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IEEE International Conference on robotics and Automation (ICRA)

作者： David R. Gomes Miguel Ayala Botto Pedro U. Lima Laboratory of Robotics and Engineering Systems ISR/IST Universidade de Lisboa Portugal IDMEC Instituto Superior Técnico Universidade de Lisboa Portugal

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Advancements in Automated Driving systems (ADSs) have enabled the achievement of a certain level of autonomy while commuting in a car. However, emergency and high-speed maneuvers still arise as significant challenges for ADSs due to the intrinsic nonlinearity and fast-paced behavior of such events. These maneuvers are a distinctive feature within the recently established motorsport discipline of Autonomous Racing (AR). In this work, we explore the use of Learning-based Model Predictive Control (LMPC) to address possible model mismatches of the first principles model in high-speed racing. To this end, a Model Predictive Contouring Control (MPCC) (a specific formulation of the standard Model Predictive Control, MPC) is formulated, and a Neural Network (NN) that leverages the use of Feedforward and Recurrent layers is employed to learn the errors of the first principles model. By combining the NN with the first principles model, the LMPC is born, capable of accurately predicting the future with a computational effort compatible with real-time feasibility, effectively handling the vehicle at its limits. Furthermore, the controller can adapt to changing environments by training the NN during the race. The MPCC (formulation without the NN) is deployed on a real autonomous formula student racing car showing an improvement of 16 % in mean lap times across the same track between a common geometric controller. The LMPC is analyzed in a high-fidelity simulator, achieving an improvement of 8.9 % in mean lap times when compared to the MPCC.

关键词： Training Adaptation models Computational modeling Artificial neural networks Predictive models Real-time systems Automobiles

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A Look-Up Table Based Inverter Nonlinearity Compensation Method Considering Parameter Inconsistency of Upper and Lower Bridge Arms

A Look-Up Table Based Inverter Nonlinearity Compensation Met...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Yonghe Huang Dianguo Xu Yan Xu Yong Yu Junyu Zhao Xubo Gong School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China The State key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

In motor drive systems, voltage source inverter (VSI) nonlinearity will produce voltage error, cause current harmonics, and affect the control performance. Among the VSI nonlinearity factors, the parasitic capacitance is the fundamental cause of the nonlinear relationship between voltage error and phase current. If the parameter inconsistency of the upper and lower bridge arm is not considered, the voltage error is an odd function. However, in practical applications, the parameters of the upper and lower bridge arms are usually slightly different, and the voltage error will no longer be an odd function. Considering the influence of parameter inconsistency, this article proposes an accurate look-up table (LUT) based method for VSI nonlinearity compensation. By injecting positive staircase current and negative staircase current separately in self-commissioning process, an accurate voltage error LUT is obtained through numerical fitting methods. The proposed method does not require any parameter of power devices. Experimental results verify the effectiveness of the proposed method.

关键词： Industrial electronics Motor drives Accuracy Voltage source inverters Fitting Bridge circuits Table lookup

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Combined Locomotion and Direction Control of Ferrofluidic Robots*

Combined Locomotion and Direction Control of Ferrofluidic Ro...

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International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Qinkai Chen Haozhe Feng Xinjian Fan Lining Sun Zhan Yang Hui Xie School of Mechanical and Electrical Engineering Soochow University Suzhou China State Key Laboratory of Robotics and Systems Harbin Institute of Technology Yikuang Harbin China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

As the characteristics of low invasiveness, good controllability and deformability, ferrofluid robots have enormous potential for technological applications in the medical field. With the volume of ferromagnetic fluid robots increases, a motion control strategy coupled with magnetic moment and gradient force is usually adopted which makes it impossible for the robot to perform complex movements and limits the application of the ferrofluid robot. By designing a control system that decouples magnetic torque and magnetic gradient force, joint control of the locomotion and direction of a ferrofluid robot has been achieved. The results indicate that the miniature ferrofluid robot (MFR) has achieved directional controllable trajectory motion and ultimately achieved autonomous path selection. These extended functions can further promote the medical application of micro robots in closed and complex environments such as human blood vessels.

关键词： Ferrofluid Targeted drug delivery Torque Three-dimensional displays Force Blood vessels Trajectory Motion control Robots Tumors

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Bio-inspired visual relative localization for large swarms of UAVs

Bio-inspired visual relative localization for large swarms o...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Martin Křížek Matouš Vrba Antonella Barišić Kulaš Stjepan Bogdan Martin Saska Faculty of Electrical Engineering Czech Technical University in Prague Prague Laboratory for Robotics and Intelligent Control Systems (LARICS) Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

We propose a new approach to visual perception for relative localization of agents within large-scale swarms of Unmanned Aerial Vehicles (UAVs). Inspired by biological perception utilized by schools of sardines, swarms of bees, and other large groups of animals capable of moving in a decentralized yet coherent manner, our method does not rely on detecting individual neighbors by each agent and estimating their relative position, but rather we propose to regress a neighbor density over distance. This allows for a more accurate distance estimation as well as better scalability with respect to the number of neighbors. Additionally, a novel swarm control algorithm is proposed to make it compatible with the new relative localization method. We provide a thorough evaluation of the presented methods and demonstrate that the regressing approach to distance estimation is more robust to varying relative pose of the targets and that it is suitable to be used as the main source of relative localization for swarm stabilization.

