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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Zhengcai Cao Ji Xia Yinbin Shi MengChu Zhou State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China College of Information Science and Technology Beijing University of Chemical Technology Beijing China School of Information and Electronic Engineering Zhejiang Gongshang University Hangzhou China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Image captioning is a multi-modal task that enables the transformation from scene images to natural language, providing valuable insights for visually impaired individuals to understand their environment. Therefore, its application to wearable navigation devices for visually impaired individuals holds immense potential. However, in practical applications, confusion between scene visuals and semantics, coupled with model complexity, often leads to performance degradation, resulting in inaccurate environmental interpretation. In light of this, we introduce a Lightweight De-confounding Transformer Network (LDTNet) for image captioning equipped with a Causal Adjustment module to eliminate confounders. Moreover, we design a Suppression Gate Unit that efficiently integrates fine-grained information from shallow features, while reducing the number of network layers to have a lightweight model. Experimental results demonstrate that our approach not only addresses the visual-semantic confusion issue effectively but also improves the response speed of wearable devices in comparison with the state of the art. Twenty volunteers are recruited to evaluate LDTNet’s efficacy in real-world settings in terms of both response speed and generated outputs by wearing the resulting assistive navigation devices. The outcomes well show its outstanding performance and great potential for visualy impaired individuals to use.

关键词： Performance evaluation Hands Visualization Navigation System performance Semantics Natural languages Logic gates Transformers Wearable devices

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A modified YOLOv4 detection method for a vision-based underwater garbage cleaning robot

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Frontiers of Information Technology & Electronic engineering 2022年第8期23卷 1217-1228页

作者： Manjun TIAN Xiali LI Shihan KONG Licheng WU Junzhi YU First Research Institute of the Ministry of Public Security of PRC Beijing 100048China School of Information Engineering Minzu University of ChinaBeijing 100081China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

To tackle the problem of aquatic environment pollution,a vision-based autonomous underwater garbage cleaning robot has been developed in our *** propose a garbage detection method based on a modified YOLOv4,allowing high-speed and high-precision object ***,the YOLOv4 algorithm is chosen as a basic neural network framework to perform object *** the purpose of further improvement on the detection accuracy,YOLOv4 is transformed into a four-scale detection *** improve the detection speed,model pruning is applied to the new *** virtue of the improved detection methods,the robot can collect garbage *** detection speed is up to 66.67 frames/s with a mean average precision(mAP)of 95.099%,and experimental results demonstrate that both the detection speed and the accuracy of the improved YOLOv4 are excellent.

关键词： Object detection Aquatic environment Garbage cleaning robot Modified YOLOv4

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A high-accuracy, low-budget Sensor Glove for Trajectory Model Learning 20

A high-accuracy, low-budget Sensor Glove for Trajectory Mode...

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20th International Conference on Advanced robotics, ICAR 2021

作者： Denz, Robin Demirci, Rabia Cansev, M. Ege Bliek, Adna Beckerle, Philipp Rueckert, Elmar Rottmann, Nils Institute For Robotics and Cognitive Systems University of Luebeck Luebeck23562 Germany Chair of Autonomous Systems and Mechatronics Friedrich-Alexander-University Department of Electrical Engineering Erlangen-Nürnberg Germany Chair of Cyber-Physical-Systems Montanuniversität Leoben Leoben Austria

ISBN: (纸本)9781665436847

Sensor gloves are gaining importance in tracking hand and finger movements in virtual reality applications as well as in scientific research. They introduce an unrestricted way of capturing motion without the dependence on direct line of sight as for visual tracking systems. With such sensor gloves, data of complex motion tasks can be recorded and used for modeling probabilistic trajectories or teleoperation of robotic arms. While a multitude of sensor glove designs relying on different functional principles exist, these approaches require either sensitive calibration and sensor fusion methods or complex manufacturing processes. In this paper, we propose a low-budget, yet accurate sensor glove system that uses flex sensors for fast and efficient motion tracking. We evaluate the performance of our sensor glove, such as accuracy and latency, and demonstrate the functionality by recording motion data for learning probabilistic movement models. © 2021 IEEE.

