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A Multi-model Fusion of LiDAR-inertial Odometry via Localization and Mapping

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A Multi-model Fusion of LiDAR-inertial Odometry via Localiza...

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

作者： An Duy Nguyen Chuong Phuoc Le Pratik Walunj Anton Netchaev Thanh Nho Do Hung Manh La Department of Computer Science and Engineering Advanced Robotics and Automation (ARA) Lab University of Nevada Reno NV USA USACE Engineer Research and Development Center (ERDC) Information Technology Lab Vicksburg MS USA Graduate School of Biomedical Engineering UNSW Sydney Kensington Campus NSW Australia

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This work presents a comprehensive LiDAR-inertial odometry framework featuring robust smoothing and mapping capabilities, effectively correcting LiDAR feature point skewness using an inertial measurement unit (IMU). While the Extended Kalman Filter (EKF) is a common choice for nonlinear motion estimation, its complexity grows when handling maneuvering targets. To overcome this challenge, a new framework that incorporates the Iterated Interactive Multiple Models of Kalman Filter (IMMKF) is given, providing a solution for reliable navigation in dynamic motion and noisy conditions. To ensure map consistency, an ikd-tree that facilitates continuous updates and adaptive rebalance is employed, preserving the map’s integrity. To guarantee the robustness of our approach, it undergoes extensive testing across diverse scales of indoor and outdoor environments. This testing scenario simulates absolute GPS denial. In terms of estimated motion, the new algorithm demonstrates superior accuracy compared to existing approaches. The implementation is openly accessible on GitHub 4 for further exploration.

关键词： Location awareness Technological innovation Laser radar Accuracy Smoothing methods Computational modeling Feature extraction Odometry Kalman filters Testing

Multi-robot Task Allocation for Nursing Home Based on Improved Particle Swarm Algorithm 2

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Multi-robot Task Allocation for Nursing Home Based on Improv...

2021 2nd International Conference on Machine Learning and Computer Application, ICMLCA 2021

作者： Sun, Jin Zhao, Donghui Ren, Zhechen Yang, Zihao Liu, Houde Yang, Junyou School of Electrical Engineering Shenyang University of Technology Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China The Center for Artificial Intelligence and Robotics Tsinghua University Beijing China

ISBN: (纸本)9783800757398

For multi-robot task allocation problem in a nursing home environment, this paper develops an optimisation model with the objectives of shortest task completion time, lowest system energy consumption and maximum number of tasks completed. An improved particle swarm algorithm is also proposed to solve the model efficiently. In the design of the algorithm, the concept of allocation radius is defined, and an encoding method is designed specifically for this problem, transforming the decision variables from discrete to continuous. The encoding method enables the continuous algorithm to solve discrete problems and shifts the processing of some constraints from the encoding layer to the decoding layer, which greatly improves the efficiency of the algorithm's solution. In addition, the improved algorithm incorporates updated formulations of the flame algorithm, genetic algorithm and particle swarm algorithm, which enhances the diversity of generating individuals and improves the exploration capability of the algorithm. Finally, the improved algorithm proposed in this paper is compared with other swarm intelligence algorithms. The experimental results show that the improved algorithm outperforms other algorithms in terms of solution energy consumption, time and system gain, and converges faster, indicating that the proposed algorithm plays a greater role in planning multi-robot task allocation schemes. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Genetic algorithms

Generalized Multi-kernel Maximum Correntropy Kalman Filter for Disturbance Estimation

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arXiv 2023年

作者： Li, Shilei Shi, Dawei Lou, Yunjiang Zou, Wulin Shi, Ling The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong The School of Automation Beijing Institute of Technology China The State Key Laboratory of Robotics and System School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen518055 China Xeno Dynamics Control Department Xeno Dynamics Co. Ltd Shenzhen518055 China

Disturbance observers have been attracting continuing research efforts and are widely used in many applications. Among them, the Kalman filter-based disturbance observer is an attractive one since it estimates both the state and the disturbance simultaneously, and is optimal for a linear system with Gaussian noises. Unfortunately, The noise in the disturbance channel typically exhibits a heavy-tailed distribution because the nominal disturbance dynamics usually do not align with the practical ones. To handle this issue, we propose a generalized multi-kernel maximum correntropy Kalman filter for disturbance estimation, which is less conservative by adopting different kernel bandwidths for different channels and exhibits excellent performance both with and without external disturbance. The convergence of the fixed point iteration and the complexity of the proposed algorithm are given. Simulations on a robotic manipulator reveal that the proposed algorithm is very efficient in disturbance estimation with moderate algorithm complexity. Copyright © 2023, The Authors. All rights reserved.