关键词： Location awareness Visualization Scalability Estimation Object detection Autonomous aerial vehicles Robustness

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A Graph-Based Self-Calibration Technique for Cable-Driven Robots with Sagging Cable

A Graph-Based Self-Calibration Technique for Cable-Driven Ro...

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

作者： M. R. Dindarloo A. S. Mirjalili S. A. Khalilpour R. Khorrambakht Stephan Weiss H. D. Taghirad Advanced Robotics and Automated Systems (ARAS) Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering Tandon School of Engineering Control/Robotics Research Laboratory New York University Brooklyn NY Department of Smart Systems Technologies University of Klagenfurt Austria

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

The efficient operation of large-scale Cable-Driven Parallel Robots (CDPRs) relies on precise calibration of kinematic parameters and the simplicity of the calibration process. This paper presents a graph-based self-calibration framework that explicitly addresses cable sag effects and facilitates the calibration procedure for large-scale CDPRs by only relying on internal sensors. A unified factor graph is proposed, incorporating a catenary cable model to capture cable sagging. The factor graph iteratively refines kinematic parameters, including anchor point locations and initial cable length, by considering jointly onboard sensor data and the robot’s kineto-static model. The applicability and accuracy of the proposed technique are demonstrated through Finite Element (FE) simulations, on both large and small-scale CDPRs subjected to significant initialization perturbations.

关键词： Meters Accuracy Perturbation methods Kinematics Robot sensing systems End effectors Software Calibration Sensors Finite element analysis

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Performance Comparison of Teleoperation Interfaces for Ultra-Lightweight Anthropomorphic Arms

Performance Comparison of Teleoperation Interfaces for Ultra...

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

作者： Filip Zorić Alejandro Suarez Goran Vasiljević Matko Orsag Zdenko Kovačić Anibal Ollero Laboratory for Robotics and Intelligent Control Systems (LARICS) Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia GRVC Robotics Lab University of Seville Sevilla Spain

This paper presents a comparative performance evaluation of three different teleoperation interfaces for very low weight (<3 kg) anthropomorphic dual arms intended to conduct complex manipulation tasks involving a certain level of dexterity, accuracy and agility, either in ground service or in aerial manipulation applications. A visual human pose estimation system is developed to obtain the Cartesian and joint values of the user, which are mapped to the corresponding pose of the dual arm manipulator exploiting the equivalent human-robot kinematics. A leader-follower scheme is also presented, using a reduced scale dual arm that can replicate directly the joint positions of the leader arms to the follower arms. A 6-DOF (degrees of freedom) joystick is proposed to generate linear motions more accurately. A total of 60 ground tests were conducted involving 10 participants to determine the accuracy and time performance in two benchmarks (box edges and S contour tracking). Finally, the visual and leader-follower interfaces were evaluated with the dual arm aerial manipulator on flight tests, reporting several findings derived from the system evaluation.

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A distributed variable density path search and simplification method for industrial manipulators with end-effector's attitude constraints

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Frontiers of Information Technology & Electronic engineering 2023年第4期24卷 536-552页

作者： Jin WANG Shengjie LI Haiyun ZHANG Guodong LU Yichang FENG Peng WANG Jituo LI State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering.Zhejiang UniversityHangzhou 310027China Engineering Research Center for Design Engineering and Digital Twin of Zhejiang Province School of Mechanical EngineeringZhejiang UniversityHangzhou 310027China School of Robotics Ningbo University of TechnologyNingbo 31521lChina

In many robot operation scenarios, the end-effector's attitude constraints of movement are indispensable for the task process, such as robotic welding, spraying, handling, and stacking. Meanwhile, the inverse kinematics, collision detection, and space search are involved in the path planning procedure under attitude constraints, making it difficult to achieve satisfactory efficiency and effectiveness in practice. To address these problems, we propose a distributed variable density path planning method with attitude constraints(DVDP-AC) for industrial robots. First, a position – attitude constraints reconstruction(PACR) approach is proposed in the inverse kinematic solution. Then, the distributed signed-distance-field(DSDF) model with single-step safety sphere(SSS) is designed to improve the efficiency of collision detection. Based on this, the variable density path search method is adopted in the Cartesian space. Furthermore, a novel forward sequential path simplification(FSPS) approach is proposed to adaptively eliminate redundant path points considering path accessibility. Finally, experimental results verify the performance and effectiveness of the proposed DVDP-AC method under end-effector's attitude constraints, and its characteristics and advantages are demonstrated by comparison with current mainstream path planning methods.