关键词： Budget control

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Replacing Gallium Oxide shell with conductive Ag: Toward printable and recyclable composite for highly stretchable electronics, electromagnetic shielding, and thermal interfaces

arXiv

引用

arXiv 2025年

作者： Hajalilou, Abdollah Parvini, Elahe Morgado, Tiago A. Lopes, Pedro Alhais Jorge, M. Estrela Melo Freitas, Marta Tavakoli, Mahmoud Institute of Systems and Robotics Department of Electrical Engineering University of Coimbra Coimbra3030-290 Portugal Instituto de Telecomunicações Department of Electrical Engineering University of Coimbra Coimbra3030-290 Portugal Faculdade de Ciências Universidade de Lisboa Lisboa1749-016 Portugal

Liquid metal (LM)-based composites hold promise for soft electronics due to their high conductivity and fluidic nature. However, the presence of α-Ga2O3 and GaOOH layers around LM droplets impairs conductivity and performance. We tackle this issue by replacing the oxide layer with conductive silver (Ag) using an ultrasonic-assisted galvanic replacement reaction. The Ag-coated nanoparticles form aggregated, porous microparticles that are mixed with Styrene-Isoprene-Styrene (SIS) polymers, resulting in a digitally printable composite with superior electrical conductivity and electromechanical properties compared to conventional fillers. Adding more LM enhances these properties further. The composite achieves EMI shielding effectiveness (SE) exceeding 75 dB in the X-band frequency range, even at 200% strain, meeting stringent military and medical standards. It is applicable in wireless communications, Bluetooth signal blocking, and as a thermal interface material (TIM). Additionally, we highlight its recyclability using a biodegradable solvent, underscoring its eco-friendly potential. This composite represents a significant advancement in stretchable electronics and EMI shielding, with implications for wearable and bioelectronic applications. © 2025, CC BY-NC-ND.

关键词： Electromagnetic shielding

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Collision-Aware MPCC Integrated with Neural Augmentation for Quadrotor Trajectory Tracking

Collision-Aware MPCC Integrated with Neural Augmentation for...

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International Conference on Mechatronics (ICM)

作者： Chuanqi Hu Jin Wang Yikai Chen Yonghang Chen Zhi Zheng Jun Meng Guodong Lu Polytechnic Institute Zhejiang University Hangzhou China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou China Zhejiang Key Laboratory of Industrial Big Data and Robot Intelligent Systems Zhejiang University Hangzhou China Robotics Research Center of Yuyao City Ningbo China School of Mechanical Engineering Zhejiang University Hangzhou China National Elite Institute of Engineering Chongqing University Chongqing China College of Electrical Engineering Zhejiang University Hangzhou China Center for Data Mining and Systems Biology College of Electrical Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798331533892

ISBN: (纸本)9798331533908

This paper presents a trajectory tracking algorithm designed for autonomous quadrotors to navigate complex dy-namic environments that is resilient to collision disturbances. Since it combines Model Predictive Contouring Control (MPCC) with the capabilities of neural networks, our method is named MPCC Integrated with Neural Augmentation (MINA). By equip-ping the quadrotor with PVDF piezoelectric sensors, we achieve real-time perception of collision forces and utilize S4D-Conv Adaptive Net Architecture (SANA) for state computation, a network that integrates the advantages of S4D and convolutional kernels to enhance the accuracy of state predictions. We incorporate the predicted results into the MPCC framework to optimize the thrust output of the quadrotor for the next time step, ensuring precise trajectory tracking. Experimental validation demonstrates the reliability and effectiveness of our algorithm, providing an innovative solution for autonomous flight and trajectory tracking of quadrotors in complex dynamic environments.

