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3D Printed Differential Drive Robot with LiDAR and 3D Depth Camera

3D Printed Differential Drive Robot with LiDAR and 3D Depth ...

引用

IEEE International Conference on Control and robotics engineering (ICCRE)

作者： Ng Danny Wee-Kiat Kwan Ban-Hoe Chan Siow Cheng Choon-Hian Goh Netizen Robotics Selangor Malaysia Department of Mechatronics and BioMedical Engineering Universiti Tunku Abdul Rahman Kajang Malaysia

ISBN: (数字)9798350372694

ISBN: (纸本)9798350372700

This paper presents the design of a 3D printed mobile differential drive robot with LiDAR and 3D depth sensing. The robot is designed to be low cost and easy to build, making it suitable for educational and research purposes. All the main structures of the robot are 3D printed while the parts used in the robot are from off-the-shelf components. All the design files and source code used in this project is shared in the github repository. The robot is equipped with a LiDAR sensor for mapping and navigation, and a 3D depth sensing camera for object recognition. Robot Operating System (ROS) running on an Intel single board computer serves as the middleware for all robot control operations. The developed robot is able to run simultaneous localization and mapping (SLAM) and perform autonomous navigation. Design files and the software for the robot can be obtained from the github reposi-tory https://***/dannyngweekiat/3D-Printed-Differential-Drive-Bot.

关键词： Three-dimensional displays Laser radar Simultaneous localization and mapping Source coding Robot vision systems Robot sensing systems Cameras

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Reduced-Order Nominal Model Design and Validation For Task Space DOB-Based Motion Control of An Industrial Robot

Reduced-Order Nominal Model Design and Validation For Task S...

引用

IEEE/ASME (AIM) International Conference on Advanced Intelligent mechatronics

作者： Kangwagye Samuel Kevin Haninger Sehoon Oh Chan Lee Department of Robotics and Mechatronics Engineering DGIST Daegu Korea Department of Automation Fraunhofer IPK Berlin Germany Department of Robotics Engineering Yeungnam University Gyeongsan Korea

In conventional robust motion control systems, disturbance observer (DOB) nominal models are designed with same order as the actual plant such that the nominal model directly cancels with the actual plant dynamics. However, for multi-DOF systems such as 6-DOF industrial robots, identifying the higher-order model is laborious. Moreover, there is a high risk of obtaining a nominal model with large deviation from the actual plant due to severe parameter uncertainty. Thus, a reduced-order nominal model is derived from the actual plant model and compared with the one which same order as the actual plant in this paper. The designed model is simple, easy to identify and implement. From the analyses and experiment results, DOB with the proposed nominal model is not affected by severe robot model uncertainty and show significant improvement in motion control performance in terms of transient response and tracking accuracy.

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ExSLeR: Development of a Robotic Arm for Human Skill Learning

ExSLeR: Development of a Robotic Arm for Human Skill Learnin...

引用

IEEE/ASME (AIM) International Conference on Advanced Intelligent mechatronics

作者： Deokjin Lee Kiyoung Choi Junyoung Kim Wonbum Yun Taehoon Kim Kanghyun Nam Sehoon Oh Department of Robotics and Mechatronics Engineering DGIST Daegu Korea Department of Mechanical Engineering Yeungnam University Gyeongsan Korea

The trend in robotics has shifted from collaboration with humans to learning and reproducing human skills, reflecting a growing social demand. In response, it is imperative to consider both hardware and software aspects in the design of robots. On the hardware side, the robot should be equipped with adequate sensors for mimicking human motion and force, and its design should meet necessary requirements such as workspace, degree of freedom, payload capacity, and weight, all of which are contingent upon the intended use of the robot. On the software side, the robot should be equipped with a real-time system and stable control algorithms to ensure safe operation. This paper presents the ExSLeR arm which meets the requirements for human skill learning. The performance of the ExSLeR arm is validated by a set of experiments through motion tracking with heavy payload and compliant interaction control tasks.

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Analysis and Design Optimization of Surface Permanent Magnet Motor to Improve Torque Density and Ripple 11

Analysis and Design Optimization of Surface Permanent Magnet...

引用

11th International Conference on Power Electronics - ECCE Asia, ICPE 2023-ECCE Asia

作者： Shakhin, Yussuf Talapiden, Kulash Minh Thao, Nguyen Gia Bagheri, Mehdi Duc Do, Ton Department of Robotics and Mechatronics AstanaZ05H0P9 Kazakhstan Toyota Technological Institute Graduate School of Engineering Japan Department of Electrical and Computer Engineering AstanaZ05H0P9 Kazakhstan

ISBN: (纸本)9788957083505

Small-scale permanent magnet motor to reach high torque density and low torque ripple is discussed in this research. To increase the torque density, meanwhile making the motor size smaller and lighter, the motor axial length within a constrained diameter is optimized in view of various pole-slot configurations. Different slot-poles are selected and various combinations are studied, and the stator windings are optimized. To compare the torque density and ripple of new designs, precise models are created and simulated through ANSYS Maxwell 2D FEA under constant operational conditions, such as rated speed, torque, and power. Over the new designs, the influence of loss and temperature distribution variations in motor elements are analyzed. The simulation results show that the proposed 20-pole 18-slot motor design will obtain superior torque density and lower torque ripple compared to the baseline design. The final design provides a 30.7 % improvement of the torque density within the same rated torque condition. © 2023 The Korean Institute of Power Electronics.