关键词： Kalman filters

Dynamic modeling and analysis for a differential modular robot joint with the friction model

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Dynamic modeling and analysis for a differential modular rob...

IEEE International Conference on robotics and Biomimetics

作者： Yukun Liu Ruiqing Luo Minghui He Liang Du Sheng Bao Jianjun Yuan Weiwei Wan Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai China Shanghai Robotics Institute Shanghai University Shanghai China Department of System Innovation Graduate School of Engineering Science Osaka University Toyonaka Osaka Japan

ISBN: (纸本)9781665481106

The study of friction has long been popular with scientists. Considering the coupling characteristic of multi-input-multi-output (MIMO) system, the coupling friction model was established, which was based on Coulomb-Viscous friction model for the differential modular robot joint (DMRJ) according to the law of conservation of energy. Then, we identified the coefficients of the friction model through the experiment. In order to verify the accuracy of the established friction model, we regarded the DMRJ as a 2-DoF linkage and built the inertial dynamic model based on Lie theory, whose inertial parameters were estimated by computer aided design (CAD). Besides, we chose the trajectory based on the Fourier series, which has good performance in anti-interference ability, as the verification trajectory. From the generated trajectories, we used a trajectory that is able to change as much as possible in speed, position and acceleration to estimate the accuracy of the model comprehensively. Finally, the result indicated the model had good accuracy.

关键词： Couplings Solid modeling Analytical models Design automation Friction Computational modeling Biological system modeling

Model-Free Large-Scale Cloth Spreading With Mobile Manipulation: Initial Feasibility Study

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arXiv 2023年

作者： Chu, Xiangyu Wang, Shengzhi Feng, Minjian Zheng, Jiaxi Zhao, Yuxuan Huang, Jing Samuel Au, K.W. Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong Multi-Scale Medical Robotics Center Hong Kong School of Engineering Westlake University China Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and Technology Hong Kong

Cloth manipulation is common in domestic and service tasks, and most studies use fixed-base manipulators to manipulate objects whose sizes are relatively small with respect to the manipulators' workspace, such as towels, shirts, and rags. In contrast, manipulation of large-scale cloth, such as bed making and tablecloth spreading, poses additional challenges of reachability and manipulation control. To address them, this paper presents a novel framework to spread large-scale cloth, with a single-arm mobile manipulator that can solve the reachability issue, for an initial feasibility study. On the manipulation control side, without modeling highly deformable cloth, a vision-based manipulation control scheme is applied and based on an online-update Jacobian matrix mapping from selected feature points to the end-effector motion. To coordinate the control of the manipulator and mobile platform, Behavior Trees (BTs) are used because of their modularity. Finally, experiments are conducted, including validation of the model-free manipulation control for cloth spreading in different conditions and the large-scale cloth spreading framework. The experimental results demonstrate the large-scale cloth spreading task feasibility with a single-arm mobile manipulator and the model-free deformation controller. Copyright © 2023, The Authors. All rights reserved.

关键词： Manipulators

Cooperative Aerial Robot Inspection Challenge: A Benchmark for Heterogeneous Multi-UAV Planning and Lessons Learned

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arXiv 2025年

作者： Cao, Muqing Nguyen, Thien-Minh Yuan, Shenghai Anastasiou, Andreas Zacharia, Angelos Papaioannou, Savvas Kolios, Panayiotis Panayiotou, Christos G. Polycarpou, Marios M. Xu, Xinhang Zhang, Mingjie Gao, Fei Zhou, Boyu Chen, Ben M. Xie, Lihua Robotics Institute Carnegie Mellon University United States School of Electrical and Electronic Engineering Nanyang Technological University Singapore KIOS Research Innovation Center of Excellence Department of Electrical and Computer Engineering University of Cyprus Cyprus School of Artificial Intelligence Sun Yat-sen University China Zhejiang University China Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong

We propose the Cooperative Aerial Robot Inspection Challenge (CARIC), a simulation-based benchmark for motion planning algorithms in heterogeneous multi-UAV systems. CARIC features UAV teams with complementary sensors, realistic constraints, and evaluation metrics prioritizing inspection quality and efficiency. It offers a ready-to-use perception-control software stack and diverse scenarios to support the development and evaluation of task allocation and motion planning algorithms. Competitions using CARIC were held at IEEE CDC 2023 and the IROS 2024 Workshop on Multi-Robot Perception and Navigation, attracting innovative solutions from research teams worldwide. This paper examines the top three teams from CDC 2023, analyzing their exploration, inspection, and task allocation strategies while drawing insights into their performance across scenarios. The results highlight the task’s complexity and suggest promising directions for future research in cooperative multi-UAV systems. © 2025, CC BY-NC-ND.

