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Nonsmooth Dynamic Modeling of a Humanoid Robot with Parallel Mechanisms 16th

Nonsmooth Dynamic Modeling of a Humanoid Robot with Paral...

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

作者： Xiong, Jiaming Liang, Dingkun Wang, Xin Huang, Yongshan Xie, Anhuan Gu, Jason Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Lab Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Department of Electrical and Computer Engineering Dalhousie University HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9789819964918

This paper establishes a nonsmooth dynamic model for a humanoid robot with parallel mechanisms. Firstly, the constraint equations of the parallel mechanism are derived through kinematic analysis. By combining the links involved in closed-loop constraints into aggregate nodes, the topology of the robot can be equivalent to a tree structure. Equivalent physical quantities for the aggregate nodes are defined to unify their treatment with individual nodes during dynamic modeling. Subsequently, the contact and impact dynamics of the robot are modeled using constraint-based methods, with a frictional multiple impacts model employed for impacts. Due to the high degree of freedom of the robot, recursive methods are adopted to calculate the corresponding dynamic matrices. Finally, numerical examples are provided to illustrate the dynamic model of the robot. A comparison with the compliance-based methods of Simscape Multibody demonstrates that our dynamic model can reflect more realistic physical processes, providing a more accurate simulation environment for the motion control of the robot. The simulation of standing balance control is also performed based on our dynamic model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Anthropomorphic robots

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A Joint Tracking System: Robot is Online to Access Surveillance Views

A Joint Tracking System: Robot is Online to Access Surveilla...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Lin, Zheyuan Ji, Shanshan Wang, Wen Qin, Mengjie Yang, Rong Wan, Minhong Gu, Jason Li, Te Zhang, Chunlong Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Research Center for Intelligent Robotics Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9798350325706

The application of robots in social life, equipped with sensors and actuators and embedded with AI, assists people in all aspects. However, the first perspective of the robot horizon is heavily constrained, which weakens its performance. A joint tracking system is designed and built to deal with this, by integrating a surveillance system with the robot visual, providing a third perspective. This system takes one horizontal view and two top views from various directions as inputs and matches a person among the frames and in time sequence. In order to deal with the identity match with a huge visual feature gap, a special dataset is collected, simultaneously labeling identities from a mobile robot perspective and multiple indoor static surveillance monitors. The experiment shows that such match is a task worth exploring that can be better handled by training on our dataset than existing open source Re-identification (Re-id) datasets. Moreover, in the real scenario, this system improves the performance on issues like in and out of the robot's field of vision and heavy occlusion by people or objects. © 2023 IEEE.

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A Comprehensive SLAM Dataset for Indoor Exhibition Environments: Data Collection, Processing, and Comparative Evaluation

A Comprehensive SLAM Dataset for Indoor Exhibition Environme...

引用

2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Yuan, Songyu Zhang, Jing Pan, Chen Zhang, Chunlong Wan, Minhong Zheng, Tao Gu, Jason Zhejiang Lab Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9798350325706

The field of Simultaneous Localization and Mapping(SLAM) has witnessed significant advancements in recent years. However, due to the difficulty of data obtains and ground-truth makes, there is a lack of real indoor scenarios datasets, especially the scenarios with less-texture, repeat-texture, extreme light condition, causing the slowly progress in indoor SLAM. In this paper, we present a dataset captured in a real indoor exhibition hall with diverse type of sensor data. Which contributes to diverse school of SLAM that using different sensors. We provide ground-truth 6DoF pose captured by motion capture devices, RGB-D data captured by a RealSense D455 camera. Laser-data captured by Ouster. And a high-resolution color point cloud captured by a laser scanner. This dataset offers three distinct sources of ground truth from real-world scenarios. It combines motion capture, ICP based laser localization, and visual localization methods to provide comprehensive and accurate reference data. This dataset is designed for evaluating positioning methods that employ various types of sensors, moving beyond a singular matrix-based evaluation approach. Besides, We show results of several state-of-the-art SLAM method in our datasets, illustrates the utility of our dataset and served as a reference for other researcher. We converge LiDAR-based SLAM with ground truth, made a good closure. An ensemble approach-based Visual SLAM, achieves results of odometry errors of 4% and loop closure position errors of 40 cm. Additionally, visual localization demonstrated an absolute position error of 21 cm using high-resolution point clouds. We highlight the potentials of our indoor datasets in LiDAR SLAM, RGB-D SLAM, and visual localization and combines method. The datasets are available at https://***/IMBAfarmer09/ExhibitionDataset © 2023 IEEE.

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Enhancing Human-Robot Cohesion through HAT Methods: A Crowd-Avoidance Model for Safety Aware Navigation 4

Enhancing Human-Robot Cohesion through HAT Methods: A Crowd-...