关键词： Finite element method

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The Effects of Dyadic vs Triadic Interaction on Children’s Cognitive and Affective Gains in Robot-Assisted Alphabet Learning 14th

The Effects of Dyadic vs Triadic Interaction on Children’...

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14th International Conference on Social robotics, ICSR 2022

作者： Telisheva, Zhansaule Zhanatkyzy, Aida Oralbayeva, Nurziya Amirova, Aida Aimysheva, Arna Sandygulova, Anara Department of Robotics and Mechatronics School of Engineering and Digital Sciences Nazarbayev University Astana Kazakhstan Graduate School of Education Nazarbayev University Astana Kazakhstan

ISBN: (纸本)9783031246692

Robot-assisted language learning (RALL) is an emerging field of human-robot interaction to support language acquisition and literacy development with a social robot in multi-modal ways. As learning is an inherently social activity, the effectiveness of dyadic and triadic types of social interaction in RALL and child-robot interaction (CRI) needs to be investigated. In early literacy education, the Montessori method is a remarkable child-centered and collaborative learning approach. Bridging these two spaces, our work attempts to examine if the nature of social interaction, dyadic and triadic, affects children’s outcomes in an environment that adheres to the Montessori principles. To this end, we conducted a between-subject design experiment with 33 Kazakh children aged 6–8 to compare the effectiveness of learning Kazakh Latin in the dyadic and triadic conditions in a Moveable Alphabet learning scenario with a social robot. The analyses revealed mixed results for dyadic and triadic conditions in terms of cognitive gains, while emotional engagement was better in the triadic condition. We discuss these results in the perspective of key insights from the current study and implications for future research. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Human robot interaction

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Exploring Neural Networks for Forward Kinematics of the Robotic Arm with Different Length Configurations: A Comparative Analysis 2

Exploring Neural Networks for Forward Kinematics of the Robo...

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Bouzid, Rania Narayan, Jyotindra Gritli, Hassène Higher Institute of Information and Communication Technologies Tunis Borj Cedria1164 Tunisia Indian Institute of Technology Guwahati Mechatronics and Robotics Laboratory Department of Mechanical Engineering Assam Guwahati781039 India National Engineering School of Tunis Le Belvédère Tunis1002 Tunisia

ISBN: (纸本)9798350360523

Our work investigates the utilization of Artificial Neural Networks (ANNs) to address the complexities associated with Forward Kinematics (FK) problems within the field of robotics. We undertake an extensive comparative analysis to assess how ANNs perform under different circumstances with robotic arms of varying lengths and impact the overall system's functionality. The training, testing, and validation of ANNs are carried out using MATLAB for a simulated 2-DoF serial robotic arm involving three distinct datasets: fixed step size, random step size, and sinusoidal step size. Three training optimizers, namely Levenberg Marquardt (LM), Bayesian Regularization (BR), and Stochastic Conjugate Gradient (SCG), are considered within the ANN architecture. Based on Mean Square Error (MSE) values, the numerical findings reveal the potential of ANN in estimating forward kinematic solutions of complex robotic manipulators with different arm lengths and reducing computational complexity. © 2024 IEEE.

关键词： Robotic arms

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Moveable Älıpbi: The Montessori Method for Robot-Assisted Alphabet Learning 14th

Moveable Älıpbi: The Montessori Method for Robot-Assisted...

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14th International Conference on Social robotics, ICSR 2022

作者： Zhanatkyzy, Aida Telisheva, Zhansaule Amirova, Aida Oralbayeva, Nurziya Aimysheva, Arna Sandygulova, Anara Department of Robotics and Mechatronics School of Engineering and Digital Sciences Nazarbayev University Astana Kazakhstan Graduate School of Education Nazarbayev University Astana Kazakhstan

ISBN: (纸本)9783031246692

The Montessori method is well-known for its child-centered and hands-on learning approach for early literacy development. This study is the first to apply the Montessori method in robot-assisted language learning (RALL). We developed an alphabet learning system that consists of a Moveable alphabet, a tablet, and a social robot. We conducted a between-subjects experiment with 89 Kazakh children aged 6–11 that learned the Kazakh Latin alphabet either with a Montessori-human (MH) or a Montessori-robot (MR) teacher. We examined the effects of the learning method on children’s learning gains and emotional outcomes across these two conditions. Our results suggest that in the Montessori learning environment the MH teacher was significantly more effective in providing early literacy support than the MR teacher. The emotional states were mixed between grades, but the children in the MR condition felt happier than those in the MH condition in Grades 1 (ages 6–7) and 4 (ages 10–11). This exploratory study suggests testing the method’s effectiveness in long-term child-robot interactions, with varied learning tasks over time. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Human robot interaction