关键词： Motion planning

A Parameter Identification Method for Coupled Dynamics of Robotic Manipulator with Differential Modular Joints

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A Parameter Identification Method for Coupled Dynamics of Ro...

IEEE International Conference on robotics and Biomimetics

作者： Minghui He Ruiqing Luo Yukun Liu Liang Du Sheng Bao Jianjun Yuan Weiwei Wan Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai China Shanghai Robotics Institute Shanghai University Shanghai China Department of System Innovation Graduate School of Engineering Science Osaka University Toyonaka Osaka Japan

ISBN: (纸本)9781665481106

In the daily nursing care for people with disabilities, lifting is the most basic and common action. A robotic manipulator with differential modular joints (DMJ) is designed to accomplish this task. To better implement force-control applications of the robotic manipulator with DMJs, this paper proposes a coupled dynamics identification method based on the multi-input, multi-output (MIMO) feature. Considering the frictions of transmission parts and links, the dynamics of the DMJ is analyzed based on the transformation of energy, and then the parameter-linearized dynamic model of the robotic manipulator with n DMJs is proposed according to the mapping relationship between transmission part level and link level. The identification and verification experiments show that the presented method can obtain the accurate dynamic model parameters. This work lays a foundation for the force-control research of the robotic manipulator with DMJs in the future.

关键词： Analytical models Parameter estimation Friction Biomimetics Biological system modeling Dynamics Medical services

ROBUST: 221 Bugs in the Robot Operating System

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arXiv 2024年

作者： Timperley, Christopher S. van der Hoorn, Gijs Santos, André Deshpande, Harshavardhan Wąsowski, Andrzej School of Computer Science Carnegie Mellon University United States Department of Cognitive Robotics faculty of Mechanical Maritime and Materials Engineering Delft University of Technology Netherlands VORTEX CoLab Portugal Fraunhofer Institute for Manufacturing Engineering and Automation IPA Germany Department of Computer Science IT University of Copenhagen Denmark

As robotic systems such as autonomous cars and delivery drones assume greater roles and responsibilities within society, the likelihood and impact of catastrophic software failure within those systems is increased. To aid researchers in the development of new methods to measure and assure the safety and quality of robotics software, we systematically curated a dataset of 221 bugs across 7 popular and diverse software systems implemented via the Robot Operating System (ROS). We produce historically accurate recreations of each of the 221 defective software versions in the form of Docker images, and use a grounded theory approach to examine and categorize their corresponding faults, failures, and fixes. Finally, we reflect on the implications of our findings and outline future research directions for the community. © 2024, CC BY-NC-SA.

关键词： Robot Operating System

Miniature Reconfigurable Modular Soft Robots Using Liquid Crystal Elastomer Actuation

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Miniature Reconfigurable Modular Soft Robots Using Liquid Cr...

ASME/IFToMM International Conference on Reconfigurable Mechanisms and Robots, ReMAR

作者： Huayu Zhang Jiajun An Tianle Pan Upinder Kaur Zhijian Wang Xuchen Wang Qiguang He Xin Ma Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong SAR Multiscale Medical Robotics Centre Hong Kong SAR Department of Agricultural and Biological Engineering Purdue University USA Key Laboratory of Aerospace Advanced Materials and Performance Ministry of Education School of Materials Science and Engineering Beihang University China

ISBN: (数字)9798350395969

ISBN: (纸本)9798350395976

Soft robotics is rapidly evolving, fueled by advancements in controllable materials. Liquid crystal elastomers (LCEs) stand out with their exceptional actuation capabilities, ease of processing, and built-in programmability. However, current LCE robots struggle with limited dexterity and adaptability, hindering their real-world potential. We address this limitation by introducing a novel modular design approach that unlocks the full potential of LCEs. Our miniature, highly deformable soft robot utilizes reconfigurable LCE modules for bending and twisting, enabling enhanced manipulability through serial combinations. Demonstrating its dexterity, the modular robot performs intricate fingertip manipulation, allowing a miniature gripper to rotate a small object. This achievement highlights the reconfigurability and utility of our system, paving the way for more dexterous and versatile LCE-based robots.

关键词： Elastomers Soft robotics Bending Grippers