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检索条件"机构=Laboratory for Robotics and Systems in Engineering and Science"

共 819 条记录，以下是151-160 订阅

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Online Multi-Contact Feedback Model Predictive Control for Interactive Robotic Tasks

Online Multi-Contact Feedback Model Predictive Control for I...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Seo Wook Han Maged Iskandar Jinoh Lee Min Jun Kim Intelligent Robotic Systems Laboratory Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea Institute of Robotics and Mechatronics German Aerospace Center (DLR) Wessling Germany Department of Mechanical Engineering KAIST Daejeon Republic of Korea

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In this paper, we propose a model predictive control (MPC) that accomplishes interactive robotic tasks, in which multiple contacts may occur at unknown locations. To address such scenarios, we made an explicit contact feedback loop in the MPC framework. An algorithm called Multi-Contact Particle Filter with Exploration Particle (MCP-EP) is employed to establish real-time feedback of multi-contact information. Then the interaction locations and forces are accommodated in the MPC framework via a spring contact model. Moreover, we achieved real-time control for a 7 degrees of freedom robot without any simplifying assumptions by employing a Differential-Dynamic-Programming algorithm. We achieved 6.8kHz, 1.9kHz, and 1.8kHz update rates of the MPC for 0, 1, and 2 contacts, respectively. This allows the robot to handle unexpected contacts in real time. Real-world experiments show the effectiveness of the proposed method in various scenarios.

关键词： Feedback loop Prediction algorithms Real-time systems Particle filters Task analysis Springs Robots

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A Lightweight De-confounding Transformer for Image Captioning in Wearable Assistive Navigation Device

A Lightweight De-confounding Transformer for Image Captionin...

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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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Biodegradable Gliding Paper Flyers Fabricated Through Inkjet Printing

Biodegradable Gliding Paper Flyers Fabricated Through Inkjet...

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

作者： Luca Girardi Rui Wu Yuki Fukatsu Hiroki Shigemune Stefano Mintchev Department of Environmental Systems Science Environmental Robotics Laboratory ETH Zurich Zurich Switzerland Swiss Federal Institute for Forest Snow and Landscape Research (WSL) Birmensdorf Switzerland Department of Electrical Engineering Shibaura Institute of Technology Tokyo Japan

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Seed-inspired minimalist microflyers are showing potential as dispersal platforms for sensor networks and seeds. Their function relies on the sheer number of low-cost flyers, inevitably raising concerns about the post-operation environmental impact. We propose a biodegradable paper glider platform fabricated through origami inkjet printing. This method can fold origami along printing patterns on different paper varieties. We created a printing pattern that allows 2D paper sheets to self-fold into a 3D flying wing glider with designable wing geometry and center of gravity (CG). The design allows stable and repeatable gliding behavior, proven in our gliding tests. It successfully achieves the dispersal of multiple gliders from a hovering drone, covering an average horizontal distance larger than the release height. We also tested the biodegradation of different paper types compatible with the printing method, showing near-complete degradation after 15 weeks in moist soil. Our study presents a novel, potentially scalable approach for fabricating environmentally friendly microflyers, offering new avenues for remote environmental sensing and automated forest restoration programs.

关键词： Geometry Atmospheric modeling Forestry Aerodynamics Three-dimensional printing Stability analysis Ink jet printing Seeds (agriculture) Thermal stability Paints

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Motion Planning for Nonlinear Robotic System based on ADMM and Convex Feasible Set Algorithm

Motion Planning for Nonlinear Robotic System based on ADMM a...

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IEEE Conference on Decision and Control

作者： Ruishuang Chen Zaiyue Yang Jie Cheng Zhihui Liang Department of Mechanical and Energy Engineering and the Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology Shenzhen China

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

In the motion planning of robot, nonlinear dynamic constraints and obstacle avoidance constraints make the problem highly non-convex and difficult to solve. In this paper, a general algorithmic framework for trajectory optimization is proposed based on alternating direction method of multipliers (ADMM) and convex feasible set algorithm (CFS). The ADMM framework decomposes the original problem into an optimal control sub-problem with only dynamic constraints and a subproblem with only obstacle avoidance constraints, while the sub-problem with obstacle avoidance constraints is solved via CFS based on the geometric properties of the feasible region. The convergence of proposed algorithm is proven, and the simulation results in different cases verify the feasibility and effectiveness of proposed algorithm.