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4th IEEE International Conference on Human-Machine systems, ICHMS 2024

作者： Sellers, Timothy Lei, Tingjun Luo, Chaomin Liu, Lantao Carruth, Daniel W. Mississippi State University Department Of Electrical And Computer Engineering Mississippi StateMS39762 United States Indiana University Department Of Intelligent Systems Engineering BloomingtonIN47408 United States Mississippi State University Center For Advanced Vehicular Systems MS39759 United States

ISBN: (纸本)9798350315790

In the world of autonomous robots, achieving complete accuracy remains a challenge, underscoring the importance of human intervention, especially regarding safety. In Human-Autonomy Teaming (HAT), ensuring safe and effective human-robot cooperation in dynamic indoor settings is crucial. This paper introduces a framework designed to address this accuracy shortfall, enhancing safety and robotic interactions in these environments. Central to our approach is a hybrid graph system that melds the Generalized Voronoi Diagram (GVD) with spatio-temporal graphs, harmonizing human feedback, environmental elements, and key waypoints. An essential component is the improved Node Selection Algorithm (iNSA), which utilizes the revised Grey Wolf Optimization (rGWO) for enhanced adaptability and performance. Human insights are instrumental, from supplying initial environmental data and determining key waypoints to stepping in during unexpected challenges or dynamic changes in the environment. Extensive simulation and comparison tests confirm the reliability and effectiveness of our model, highlighting its unique advantages in the realm of HAT. © 2024 IEEE.

关键词： Motion planning

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Quantum Calculus-Based Two-Dimensional Least Mean Square Algorithm 58

Quantum Calculus-Based Two-Dimensional Least Mean Square Alg...

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58th Asilomar Conference on Signals, systems and computers, ACSSC 2024

作者： Moinuddin, Muhammad Zerguine, Azzedine Al-Saggaf, Ubaid M. Arif, Muhammad King Abdulaziz University Electrical and Computer Engineering Department The Centre of Excellence in Intelligent Engineering Systems Jeddah Saudi Arabia Kfupm Electrical Engineering Department The Interdisciplinary Research Center for Communication Systems and Sensing Dhahran31261 Saudi Arabia Institute of Networked and Embedded Systems University of Klagenfurt Klagenfurt Austria The Ubiquitous Sensing Systems Lab University of Klagenfurt-Silicon Austria Labs Klagenfurt Austria

ISBN: (纸本)9798350354058

Recent work of the one-dimensional q-LMS algorithm give insight that the Quantum Calculus based gradient called the q-gradient is capable of improving the convergence behavior in contrast to the standard LMS algorithm. The reason for this is the fact that the q-derivative takes larger steps in minimizing a cost function as it evaluates the secant in contrast to the tangent of the cost function. Motivated by this, we propose a two-dimensional version of the q-LMS algorithm. More precisely, we employ Quantum Calculus based q-gradient in steepest descent optimization of mean-square-error (MSE) cost function in 2D adaptive filtering scenario to obtain two-dimensional q-LMS (2D q-LMS) algorithm. A thorough analytical investigation of the proposed 2D q-LMS algorithm in both mean and mean-square sense is provided. Both the transient and steady-state convergence behaviours are examined. Consequently, excess MSE (EMSE) learning curve and its steady-state expression are evaluated in closed form. Simulation results are presented for the application of noise cancelation in images to show the superiority of the proposed 2D q-LMS algorithm. © 2024 IEEE.

关键词： Cost functions

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Lightweight Design and Property Analysis of Humanoid Robot Thigh Integrated Structure with Appearance 16th

Lightweight Design and Property Analysis of Humanoid Robot T...

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

作者： Nie, Daming Gu, Jason Zhang, Yu Jiang, Hongjian Research Center for Intelligent Robotics Zhejiang Lab Hangzhou310058 China Department of Electrical and Computer Engineering Dalhousie University HalifaxB3M 1A2 Canada

ISBN: (纸本)9789819964949

The lightweight and high stiffness leg structure of humanoid robots can effectively reduce rotational inertia and energy consumption, improving the robot's ability to quickly switch motion states. Based on the lightweight requirements of robots, this article proposes an innovative design method for humanoid robot legs based on the "structure-appearance" integration of light-alloy additive manufacturing technology. The load-bearing part of the leg structure is designed as a "shell + density-variable lattice" configuration, and the appearance part is set as a thin shell with equal thickness. The load-bearing part and the appearance one are combined together, resulting in a 20% weight reduction compared to traditional legs. The leg structure sample was processed using metal additive manufacturing method, and tested by a set of personalized fixture. When applying 200 Nm loading under pure torsion conditions, the local strain did not exceed 0.0175%, indicating that it meets the usage requirements. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Anthropomorphic robots

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Onboard Perception-Assisted High Fidelity Simulation Framework for Autonomous Planetary Soft-Landing

