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IEEE International Conference on robotics and Biomimetics

作者： Jongwon Park Young Kook Kim Won Suk Jung Kyung-Soo Kim Soohyun Kim Department of Mechanical Engineering KAIST Robotics Program KAIST

ISBN: (纸本)9781457721366

This paper introduces 'Ground Following Locomotion' as a means to traverse rough terrain inspired by pill bugs (Armadillidium vulgare). The locomotion of pill bugs is unique and effective on irregular terrain. Pill bugs bend their bodies actively along with the terrain to maintain traction force and the behavior enables them to overcome irregular terrain easily. This biological principle can be applied to small robots to overcome rough terrain by adjusting relative positions of body modules. Analysis and simulations will be conducted to compare performance of adjustable joint model (ground following locomotion) and fixed joint model and the results will show that the performance of ground following locomotion is effective to overcome vertical obstacles. The principle described here could be applied to small ground robots to improve mobility on rough terrains.

关键词： Locomotion Rough terrain Robot Pill Dosage Form bugs Bugs small robots terrains ground Traction force landscapes Respiratory Inspiration

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Design improvements and dynamic characterization on fluidic elastomer actuators for a soft robotic snake

Design improvements and dynamic characterization on fluidic ...

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IEEE International Conference on Technologies for Practical Robot Applications (TePRA)

作者： Ming Luo Weijia Tao Fuchen Chen Tri K. Khuu Selim Ozel Cagdas D. Onal Robotics Engineering Program Worcester Polytechnic Institute MA USA Mechanical Engineering Department and Robotics Engineering Program Worcester Polytechnic Institute MA USA

This paper addresses the design and dynamic analysis of a new generation of fluidic elastomer actuators (FEAs) that offer bidirectional bending developed as motion segments of a pressure-operated soft robotic snake. Our prior work on FEAs has identified a number of limitations, namely a high center of gravity, narrow base, slow dynamics, and a small range of pressure inputs. We developed two versions of FEAs based on an improved design concept with different geometric parameters and characterized their dynamic response under a custom visual tracking system. Compared with the previous actuators, the FEAs developed in this work offer robust operation, safety at larger input pressure values, faster response, lower center of gravity and a flat bottom for better compatibility for snake-like undulatory locomotion.

关键词： Actuators Robot kinematics Rubber Pneumatic systems Fabrication Valves

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Linear One-to-Many (OTM) system

Linear One-to-Many (OTM) system

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IEEE International Conference on Technologies for Practical Robot Applications (TePRA)

作者： Thane R. Hunt Christopher J. Berthelette Marko B. Popovic Robotics Engineering Program Worcester Polytechnic Institute Worcester MA USA Robotics Engineering Program Mechanical Engineering Department Worcester Polytechnic Institute Worcester MA USA Robotics Engineering Program Biomedical Engineering Department Physics Department Worcester Polytechnic Institute Worcester MA USA

We report on progress on the "One-To-Many" (OTM) concept that allows a single electric motor to store energy in the form of elastic potential energy to drive multiple (e.g. hundred) motor units or independently controlled mechanical degrees of freedom. Critical to this concept is the OTM architecture which utilizes light weight, high-speed, energy efficient, robust, and cost-effective clutches that provide positional feedback. Here, we address linear springs as elastic mediums for energy storage and bi-stable solenoid based clutches that require minimal energy to transition between states. We analyze the power transfer of the system, discuss current and future designs and suggest avenues for potential applications of this practical technology.

关键词： Prototypes Mechanical cables Vehicles

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Development of Automatic Detection and Monitoring Application System for Peristaltic Condition based on Machine Learning and Internet of Thing (IoT) System 7

Development of Automatic Detection and Monitoring Applicatio...

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7th International Conference of Computer and Informatics engineering, IC2IE 2024

作者： Astuti, Winda Giovanni Benedict Davin, K. Nurul Puji, Muhammad Kunaifi, Matthew Andriatin, Yuli Astuti Bina Nusantara University Binus Aso School of Engineering Automotive and Robotics Program Computer Engineering Department Jakarta Indonesia Cilacap Regional General Hospital Gatot Subroto No.28 Cilacap Indonesia

