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IEEE International Conference on Mechatronics and Automation

作者： Kitti Suwanratchatamanee Hideyuki Sawada Shuji Hashimoto Department of Engineering Robotics Research and Development Center Golden Robot Co. Ltd Banchang Rayong Thailand Department of Applied Physics Graduate School of Advanced Science and Engineering Faculty of Science and Engineering Waseda University Tokyo Japan Waseda University Tokyo Japan

ISBN: (数字)9798350388077

ISBN: (纸本)9798350388084

This paper presents the handling collaborative robot (Cobot) system for grasping the medical cotton cloth porous that were arranged in matching layers from one point to another point by arranged them in matching layers again. The important is to not grasping all layer objects together in once, but must be separately for each layer by layer. As the object to be grasped is the cotton cloth porous to be used in the medical purpose, thus the cleanness and must not leave any wrinkles or marks when handled the fabric are necessity required before packaging process. The proposed handling collaborative robot system contains the novel tooling called "Bernoulli Gripper" can achieve this handling task perfectly with 100% success rate of experiments. This gripper was developed to lifts the porous fabric sheet up in such a way that it does not grasping touch by utilizing four points Bernoulli principle elements like no other grippers that need to do the touching forces and always leave wrinkles or marks when handled the fabric, such as pneumatic suction cup, robot hand and fingers. Moreover, the research objective is to produce the handling robot system that can achieve the non-contact grasping and do collaborative tasks together with human in the same environment. As the result, our proposed system can be used for working together with human worker as the collaborative partner to arrange these medical cotton cloth porous products with about 6.5 seconds per sheet in the real production line suitably.

关键词： Mechatronics Grasping Collaborative robots Production Pneumatic systems Packaging Fabrics

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Comparison and Improvement of Local Planners on ROS for Narrow Passages 4

Comparison and Improvement of Local Planners on ROS for Narr...

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4th International Conference on High Performance Big Data and Intelligent Systems, HDIS 2022

作者： Yuan, Huajun Li, Hanlin Zhang, Yuhan Du, Shuang Yu, Limin Wang, Xinheng School of Advanced Technology Xi'An Jiaotong-Liverpool University Suzhou215123 China Suzhou Inteleizhen Intelligent Technology Co. Ltd Department of Research and Development Suzhou215123 China Xi'An Jiaotong-Liverpool University Department of Communications and Networking Suzhou215123 China Xi'An Jiaotong-Liverpool University Department of Mechatronics and Robotics Suzhou215123 China

ISBN: (数字)9781665491440

ISBN: (纸本)9781665491440

Path planning is challenging in various extreme and complex environments due to the explosive growth of autonomous mobile robots. The widely used Dynamic Window Approach (DWA) and Time Elastic Band (TEB) local planners are integrated into Robot Operating System (ROS). A great quantity of their parameters has a significant impact on the actual performance of planning. Aiming at the scenario of robots passing through narrow passages, this work compared and optimized the typical DWA and TEB. The results of simulations showed that the improved DWA and TEB local path planners both have better performance with gentler fluctuations of velocity and smoother paths of travel in continuous narrow passages. In addition, the number of collisions was reduced to zero and the time consumption of completing navigation was decreased by an average of 15% and 7%, respectively. Moreover, the general strategies and suggestions for adjusting related parameters of DWA and TEB through narrow passages were given in this paper. Finally, the adjusted TEB local planner was applied to the customized robot in a real similar environment, and it accomplished the navigation stably with a smooth path. The results of real experiments proved the validity and reliability of our work further. © 2022 IEEE.

关键词： Robot Operating System

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

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

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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

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CAIS: Culvert Autonomous Inspection Robotic System

CAIS: Culvert Autonomous Inspection Robotic System

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

作者： Chuong Phuoc Le Pratik Walunj An Duy Nguyen Yongyi Zhou Binh Nguyen Thang Nguyen Anton Netchaev Hung Manh La Department of Computer Science and Engineering Advanced Robotics and Automation (ARA) Lab University of Nevada Reno NV USA Department of Engineering Texas A&M University–Corpus Christi Corpus Christi TX USA USACE Engineer Research and Development Center (ERDC) Information Technology Lab Vicksburg MS USA

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Culverts, essential components of drainage systems, require regular inspection to ensure optimal functionality. However, culvert inspections pose numerous challenges, including accessibility, manpower, defect localization, and reliance on superficial assessments. To address these challenges, we propose a novel Culvert Autonomous Inspection Robotic System (CAIS) equipped with advanced sensing and evaluation capabilities. Our solution integrates an RGBD camera, deep learning, lighting systems, and non-destructive evaluation (NDE) techniques to enable accurate and comprehensive condition assessments. We present a pioneering Partially Observable Markov Decision Process (POMDP) framework to resolve uncertainty in autonomous inspections, especially in confined and unstructured environments like culverts or tunnels. The framework outputs detailed 3D maps highlighting visual defects and NDE condition assessments, demonstrating consistent and reliable performance in both indoor and outdoor scenarios. Additionally, we provide an open-source implementation of our framework on GitHub, contributing to the advancement of autonomous inspection technology and fostering collaboration within the research community. Source codes are available * .