关键词： Trajectory tracking Navigation Heuristic algorithms Neural networks Reliability theory Predictive models Prediction algorithms Real-time systems Sensors Quadrotors

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Fast Path Planning for Autonomous Vehicle Parking with Safety-Guarantee using Hamilton-Jacobi Reachability

arXiv

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arXiv 2023年

作者： Chi, Xuemin Zeng, Jun Huang, Jihao Liu, Zhitao Su, Hongye State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Hybrid Robotics Group the Department of Mechanical Engineering UC Berkeley United States

We present a fast planning architecture called Hamilton-Jacobi-based bidirectional A* (HJBA*) to solve general tight parking scenarios. The algorithm is a two-layer composed of a high-level HJ-based reachability analysis and a lower-level bidirectional A* search algorithm. In high-level reachability analysis, a backward reachable tube (BRT) concerning vehicle dynamics is computed by the HJ analysis and it intersects with a safe set to get a safe reachable set. The safe set is defined by constraints of positive signed distances for obstacles in the environment and computed by solving QP optimization problems offline. For states inside the intersection set, i.e., the safe reachable set, the computed backward reachable tube ensures they are reachable subjected to system dynamics and input bounds, and the safe set guarantees they satisfy parking safety with respect to obstacles in different shapes. For online computation, randomized states are sampled from the safe reachable set, and used as heuristic guide points to be considered in the bidirectional A* search. The bidirectional A* search is paralleled for each randomized state from the safe reachable set. We show that the proposed two-level planning algorithm is able to solve different parking scenarios effectively and computationally fast for typical parking requests. We validate our algorithm through simulations in large-scale randomized parking scenarios and demonstrate it to be able to outperform other state-of-the-art parking planning algorithms. Copyright © 2023, The Authors. All rights reserved.

关键词： Motion planning

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Lidar-Inertial and Downward Vision Based Mobile Robot SLAM in Digital Workshops

Lidar-Inertial and Downward Vision Based Mobile Robot SLAM i...

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Data Driven Control and Learning systems (DDCLS)

作者： Yanchao Zhang Hao Geng Bin Liu Yinlong Zhang Xudong Yuan Sichao Zhang School of Information Science and Engineering Shenyang University of Technology Shenyang China Guangzhou Institute of Industrial Intelligence Guangzhou China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

In order to solve the problems of long-term cumulative error and the absence of absolute pose in the existing Lidar-Inertial Measurement Unit (IMU) fusion methods for Automated Guided Vehicle (AGV) Simultaneous Localization and Mapping (SLAM), we propose a new SLAM method for mobile robot, integrating Lidar, IMU, and a downward vision camera. Firstly, we tightly couple Lidar-IMU and downward vision camera using a multimodal fusion framework. Downward visual measurements are integrated as QR factors into the factor graph, providing absolute pose information to correct cumulative error in the Lidar-IMU system and enable the joint pose estimation of the AGV. Secondly, an enhanced Iterative Closest Point (ICP) point cloud matching algorithm has been developed to correct the incorrect pose. This approach achieves Scan-to-Map alignment by employing a coarse-to-fine matching strategy, thereby enhancing the accuracy of point cloud alignment. Finally, the extended Kalman filter is used to optimize the Lidar pose drift, as well as the Lidar mapping effectively by using the Lidar-IMU as the measurements and the downward visual measurements as the updates. The algorithm has been extensively evaluated on the developed AGV experimental platform. The experimental results show that the position error is less than 0.02 meters and the orientation error is less than 1°, which solves the problems of long-term error accumulation and the lack of absolute pose information for AGV navigation.

关键词： Point cloud compression Visualization Laser radar Simultaneous localization and mapping Conferences Robot vision systems Measurement uncertainty

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Velocity Obstacle for Polytopic Collision Avoidance for Distributed Multi-robot systems

arXiv

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arXiv 2023年

作者： Huang, Jihao Zeng, Jun Chi, Xuemin Sreenath, Koushil Liu, Zhitao Su, Hongye State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Hybrid Robotics Group The Department of Mechanical Engineering UC Berkeley United States