ISBN: (纸本)9798331505530

Poor sanitation and limited access to clean water are the main causes of increased risk of gastrointestinal diseases. In Indonesia, environmental hygiene problems are the main cause of digestive tract disorders, which contribute to more than 25% of deaths each year according to data from the Ministry of Health. Digestive disease is one of the diseases that often appears due to Poor sanitation and limited access to clean water. The development of a digital stethoscope for early detection of problems in the digestive tract would be useful, especially in remote areas. The sound was recorded from a Mel Frequency Cepstral Coefficient (MFCC) technique. The resulting features extracted from the stethoscope sound signal, are used as the inputs for the machine learning which applied three types of method, they are Logistic Regression (LR), combination of Logistic Regression (LR) and K-Nearest Neighbors (KNN), combination of Logistic Regression (LR) and Support Vector Machine (SVM). The experiment of MFCC with three types of machine learning methods above, based the sound from a stethoscope. Experimental results show the combination of Logistic Regression (LR) and K-Nearest Neighbors (KNN) has exceeded results among other methods, with the training and testing accuracy of 90 % and 88 % respectively. They confirm the effectiveness of the proposed intelligent automatic stethoscope sound identification based on Mel-Frequency Cepstral Coefficient (MFCC) and Linear Regression. Furthermore, the system continuously saves and monitors the result of the patient. © 2024 IEEE.

关键词： Logistic regression

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Three-dimensional reconstruction of a semi-submersible offshore platform with an unmanned surface vehicle

Three-dimensional reconstruction of a semi-submersible offsh...

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OCEANS - Europe

作者： Jungwook Han Minju Kang Jeonghyeon Wang Jinwhan Kim Department of Mechanical Engineering Robotics Program KAIST Daejeon Korea

ISBN: (纸本)9781467397254

This paper addresses the three-dimensional (3D) reconstruction of a floating structure with an unmanned surface vehicle (USV). Onboard lidar and sonar sensors are employed to collect a volumetric point cloud of the structure both above and below the waterline. These measurements are obtained in the vehicle-fixed frame; thus, for successful 3D reconstruction, precision estimation of trajectory and attitude is required. GPS signals are severely deteriorated or unavailable near and under floating structures. Therefore, relative navigation with respect to the planar surfaces of their hull structures is performed in the framework of simultaneous localization and mapping (SLAM). This approach enables high-precision navigation and mapping near and under a large floating structure. A field experiment was performed in a semi-submersible offshore platform environment and the results are presented.

关键词： Three-dimensional displays Vehicles Laser radar Sensors Surface reconstruction Sonar navigation Sonar

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Underwater Visual SLAM with Loop-Closure using Image-to-Image Link Recovery

Underwater Visual SLAM with Loop-Closure using Image-to-Imag...

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OCEANS

作者： Seonghun Hong Taeyun Kim Jinwhan Kim Robotics Program Department of Mechanical Engineering KAIST Daejeon Korea

ISBN: (纸本)9781479987375

This study develops an underwater visual simultaneous localization and mapping (SLAM) algorithm using a monocular vision as a major measurement sensor, focusing in particular on the loop-closure problem. Although most vision-based loop-closure approaches have been implemented by feature-based pairwise image matching, matching underwater images is generally a challenging task due to the limited number of feature correspondences or relatively small overlapping regions between the compared images. The lack of loop-closing events caused by these challenges can degrade the navigation and mapping performance of visual SLAM. For robust visual SLAM, a loop-closure algorithm that can recover image-to-image matching links is presented. The proposed loop-closure algorithm is more resilient to failures of pairwise matching and thus can maximize the use of image-to-image links, thereby improving the estimation performance in the context of visual SLAM. To validate the effectiveness of the proposed algorithm, a hover-capable unmanned underwater vehicle was used for in-water experiments, and the proposed algorithm was also evaluated through a series of comparative results drawn from an experimental dataset.

关键词： Underwater visual SLAM Loop-closure Link recovery

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Automatic petrol and diesel engine sound identification based on machine learning approaches 1

Automatic petrol and diesel engine sound identification base...

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1st International Conference on Automotive, Manufacturing, and Mechanical engineering, IC-AMME 2018

作者： Frederick, Halim Winda, Astuti Solihin, Mahmud Iwan Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia Faculty of Engineering Technology and Built Environment UCSI University Cheras Kuala Lumpur56000 Malaysia

Petrol and diesel engine have a significantly different way to convert chemical energy into mechanical energy. In this work, the intelligent system approach is used to automatically identify the type of engine based on the sound of the engine. The combination of signal processing and machine learning technique for automatic petrol and diesel engine sound identification is presented in this work. After a signal preprocessing step of the engine sound, a Fast Fourier Transform (FFT)-based frequency characteristic modelling technique is applied as the feature extraction method. The resulting features extracted from the sound signal, in the form of frequency in the FFT matrix, are used as the inputs for the machine learning, the Support Vector Machine (SVM), step of the proposed approach. The experiment of FFT with SVM-based diesel and petrol engine sound identification has been carried out. The results show that the proposed approach produces a good accuracy in the relatively short training time. Experimental results show the training and testing accuracy of 100 % and 100 % respectively. They confirm the effectiveness of the proposed intelligent automatic diesel and petrol engine sound identification based on Fast Fourier Transform (FFT) and Support Vector Machines (SVMs). © 2019 The Authors, published by EDP Sciences.