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Dual UWB Anchors-Based Target Tracking Strategy for an Omnidirectional Mobile Robot

Dual UWB Anchors-Based Target Tracking Strategy for an Omnid...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Le Bao Kai Li Wenbin Dong Wenqi Li Kyoosik Shin Changsoo Han Wansoo Kim Department of Mechatronics Engineering Hanyang University Ansan Republic of Korea Robotics Department Hanyang University ERICA Ansan Republic of Korea

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

Target tracking mobile robots still face challenges in terms of localization accuracy and tracking performance. This study presents a novel target tracking strategy for an omnidirectional mobile robot by using dual ultra-wideband (UWB) anchors. The proposed target tracking strategy integrates these sensors with a Mecanum wheeled mobile platform, optimizing motion control and target tracking. Based on the developed dual UWB anchors’ geometric localization model, the horizontal relative distance and orientation between the target and the robot were estimated. In tracking scenarios, the robot demonstrates advanced adaptability: While the target is at close-range, the robot rotates in place for orientation tracking to directly face the target, and the designed tracking algorithm allows the robot to dynamically adjust its rotation speed, resulting in smooth tracking movements. While the target is at longer-range, the robot dynamically modifies its tracking speed and orientation according to relative positional data, to ensure effective and continuous target following. Through experimental validation, the lateral error during target tracking is reduced, the tracking accuracy is improved by 50% compared to existing related studies, and the tracking performance is smoother.

关键词： Location awareness Target tracking Accuracy Robot sensing systems Sensor systems Sensors Mobile robots Reliability Faces Ultra wideband technology

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Action-Driven Tactile Object Exploration for Shape Reconstruction via Silver Nanowire Injected Sensors

Action-Driven Tactile Object Exploration for Shape Reconstru...

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2024 IEEE/SICE International Symposium on System Integration, SII 2024

作者： Mussin, Tleukhan Kassym, Yermakhan Kabdyshev, Nurlan Kaikanov, Marat Kappassov, Zhanat School Engineering and Digital Sciences Nazarbayev University Kazakhstan Nazarbayev University Dept. of Robotics and Mechatronics 53 Kabanbay Batyr Ave AstanaZ05H0P9 Kazakhstan Nazarbayev University Physics Department Kazakhstan

ISBN: (纸本)9798350312072

We present an action-driven tactile exploration system using flexible touch sensors integrated into the fingertips of a robot hand. These sensors are made from foams injected with silver nanotubes that exhibit resistance changes under pressure to enable tactile perception. A microcontroller-based unit captures the resistance, with communication deployed using the Robot Operating System. Our approach is evaluated in tactile object exploration, where robotic finger movements estimate the coordinates of the points of contact upon collisions with an object. Through repeated grasps, a point cloud of the shape of an object is generated. Distinct finger movements, or affordances, are developed to collect new contact points to discriminate four different shapes, including cube, cylinder, pyramid, and sphere. We benchmark our approach on medium and large sets of objects. © 2024 IEEE.

关键词： Robot Operating System

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DEVELOPMENT OF 3D PRINTED SOFT PNEUMATIC HAND MOTION SENSORS

DEVELOPMENT OF 3D PRINTED SOFT PNEUMATIC HAND MOTION SENSORS

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ASME 2022 International Mechanical engineering Congress and Exposition, IMECE 2022

作者： Papendorp, Sky Iyun, Olukayode Schneider, Christian Tekes, Ayse Ashuri, Turaj Amiri Moghadam, Amir Ali Robotics and Mechatronics Department Kennesaw State University MariettaGA United States Mechanical Engineering Department Kennesaw State University MariettaGA United States

ISBN: (纸本)9780791886663

This paper reports on the design, fabrication, and evaluation of a novel 3D printed vacuum based soft sensor and its application as hand motion sensor. Soft sensors are an integral part of soft robotics as an emerging field of science that enables safe and easy human to machine interaction. The conventional sensors used to interface with humans in robotic systems are mechanically incompliant. Because of this mechanical compliance mismatch, these sensors cause unsafe interactions with humans. Recent advancements in 3D printing technology have allowed fabrication of complex geometries with soft polymers, perfect for more delicate and user-friendly sensors. While the existing soft pneumatic sensors work based on the positive pressure due to deformation, the proposed sensor in this work works based on vacuum due to deformation. In comparison with the similar positive pressure sensor, our vacuum-based sensor is much softer and has minimum interference with hand motion. Finite element analysis (FEA) is used to analyze the design. Also, a kinematic model of the hand is developed using Matlab to visualize the hand motion based on the sensor data. This could show the potential application of the soft hand motion sensor in virtual reality and telehealth. Copyright © 2022 by ASME.

关键词： Finite element method

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