关键词： Visualization Uncertainty Three-dimensional displays Source coding Markov decision processes Robot vision systems Inspection Sensors Reliability Software development management

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Pseudo Depth Maps for RGB-D SLAM 4

Pseudo Depth Maps for RGB-D SLAM

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4th International Conference on High Performance Big Data and Intelligent Systems, HDIS 2022

作者： Zhang, Yue Wu, Taoyu Zhao, Haocheng Du, Shuang Yu, Limin Wang, Xinheng Xi'An Jiaotong-Liverpool University School of Advanced Technology Suzhou215123 China Artificial Intelligence Department IDPT JITRI Wuxi214000 China Suzhou Inteleizhen Intelligent Technology Co. Ltd Research and Development Department Suzhou215123 China Xi'An Jiaotong-Liverpool University Department of Communications and Networking Suzhou215123 China Xi'An Jiaotong-Liverpool University Department of Mechatronics and Robotics Suzhou215123 China

ISBN: (数字)9781665491440

ISBN: (纸本)9781665491440

In visual SLAM, RGB-D cameras can actively obtain pixel depth information but are expensive and unsuitable for outdoor use. In contrast, monocular depth estimation is relatively inexpensive and more readily available. There have been some systems that fuse monocular depth estimation with SLAM algorithms, but no method that can directly generate depth maps has been tested with experiments. We propose that using monocular depth estimation results can generate 16-bit pseudo depth maps, which can be combined with monocular images as pseudo RGB-D. The relevant camera parameters can be configured according to the general RGB-D camera SLAM requirements. Experiments with Monodepth2 and ORB-SLAM3 on the KITTI dataset demonstrate that pseudo RGB-D can achieve as satisfactory results in SLAM as in stereo computation. The research paves the way for researchers can quickly examine monocular depth estimation results in more SLAM frameworks, reducing the cost of testing new depth monocular estimation frameworks. © 2022 IEEE.

关键词： Cameras

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An Adaptive Overlap-based ICP Algorithm for Multi-LiDAR Calibration in Low-overlap Situations 4

An Adaptive Overlap-based ICP Algorithm for Multi-LiDAR Cali...

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4th International Conference on High Performance Big Data and Intelligent Systems, HDIS 2022

作者： Li, Hanlin Yuan, Huajun Zhao, Haocheng Zou, Bin Yu, Limin Wang, Xinheng School of Advanced Technology Xi'An Jiaotong-Liverpool University Suzhou215123 China Department of Artificial Intelligence IDPT JITRI Wuxi214000 China Department of Research and Development Suzhou Inteleizhen Intelligent Technology Co. Ltd Suzhou215123 China Department of Communications and Networking Xi'An Jiaotong-Liverpool University Suzhou215123 China Department of Mechatronics and Robotics Xi'An Jiaotong-Liverpool University Suzhou215123 China

ISBN: (数字)9781665491440

ISBN: (纸本)9781665491440

LiDAR has been widely used as a core sensor in autonomous driving and mobile robotics. Due to the high price of spinning LiDARs, the industry always uses a combination of multiple calibrated solid-state LiDARs. However, there is usually only a small overlap FoV between LiDARs on account of their mounting positions. In such a low-overlap situation, conventional calibration methods always bring catastrophic results. To solve this problem, this paper proposed an adaptive overlap-based ICP algorithm, which can calibrate both 2D and 3D LiDARs. The algorithm adaptively extracts the overlapping point clouds by identifying the correct matching results and constructs an optimized ICP alignment. By controlling the radius range of the point cloud search, our method allows for quick extrinsic calibration of two LiDARs with low-overlap FoV. Experiments show that our algorithm achieves a more robust and accurate low-overlap registration than other methods, and also has speed advantages in general situations. © 2022 IEEE.

关键词： Calibration

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Fractional Order Integral Controller Design Based on a Bodes Ideal Transfer Function: Application to the Control of a Single Tank Process 4th

Fractional Order Integral Controller Design Based on a Bodes...

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4th International Conference on Electrical Engineering and Control Applications, ICEECA 2019

作者： Boussalem, Chahira Mansouri, Rachid Bettayeb, Maamar Hamerlain, Mustapha Automatic Department University of Tizi-Ouzou Tizi-Ouzou Algeria Productive and Robotics Division Center for Development of Advanced Technologies Algiers Algeria Center of Excellence in Intelligent Engineering Systems King Abdulaziz University Jeddah Saudi Arabia Electrical Engineering Department University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9789811564024

The paper deals with the water level control of a single tank process associated feedback linearization (FL) with a novel fractional order integral controller (FOIC) which is based on the Bodes ideal transfer function. The first controller is used to cancel the nonlinearities of the single tank process and the latter used to solve the tracking problem. The new controller is implemented on a single tank process and the results are compared with a Linear Quadratic Regulator (LQR). © 2021, Springer Nature Singapore Pte Ltd.