关键词： Heuristic algorithms Simulation Dynamics Convex functions Planning Nonlinear dynamical systems Collision avoidance

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Online Optimal Energy Management for Building Heating with Thermal Energy Storage

Online Optimal Energy Management for Building Heating with T...

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IEEE Conference on Decision and Control

作者： Mengfan Cao Shibo Chen Haoyu Miao Zaiyue Yang Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems and the Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This paper studies the online optimal energy management problem for the building heating system. This system is driven by electric heat pumps, and equipped with the thermal energy storage (TES) that provides heat flexibility. The temporal coupling introduced by building temperature dynamics and TES energy level dynamics, together with the uncertainties of real-time electricity price and outdoor temperature, pose the optimal energy management problem a computationally challenging one. Hence, based on the Lyapunov optimization method, an online algorithm is proposed to minimize the long-term time average cost of heating system. Our algorithm can ensure the building temperature constraints and TES energy level constraints are satisfied all the time. The maximum optimality gap of our algorithm is also rigorously derived. Simulation results show that this algorithm can achieve user comfort and reduce energy cost effectively.

关键词： Costs Uncertainty Simulation Heuristic algorithms Buildings Optimization methods Energy management

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CPL-CLIP: Compound Prompt Learning for Flexible-Modal Face Anti-Spoofing

CPL-CLIP: Compound Prompt Learning for Flexible-Modal Face A...

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IEEE International Joint Conference on Biometrics (IJCB)

作者： Ying Zhang Xiangyu Zhu Ajian Liu Xun Lin Jun Wan Jing Zhang Zhen Lei State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences School of Computer Science and Engineering Beihang University School of Computer Science and Engineering Macau University of Science and Technology Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation Chinese Academy of Sciences

ISBN: (数字)9798350364132

ISBN: (纸本)9798350364149

Face anti-spoofing (FAS) is pivotal in safeguarding the integrity of face recognition systems. Flexible-modal FAS utilizes multi-modal data and trains a unified model adaptable to any single-modal testing scenario. This innovation addresses the shortcomings of conventional multi-modal FAS approaches, which typically demand separate model training and deployment for each modality. However, existing flexible-modal FAS approaches activate specific network branches based on the modality of the tested sample. This not only increases the model’s parameters but also necessitates the provision of the image’s modality for testing, thereby constraining deployment flexibility. To address the issue, we present Compound Prompt Learning CLIP (CPL-CLIP), a novel method for flexible-modal FAS. This approach capitalizes on a learned textual prompt that is nearly independent of modality, thus bolstering class-based classification across arbitrary modalities. Specifically, our CPL-CLIP introduces a Dual-Branch Prompt (DBP), consisting of class and modal prompts that describe and guide classification, where each prompt is composed of learnable vectors and fixed templates. To further render the class prompt as modality-agnostic as possible, a Cosine Similarity Loss (CSL) is proposed to facilitate the maximal separation of the class prompt from the modality prompt. With only the class prompt utilized during testing, CPL-CLIP enables deployment in diverse modal testing scenarios without the necessity of the test image’s modality to be known. Extensive experiments demonstrate CPL-CLIP’s superiority over existing methods on several flexible-modal FAS benchmarks.

关键词： Training Adaptation models Technological innovation Accuracy Face recognition Benchmark testing Vectors Robustness Data models Compounds

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Automated Electromagnetic Manipulation of Micron-Scale Rotors on Unstructured Surfaces in Low Reynolds Numbers

Automated Electromagnetic Manipulation of Micron-Scale Rotor...

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International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Shihao Zhong Kailun Bai Yaozhen Hou Hen-Wei Huang Qing Shi Qiang Huang Huaping Wang Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China Science and Technology on Space Physics Laboratory Beijing China Laboratory for Translational Engineering Harvard Medical School Cambridge MA USA Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Ministry of Education Beijing China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

The utilization of magnetic microrotors in low Reynolds number liquid environments holds great promise for a wide range of biomedical applications, owing to their ability to maneuver with flexibility. However, during the movement of the microrotors on solid unstructured surfaces, the interaction with neighboring walls has the potential to generate unpredictable disruptions in its motion. This study proposes an automated electromagnetic manipulation method for guiding micron-scale surface rotors along planar paths at low Reynolds numbers. To this end, we designed a magnetic field drive system using multistage electromagnets, and a double-helix rotor with micrometer-scale dimensions. Additionally, we developed a kinematic model for the microrotor that closely resembles that of wheeled mobile robots and employed a sliding mode motion controller to ensure high-precision path following. Results obtained from simulation and experimentation confirm the efficacy of our proposed method, demonstrating precise following of planar paths.