关键词： Support vector machines

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Design of interval type-2 fuzzy logic controllers for flocking algorithm

Design of interval type-2 fuzzy logic controllers for flocki...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Seung-Mok Lee Jong-Hwan Kim Hyun Myung Department of Civil and Environmental Engineering Robotics Program KAIST Daejeon South Korea Department of Electrical Engineering and Computer Science Robotics Program KAIST Daejeon South Korea

This paper presents a novel interval type-2 fuzzy logic control architecture for flocking system when the system has noisy sensor measurements. The traditional type-1 fuzzy logic controller (FLC) using precise type-1 fuzzy sets cannot fully model and handle the uncertainties of sensor data. However, type-2 FLC using type-2 fuzzy sets with a footprint of uncertainty (FOU) produces better performances under noisy environments. In this paper, therefore, we present a reactive control architecture for flocking algorithm that is based on interval type 2 FLC to implement the flocking behaviors consisting separation, obstacle avoidance, and velocity matching behaviors. The type-2 based control system could cope with the uncertainties of noisy sensor measurements and resulted in good performances that outperformed the type-1 FLC.

关键词： Collision avoidance Robot sensing systems Trajectory Fuzzy sets Fuzzy logic Noise measurement

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RoboRover - A Jetson Nano Powered Robot Car for Object Following, Obstacle Avoidance, and Wall Following 14

RoboRover - A Jetson Nano Powered Robot Car for Object Follo...

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14th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2023

作者： Huynh, Trinh Walter, James Aveta, Federica University of Michigan Robotics Department Ann ArborMI48109 United States Wentworth Insitute of Technology Electrical and Computer Engineering Program BostonMA02115 United States

ISBN: (纸本)9798350304138

An intelligent and self-sufficient robot is essential across a wide range of fields, including transportation, industry, space exploration, and defense. Mobile robots possess the capability to undertake diverse tasks such as handling materials, aiding in disaster scenarios, conducting patrols, and executing rescue operations. As a result, the development of an autonomous robot that can navigate through both unchanging and ever-changing surroundings has become important. The primary objective of mobile robot navigation revolves around ensuring the seamless and secure traversal of the robot through complex environments, starting from an initial position, and reaching a designated goal position. This paper presents the design and implementation of a Jetson Nano powered robot car which uses local sensors to interact with an unknown environment. Object following, obstacle avoidance, and wall following features are built for the car to navigate to reach its desired destinations. © 2023 IEEE.

关键词： Mobile robots

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Inverse reinforce learning with nonparametric behavior clustering

arXiv

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arXiv 2017年

作者： Rajasekaran, Siddharthan Zhang, Jinwei Fu, Jie Department of Electrical and Computer Engineering Robotics Engineering Program Worcester Polytechnic Institute

Inverse Reinforcement Learning (IRL) is the task of learning a single reward function given a Markov Decision Process (MDP) without defining the reward function, and a set of demonstrations generated by humans/experts. However, in practice, it may be unreasonable to assume that human behaviors can be explained by one reward function since they may be inherently inconsistent. Also, demonstrations may be collected from various users and aggregated to infer and predict users behaviors. In this paper, we introduce the Non-parametric Behavior Clustering IRL algorithm to simultaneously cluster demonstrations and learn multiple reward functions from demonstrations that may be generated from more than one behaviors. Our method is iterative: It alternates between clustering demonstrations into different behavior clusters and inverse learning the reward functions until convergence. It is built upon the Expectation-Maximization formulation and non-parametric clustering in the IRL setting. Further, to improve the computation efficiency, we remove the need of completely solving multiple IRL problems for multiple clusters during the iteration steps and introduce a resampling technique to avoid generating too many unlikely clusters. We demonstrate the convergence and efficiency of the proposed method through learning multiple driver behaviors from demonstrations generated from a grid-world environment and continuous trajectories collected from autonomous robot cars using the Gazebo robot simulator. Copyright © 2017, The Authors. All rights reserved.

关键词： Demonstrations

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