Obstacle avoidance for multi-robot navigation with polytopic shapes is challenging. Existing works simplify the system dynamics or consider it as a convex or non-convex optimization problem with positive distance constraints between robots, which limits real-time performance and scalability. Additionally, generating collision-free behavior for polytopic-shaped robots is harder due to implicit and non-differentiable distance functions between polytopes. In this paper, we extend the concept of velocity obstacle (VO) principle for polytopic-shaped robots and propose a novel approach to construct the VO in the function of vertex coordinates and other robot’s states. Compared with existing work about obstacle avoidance between polytopic-shaped robots, our approach is much more computationally efficient as the proposed approach for construction of VO between polytopes is optimization-free. Based on VO representation for polytopic shapes, we later propose a navigation approach for distributed multi-robot systems. We validate our proposed VO representation and navigation approach in multiple challenging scenarios including large-scale randomized tests, and our approach outperforms the state of art in many evaluation metrics, including completion rate, deadlock rate, and the average travel distance. Copyright © 2023, The Authors. All rights reserved.

关键词： Multipurpose robots

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Optimal swing motion control for single-rod brachiation robot *

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IFAC-PapersOnLine 2023年第2期56卷 6320-6325页

作者： Juraj Lieskovský Hijiri Akahane Jaroslav Bušek Ikuo Mizuuchi Tomáš Vyhlídal Department of Instrumentation and Control Engineering Faculty of Mechanical Engineering and CIIRC-Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Technická 4 Prague 6 16607 Czechia Department of Mechanical Systems Engineering Tokyo University of Agriculture and Technology 2-24-16 Naka-cho Koganei-city Tokyo Japan

This paper focuses on the optimal swing and rotation control of a single-rod brachiation robot by repositioning its center of gravity. First, a time-optimal control is proposed and analyzed. It utilizes impulses of force at the robot's zero-angle and the turning-angle positions to reposition the center of gravity. Then, a practical implementation that addresses force limits is proposed, in the form of a PD controller paired with input-output linearization which uses the optimal solution as a setpoint. Both control policies are validated through simulations as a preliminary step to laboratory validation on an assembled single-rod robot. Enhanced attention is paid to energy evolution during the swing and rotation of the robot, in particular to the energy pumping achieved by repositioning the center of gravity.

关键词： Single-link robot optimal swing nonlinear control brachiation

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CapsuleBot: A Novel Hybrid Aerial-Ground Bi-Copter Robot with Two Actuated-Wheel-Rotors

arXiv

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arXiv 2023年

作者： Zheng, Zhi Cai, Qifeng Wang, Jin Xu, Xinhang Cao, Muqing Yu, Huan Li, Jihao Meng, Jun Lu, Guodong State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310027 China Robotics Institute of Zhejiang University Zhejiang University Hangzhou310027 China Robotics Research Center of Yuyao City Ningbo315400 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore Robotics Institute Carnegie Mellon University 5000 Forbes Avenue Pittsburgh15217 United States Center for Data Mining and Systems Biology College of Electrical Engineering Zhejiang University Hangzhou310027 China

This paper presents the design, modeling, and experimental validation of CapsuleBot, a novel hybrid aerial-ground bi-copter robot designed for long-endurance and low-noise operations. CapsuleBot combines the maneuverability of a bi-copter in the air with the low power consumption and low noise of a two-wheel self-balancing robot on the ground. To achieve this, we design an innovative mechanical structure named the actuated-wheel-rotor, which uses a servo motor and a brushless motor to function as both a tilting rotor in the air and an actuated wheel on the ground. CapsuleBot is equipped with two actuated-wheel-rotors, enabling it to achieve hybrid aerial-ground propulsion using only four motors, with no additional motors required compared to a bi-copter. Additionally, we develop comprehensive dynamics and control systems for both air and wheel mode, based on the bi-copter model and the two-wheel self-balancing robot model. A prototype of CapsuleBot is constructed, and its performance in terms of low power consumption and low noise is validated through experiments. Challenging tasks demonstrate CapsuleBot’s capability to climb steep, fly over cliffs, and traverse rough terrains. Copyright © 2023, The Authors. All rights reserved.

关键词： Antenna grounds

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