Onboard Perception-Assisted High Fidelity Simulation Framewo...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Alibekov, Ulugbek Banerjee, Avijit Satpute, Sumeet Gajanan Nikolakopoulos, George ERASMUS MUNDUS JOINT MASTER in Intelligent Field Robotic Systems Faculty of Informatics Eötvös Loránd University Budapest Hungary Robotics and AI research group Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This article presents an onboard perception-assisted high-fidelity simulation framework for autonomous planetary soft-landing, enabling visual information processing tightly integrated with advanced onboard guidance system in a realistic simulation environments. Utilizing the open source Unity game engine, a physics-based simulation toolbox integrated with the Robotic Operating System (ROS2), we effectively emulate the motion of spacecraft approaching planetary terrain. The simulation environment features a realistic 3D terrain model and a lander spacecraft equipped with onboard camera to effectively capture detailed local terrain images. The simulation engine accurately captures the spacecraft’s 6-degrees of freedom motion, seamlessly integrating space craft orientation with the associated camera feed while incorporating various illumination conditions using a light source representing the Sun. To demonstrate the efficacy of the framework, we implement a recently developed attitude-constrained minimum jerk guidance algorithm to emulate spacecraft motion. Concurrently, the visual feed from the onboard RGB camera is processed through a gradient extraction-based perception system, providing the visual odometer. This system identifies provably safe landing sites, effectively avoiding potential risks of landing on uneven terrain. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Planetary landers

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Design and Development of a Small UGV for Object Retrieval in Domestic Environments

Design and Development of a Small UGV for Object Retrieval i...

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2025 IEEE SoutheastCon, SoutheastCon 2025

作者： Jogeshwar, Bhaavin Kishore Bohannon, Joshua Sevil, Hakki Erhan Department of Intelligent Systems and Robotics PensacolaFL32514 United States Department of Electrical and Computer Engineering PensacolaFL32514 United States

ISBN: (纸本)9798331504847

The objective of this project is to develop an unmanned ground vehicle (UGV) prototype capable of retrieving small objects in domestic environments. As the robotics field continues to advance, the demand for autonomous systems that enhance daily life is rapidly increasing. Autonomous systems have the potential to improve efficiency by performing routine tasks, thereby reducing human effort and promoting convenience in household settings. This study explores the development of a small UGV designed to identify, navigate toward, and retrieve small objects while autonomously avoiding obstacles such as walls and furniture in domestic environments. The system utilizes neural networks for real-time object detection. The UGV design consists of an object retrieval mechanism suitable for handling items typically left scattered in domestic environments. The proof-of-concept results show the potential of designed UGV domestic, and could potentially enable further advancements in autonomous household assistance technologies. © 2025 IEEE.

关键词： Object detection

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Review of Inference Time Prediction Approaches of DNN: Emphasis on Service robots with cloud-edge-device architecture

Review of Inference Time Prediction Approaches of DNN: Empha...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Xiang, Tian Meng, Qiwei Zhang, Ji Zhang, Beibei Song, Wei Xie, Anhuan Gu, Jason Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Research Center for Intelligent Robotics Hangzhou311100 China The Chinese University of Hong Kong T Stone Robotics Institute Department of Mechanical and Automation Engineering Hong Kong Research Institute of Intelligent Computing Zhejiang Laboratory Research Center for Intelligent Computing Software Hangzhou311100 China Dalhousie University Electrical and Computer Engineering Halifax Canada

ISBN: (纸本)9798350325706

In recent years, the global robot market has witnessed substantial growth, particularly in the domain of service robots. Despite their expanding presence, service robots encounter limitations when operating autonomously in unstructured environments, primarily due to their constrained computational capacities. As a solution, the fusion of cloud and edge computing resources becomes imperative to expedite task inference and enhance scenario perception capabilities. The integration of cloud-edge-device models holds significant promise in bolstering the operational efficiency of robots. This entails the dynamic partitioning of intricate robotic tasks, executed collaboratively across cloud, edge, and device resources. In this landscape, deep neural network (DNN) models play a pivotal role in facilitating a wide array of robotic tasks. The inference time for each layer of a DNN model in actual deployment, emerges as a critical determinant in the model's partitioning strategy. It also serves as an important metric influencing the model's suitability for a specific hardware platform. This article presents an overview of recent advancements in predicting inference and training time of DNN models, summarizes the related methods, and finally discusses the challenges in this field and the research that can be studied in the future. © 2023 IEEE.

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Whole Body Balance Control for Bipedal Robots Based on Virtual Model Control 16th

Whole Body Balance Control for Bipedal Robots Based on Virtu...

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

作者： Gao, Chengzhi Xie, Ye Zhu, Yiting Liang, Dingkun Kong, Lingyu Wang, Xin Xie, Anhuan Gu, Jianjun Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Zhejiang University Zhejiang Hangzhou311100 China Department of Electrical and Computer Engineering Dalhousie University HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9789819964918

Due to the lack of accurate stability theoretical basis, the dynamic balance control of bipedal robots is a challenging topic. In this paper, we propose a controller that combines virtual model control and whole body control. In our framework, the whole system is simplified into a spring inverted pendulum model. Decoupling control is carried out for this model, and a virtual model is introduced to establish the relationship between the joint torque of the support leg and the state of the center of mass. The distribution of reaction force is obtained through decoupling closed-loop control. The whole body control part first uses multi task whole body control to determine the kinematics information, and then solves the joint feedforward torque through dynamical model, thus obtaining the desired force position hybrid control. Proposed algorithm improved the problem of incomplete decoupling between states and increased the stiffness of the support leg. The newly designed control framework was tested in Simscape dynamic simulation and verified the anti-interference ability and fast walking ability of Whole Body Balance Control for bipedal robots based on Virtual Model Control. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Inverted pendulum

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