关键词： Path planning Industrial robots Distributed signed-distance-field Attitude constraints Path simplification

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Exoskeleton-Based Lower Limb Rehabilitation Robot Design and Simulation for Children with Cerebral Palsy

Exoskeleton-Based Lower Limb Rehabilitation Robot Design and...

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2024 International Convention on Rehabilitation engineering and Assistive Technology and World Rehabilitation Robot Convention, i-CREATE and WRRC 2024

作者： Cao, Wujing Zhang, Shuo Zou, Yupeng Guo, Xinqiang Li, Changyu Wang, Jingxin Kobsiriphat, Worawarit Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518005 China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems China School of Mechanical Engineering China University of Petroleum China Jining Zhongke Intelligent Technology Co. Ltd. China Zhengzhou Central Hospital Zhengzhou University Department of Rehabilitation Medicine Zhengzhou China National Metal and Materials Technology Center Thailand

ISBN: (纸本)9798350355123

Squat gait is the most common abnormal gait in children with cerebral palsy. Gait training with lower limb rehabilitation robots can improve rehabilitation efficiency and reduce manual labor for them. A novel exoskeleton-based lower limb rehabilitation robot for children with cerebral palsy is proposed, considering the squat gait characteristics of children with cerebral palsy. The structure of the lower limb rehabilitation robot, which combines hip and knee with 4 active degrees of freedom exoskeleton and mobile walker, is designed and optimized. Static analysis of the key mechanical structure of the exoskeleton is conducted using ANSYS Workbench, and local structures are optimized to ensure the safety factor of the mechanical structure is greater than 1, guaranteeing reasonable structural strength and stiffness design. Dynamic simulation analysis based on the ADAMS model validates the reliability and dynamic walking effect of the lower limb exoskeleton rehabilitation robot, obtaining the curve relationship between joint angles and motion cycles, thus verifying the effectiveness of the mechanical system motion. © 2024 IEEE.

关键词： Exoskeleton (robotics)

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Formation Control of Unmanned Underwater Vehicles With Unknown Absolute Position Using Rigid Graph-Based MPC

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IEEE Internet of Things Journal 2025年

作者： Fu, Bowen Zhu, Daqi Chen, Mingzhi Yang, Simon X. University of Shanghai for Science and Technology Shanghai200093 China University of Guelph Advanced Robotics and Intelligent Systems Laboratory School of Engineering GuelphONN1G2W1 Canada

Formation control of unmanned underwater vehicles (UUVs) is of great significance to the Internet of Underwater Things (IoUT). Currently, various methods are employed for UUV formation control. Among them, rigid graph-based approaches, which rely solely on relative information between UUVs, are particularly suitable for underwater environments. However, traditional rigid graph-based formation control methods often face challenges such as control jumps and weak robustness in dynamic underwater environments. To address these challenges, a novel rigid graph-based model predictive controller (RGMPC) is proposed in this paper. The proposed approach integrates model predictive control with traditional rigid graph-based methods, effectively avoiding issues such as control jumps and thrust saturation while enhancing robustness. Moreover, constraints are constructed using backstepping methods to theoretically ensure the closed-loop stability of the algorithm. Finally, the algorithm is validated through extensive simulations based on mathematical models and further tested in the Gazebo simulator, fully demonstrating its feasibility and effectiveness. © 2014 IEEE.

关键词： Predictive control systems

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A Novel Transfer Learning Method for Robot Bearing Fault Diagnosis Based on Deep Convolutional Residual Wasserstein Adversarial Network 16th

A Novel Transfer Learning Method for Robot Bearing Fault Dia...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Pan, Bing Xiong, Xin Hu, Hailiang He, Jun Yang, Shixi The State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou China The Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province School of Mechanical Engineering Zhejiang University Hangzhou China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai200444 China Hangzhou Steam Turbine Power Group Co. Ltd. Hangzhou China

ISBN: (纸本)9789819965007

In the process of robot bearing fault diagnosis based on data-driven, transfer learning is an effective method to solve the lack of labeled data, and data distribution difference between source domain data and target domain data will lead to domain drifts under variable working conditions. In this paper, a robot bearing fault diagnosis method based on deep convolutional residual Wasserstein adversarial network (DCRWAN) is proposed to reduce domain offsets and improve the robot bearing fault diagnosis accuracy. In the proposed method, a deep convolutional residual network is constructed to extract the transferable features of source domain and target domain. Then, a domain discrimination module is constructed and the domain adversarial training is carried out to minimize the distribution discrepancy of cross-domain by the Wasserstein loss function. At the same time, a domain distribution discrepancy metrics module is applied to estimate the difference of features distribution between two domains, and further fine-tuning the network parameters to obtain domain-invariant and class-separable features for the classification. The average accuracy of the two transfer tasks using this method is 95.65% and 93.75%, respectively, and the results show that the method effectively reduces the domain differences caused by varying working conditions and improves the fault diagnosis accuracy of robot bearings under variable working conditions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Failure analysis

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