关键词： Transfer functions

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development of ROV Simulator based on Real Oceanographic Data

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IFAC-PapersOnLine 2023年第2期56卷 11590-11595页

作者： Ryusei KAMEWARI Yusuke FUJISHIMA Kuniaki KAWABATA Kenta SUZUKI Norimitsu SAKAGAMI Fumiaki TAKEMURA Satoru TAKAHASHI Graduate School of Science for Creative Emergence Kagawa University 2217-20 Hayashi-Machi Takamatsu Kagawa 761-0396 Japan Area of Mechanical Systems Engineering Faculty of Engineering and Design Kagawa University Kagawa Japan Sector of Fukushima Research and Development Japan Atomic Energy Agency Fukushima Japan Mechanical Engineering and Robotics Course Faculty of Advanced Science and Technology Ryukoku University Shiga Japan Department of Mechanical Systems Engineering National Institute of Technology Okinawa College Okinawa Japan

In recent years, demand for efficient oceanographic research for the development of marine resources has been increasing on a global scale. In general, research and operation training on underwater robotics in the ocean is very costly, and the climate and conditions of the ocean may make it impossible to conduct experiments. In this paper, we introduce an ocean simulator using real oceanographic data that can avoid these issues. First, we treat Choreonoid which is an integrated software for robots applied by National Institute of advanced Industrial Science and Technology (AIST), as the basis of the simulator software. Furthermore, to demonstrate its feasibility in a more realistic ocean environment, we introduce the seabed data obtained from oceanographic research and a function to reproduce ocean currents on the simulator. In this paper, self-localization experiment is conducted to demonstrate the effectiveness of the simulator for oceanographic research.

关键词： underwater robot oceanographic research Ocean simulator self-localization estimation

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Transformer Based Tissue Classification in Robotic Needle Biopsy

arXiv

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arXiv 2024年

作者： Wang, Fanxin Cheng, Yikun Mukherjee, Sudipta S. Bhargava, Rohit Kesavadas, Thenkurussi Department of Mechatronics and Robotics Xi'an Jiaotong-Liverpool University 215123 China Department of Mechanical Science and Engineering University of Illinois Urbana-Champaign ChampaignIL61801 United States Beckman Institute for Advanced Science and Technology Departments of Bioengineering Electrical & Computer Engineering Mechanical Science & Engineering Chemical and Biomolecular Engineering University of Illinois Urbana-Champaign ChampaignIL61801 United States Beckman Institute for Advanced Science and Technology University of Illinois Urbana-Champaign ChampaignIL61801 United States Division of Research and Economic Development University at Albany State University of New York AlbanyNY12222 United States

Image-guided minimally invasive robotic surgery is commonly employed for tasks such as needle biopsies or localized therapies. However, the nonlinear deformation of various tissue types presents difficulties for surgeons in achieving precise needle tip placement, particularly when relying on low-fidelity biopsy imaging systems. In this paper, we introduce a method to classify needle biopsy interventions and identify tissue types based on a comprehensive needle-tissue contact model that incorporates both position and force parameters. We trained a transformer model using a comprehensive dataset collected from a formerly developed robotics platform, which consists of synthetic and porcine tissue from various locations (liver, kidney, heart, belly, hock) marked with interaction phases (pre-puncture, puncture, post-puncture, neutral). This model achieves a significant classification accuracy of 0.93. Our demonstrated method can assist surgeons in identifying transitions to different tissues, aiding surgeons with tissue awareness. © 2024, CC BY.

关键词： Biopsy

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Learning Intra-group Cooperation in Multi-agent Systems

Learning Intra-group Cooperation in Multi-agent Systems

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International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Weiwei Liu Shanqi Liu Jian Yang Yong Liu The Advanced Perception on Robotics and Intelligent Learning Lab College of Control Science and Enginneering Zhejiang University Hangzhou China China Research and Development Academy of Machinery Equipment Beijing China Huzhou Institute of Zhejiang University Huzhou China

ISBN: (纸本)9781665431545

Reinforcement learning is one of the algorithms used in multi-agent systems to promote agent cooperation. However, most current multi-agent reinforcement learning algorithms improve the communication capabilities of agents for cooperation, but the overall communication is costly and even harmful due to bandwidth limitations. In addition, de-centralized execution cannot generate joint actions, which is not conducive to cooperation. Therefore, we proposed the Hierarchical Group Cooperation Network (HGCN). advanced strategy, Group Network (GroNet), learns to group all agents based on their state rather than their location. The Low-level strategy, Group Cooperation Network (GCoNet), is a method of centralized training and centralized execution within a group, which effectively promotes agent collaboration. Finally, we validated our method in various experiments.

关键词： Training Mechatronics Machine vision Collaboration Reinforcement learning Bandwidth Task analysis

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