of Colorado Boulder Department of Computer Science United States Ludwig Maximilian University Department of Computer Science Munich Germany

In this note, we present the synthesis of secure-by-construction controllers that address safety and security properties simultaneously in cyber-physical systems. Our focus is on studying a specific security property called opacity, which characterizes the system's ability to maintain plausible deniability of its secret behavior in the presence of an intruder. These controllers are synthesized based on a concept of so-called (augmented) control barrier functions. We propose conditions that facilitate the construction of the desired (augmented) control barrier functions and their corresponding secure-by-construction controllers. To compute these functions, we propose an iterative scheme that leverages iterative sum-of-square programming techniques. This approach enables efficient computation of these functions, particularly for polynomial systems. Finally, we validate the effectiveness of our results through a case study of a vehicle. © 1963-2012 IEEE.

关键词： Iterative methods

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Active Camera View Planning Based on Deep Reinforcement Learning in Indoor Exploration

Active Camera View Planning Based on Deep Reinforcement Lear...

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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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Backstepping-based adaptive control of indoor miniature airship

Backstepping-based adaptive control of indoor miniature airs...

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International Conference on Cybernetics, robotics and Control (CRC)

作者： Hongming Li Yongchun Fang Jinyang Dong Hai Yu Institute of Robotics and Automatic Information Systems College of Artificial Intelligence Nankai University Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China

Recently, research on the flight control of indoor small unmanned airships has attracted much attention. Unmanned airship has characteristics of low manufacturing cost, long dwell time, low energy consumption and so on. Under the premise of ignoring the external wind interference, a controller is designed that makes the airship move to the preset point and stay in the air. The mathematical model of the unmanned airship is first introduced in this paper. A six-degree-of-freedom equation of motion is established after force analysis, and then it is simplified to a three-degree-of-freedom model according to the geometric symmetry of the airship. Subsequently, the motion process of the airship is disassembled into horizontal motion and vertical motion, the backstepping method is used to design the controller, and unknown parameters in the model are processed with adaptive control. Finally, computer simulation experiments are carried out to verify the correctness of the model and the effectiveness of the controller from a mathematical point of view. In this paper, a small unmanned airship motion control system is designed, and its feasibility from the perspective of computer simulation is verified. These studies provide initial exploratory work on control methods for indoor unmanned airships.

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Design of Capsule Robot for Magnetic Gastric Biopsy and Drug Administration 20

Design of Capsule Robot for Magnetic Gastric Biopsy and Drug...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Xu, Zhihui Li, Zongze Liu, Shoubin Hu, Chengzhi Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen China Guangdong Prov. Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China Harbin Institute of Technology School of Mechanical and Electrical Engineering Shenzhen China

ISBN: (纸本)9798350320831

Capsule robots have emerged as a promising tool for the early diagnosis of gastrointestinal diseases. Unlike conventional gastroscopy, they offer the potential for minimally invasive or even non-invasive treatment, and can alleviate discomfort and pain in patients. However, current capsule robots have some limitations. For instance, they lack stomach tissue biopsy and drug administration functions, and the capsule robot used for biopsy does not consider the tolerance of gastrointestinal tissue. Similarly, the capsule robot used for drug administration does not account for the outlet speed of drug administration. This paper proposes a new biopsy method using a magnetically manipulated capsule robot and analyzes the principles governing the robot's manipulation during the biopsy and drug administration processes. Furthermore, an ANSYS gastric model was established and used to simulate and experimentally analyze damage to the gastric tissue model from different types of biopsy needles and their moving speeds. The appropriate type of biopsy needle and moving speed were determined to prevent damage to the gastric tissue. The study also used FLUENT to determine the appropriate thrust at the entrance of the drug cavity and the impact of the drug density on the drug outlet velocity to ensure complete adherence of the drug to the lesion. © 2023 IEEE.

关键词： Biopsy

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Force Control of Polishing Robots Considering Sensor Measurement Sensitivity and Hysteresis Characteristics

Force Control of Polishing Robots Considering Sensor Measure...

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Chinese Control and Decision Conference, CCDC

作者： Chunhui He Qingxiang Wu Shuzhen Diao Ning Sun Institute of Robotics and Automatic Information Systems College of Artificial Intelligence Nankai University Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

In virtue of its excellent flexibility, high compliance, and convenient maintenance, pneumatic polishing equipment is widely used in the surface polishing of manufacturing products. However, due to the harsh working environment of polishing robots (e.g., high temperatures, humidity, and vibrations), the probability of inaccurate measurements is increased. At the same time, pneumatic systems have strong hysteresis and nonlinear characteristics because of the materials, friction, and gas resistance. The above issues will affect the accurate tracking performance of pneumatic control systems. Therefore, this paper proposes a force control framework considering hysteresis characteristics and sensor measurement sensitivity. Furthermore, an adaptive dynamic surface control method is designed to achieve precise force control under measurement sensitivity. In addition, the stability analysis is completed by using Lyapunov techniques, and all states of the closed-loop system are also guaranteed to be bounded. Finally, several groups of simulation results demonstrate the effectiveness of the proposed method.

关键词： Temperature measurement Sensitivity Force measurement Surface resistance Measurement uncertainty Pneumatic systems Robot sensing systems

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A Directed Jump Point Search with Improved Preprocess for Path Planning

A Directed Jump Point Search with Improved Preprocess for Pa...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Zongquan Xie Lei Cheng Xiang Li Xiuqi Chen School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan China

We introduce a new algorithm called directed JPS+(Jump Point Search Plus) that addresses the large memory overheads of JPS+ and improves its performance in cases where the obstacle scale is small. Our approach involves two main modifications. First, we reduce memory usage by recording only jump points in the preprocessing stage instead of eight labels for each nodes in JPS+. And we introduce a technique to connect these precomputed jump points into jump point set. Second, we apply an optimization to JPS+ that speeds up path planning in maps with small obstacle scale and it has no negative impact on other cases. We implement our algorithm in Python and evaluate its performance in terms of memory usage and planning time. Our results demonstrate that it saves memory and speeds up the path planning, particularly in maps with small obstacle scale.

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Shape Optimization of Magnetorheological Brake for Performance Enhancement

Shape Optimization of Magnetorheological Brake for Performan...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Shi, Qiuyu Liu, Fajiang Wu, Xinyu Gao, Fei Southern University of Science and Technology Shenzhen518005 China Shenzhen Institute of Advanced Technology Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China

ISBN: (纸本)9781665481090

Magnetorheological (MR) rotary brakes leverage the magnetically controllable rheological properties of MR fluids to provide damping torque in lower limb assistance devices. This paper utilizes an optimization algorithm (Whale Optimization Algorithm (WOA)) to optimize the geometric dimension of the MR brake to enhance field-dependent brake torque. First, the mechanical design and optimization process of the MR brake were outlined. Then, the magnetic density of the MR fluid is evaluated using the ANSYS platform. With that, the WOA was exploited to optimize key design parameters across multiple iterations. According to the simulated results, the torque was improved from 17.39 Nm to 25.89 Nm, which increased by 48%. Finally, a prototype with the initial dimension was fabricated and preliminarily tested. © 2024 IEEE.

关键词： Shape optimization

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