关键词： Visualization Mechatronics Rotors Kinematics Solids Electromagnets Magnetic fields Mobile robots Micromagnetics Electromagnetics

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Trajectory Planning Towards Water-Air Trans-Media Motion for Robotic Dolphin

Trajectory Planning Towards Water-Air Trans-Media Motion for...

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Chinese Automation Congress (CAC)

作者： Yan Xiong Pengfei Zhang Di Chen Junzhi Yu Department of Advanced Manufacturing and Robotics State Key Laboratory for Turbulence and Complex Systems College of Engineering Peking University Beijing China Shandong Nuclear Power Company LTD. Yantai China School of Intelligence Science and Technology University of Science and Technology Beijing Beijing China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Water-air trans-media navigators have multi-media motion modes, breaking through the limitation that traditional robots can only operate in a single medium. Autonomous navigation is an indispensable component of the process of transmedia motion. Most of the current work has only completed the development and testing of prototypes, and the problem of task-oriented motion planning and control needs to be solved. In this paper, a safe and efficient hierarchical approach is proposed. First, a novel rapidly exploring random tree-based algorithm is proposed to search for a suitable path. Then, by fixing bound waypoints, the time-optimization trajectory is planned. Finally, the trajectory tracker is designed based on nonlinear model predictive control (NMPC). Simulation experiments numerically validate the proposed method, offering some new insights for further trans-media motions.

关键词： Tracking Trajectory planning Navigation Prototypes Prediction algorithms Trajectory Planning Testing Predictive control Dolphins

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Adaptive Planar Foot with Compliant Ankle Joint and Multi-modal Sensing for Quadruped Robots

Adaptive Planar Foot with Compliant Ankle Joint and Multi-mo...

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IEEE International Conference on robotics and Biomimetics

作者： Guowei Shi Chen Yao Wenhui Wang Zheng Zhu Zhenzhong Jia Department of Mechanical and Energy Engineering Southern University of Science and Technology (SUSTech) Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics Shenzhen China

ISBN: (纸本)9781665481106

An adaptive sensorized robot foot that can adapt to uneven and rough terrains and have contact state sensing capability is vital for legged locomotion in exploration missions. Inspired by quadruped animals, we present an adaptive planar foot with large contact area to reduce sinkage, two degrees of freedom (2-DOF) compliant ankle joint for better terrain adaptation, in-foot multi-modal sensing capability. We propose customized ankle design with encoders instead of IMU for ankle joint angle measurement, in order to mitigate the noise injected by large impact forces. The foot also provides an accurate estimated force according to foot-shank relative orientation and the 6-axis force/torque sensor data. We develop a control algorithm for a quadruped robot equipped with our proposed robot feet and test its performance through simulation. Real-world experiments including foot orientation estimation, swing sensitivity, and force perception verify that our robot foot is suitable for dynamic quadruped locomotion.

关键词： Legged locomotion Sensitivity Force measurement Heuristic algorithms Force Robot sensing systems Sensors

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End-to-end Semantic Segmentation Network for Low-Light Scenes

End-to-end Semantic Segmentation Network for Low-Light Scene...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Hongmin Mu Gang Zhang MengChu Zhou Zhengcai Cao College of Information Science and Technology Beijing University of Chemical Technology Beijing China Department of Macao Institute of Systems Engineering Macau University of Science and Technology Macao China Helen and John C. Hartmann Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In the fields of robotic perception and computer vision, achieving accurate semantic segmentation of low-light or nighttime scenes is challenging. This is primarily due to the limited visibility of objects and the reduced texture and color contrasts among them. To address the issue of limited visibility, we propose a hierarchical gated convolution unit, which simultaneously expands the receptive field and restores edge texture. To address the issue of reduced texture among objects, we propose a dual closed-loop bipartite matching algorithm to establish a total loss function consisting of the unsupervised illumination enhancement loss and supervised intersection-over-union loss, thus enabling the joint minimization of both losses via the Hungarian algorithm. We thus achieve end-to-end training for a semantic segmentation network especially suitable for handling low-light scenes. Experimental results demonstrate that the proposed network surpasses existing methods on the Cityscapes dataset and notably outperforms state-of-the-art methods on both Dark Zurich and Nighttime Driving datasets.

关键词： Training Computer vision Accuracy Convolution Semantic segmentation Lighting Logic gates

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