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Influence of Centrodes Coefficient on the Characteristic of Gear Ratio Function of the Compound Non-circular Gear Train with Improved Cycloid Tooth Profile 6th

Influence of Centrodes Coefficient on the Characteristic of ...

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6th IFToMM Asian Mechanisms and Machine Science Conference, Asian MMS 2021

作者： Thai, Nguyen Hong Van Thom, Phung Trung, Nguyen Thanh Department of Mechanical Design and Robotics School of Mechanical Engineering Hanoi University of Science and Technology Hanoi Viet Nam Vietnam National Research Institute of Mechanical Engineering Hanoi Viet Nam

ISBN: (纸本)9783030918910

In this paper, the authors evaluate the influence of the centrodes coefficients on the gear ratio function characteristics of the compound non-circular gear (CNCG) train formed by two pairs of external non-circular gears (NCGs). First, a mathematical model describing the mating centrodes for the CNCG train has been establishing. From there, evaluate the influence of centrode coefficients μ1 and μ2 of NCGs in the CNCG train on the gear ratio function characteristic for the CNCG train. A design of a CNCG train with an improved cycloid tooth profile by a rack cutter. The evaluation results show that when increasing μ1, transmission size tends to decrease, but the speed and torque variation range rises to 54.31%. While reducing μ2, the speed variation and torque range increase, but the mating centrodes of NCGs 4 is a concave curve that cannot gear shaping by a rack cutter or hob cutter must be by shaper cutter. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Function evaluation

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In Situ Material Identification, Machining Monitoring, and Cloud Logging Integrated with AI and Machine Vision

In Situ Material Identification, Machining Monitoring, and C...

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Innovative Trends in Information Technology (ICITIIT), International Conference on

作者： Penumuru Durga Prasad Deep Patel Sreekumar Muthuswamy Premkumar Karumbu Department of Mechanical Engineering Centre for AI IoT and Robotics Indian Institute of Information Technology Design and Manufacturing Kancheepuram Kancheepuram Chennai India Department of Electronics and Communications Engineering. Centre for AI IoT and Robotics Indian Institute of Information Technology Design and Manufacturing Kancheepuram Kancheepuram Chennai India

ISBN: (数字)9798350386813

ISBN: (纸本)9798350386820

Current process monitoring in machining hampers manufacturing efficiency due to manual data entry, fragmented systems, and lack of real-time data capture. This challenge is particularly tough for small to medium-sized enterprises (SMEs) without advanced tools. Our proposed methodology employs a collaborative robot (UR16e) with a machine vision system (InSight 7802C). The robot shifts the vision system to capture images of machining processes and workpieces. Enhanced with a fine-tuned Support Vector Machine (SVM) classifier, the vision system accurately identifies Aluminum, Copper, Mild Steel, and Medium-density fibreboard (MDF). Operational data, including material types and machine usage, is locally recorded and uploaded to Microsoft Azure cloud storage for data integrity and stakeholder transparency. This approach enhances process control and decision-making. Preliminary results validate its practicality and potential to boost manufacturing process monitoring. It sets a solid foundation for further exploration into smart manufacturing research, which is crucial for staying competitive in today’s rapidly evolving industrial landscape.

关键词： Support vector machines Process monitoring Cloud computing Service robots Machine vision Machining Drilling machines

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Safe Spot: Exploring perceived safety of dominant vs submissive quadruped robots

Safe Spot: Exploring perceived safety of dominant vs submiss...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Nanami Hashimoto Emma Hagens Arkady Zgonnikov Maria Luce Lupetti Department of Cognitive Robotics Delft University of Technology Delft The Netherlands Department of Industrial Design Engineering Delft University of Technology Delft The Netherlands Department of Architecture and Design Politecnico di Torino Turin Italy

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

Unprecedented possibilities of quadruped robots have driven much research on the technical aspects of these robots. However, the social perception and acceptability of quadruped robots so far remain poorly understood. This work investigates whether the way we design quadruped robots’ behaviours can affect people’s perception of safety in interactions with these robots. We designed and tested a dominant and submissive personality for the quadruped robot (Boston Dynamics Spot). These were tested in two different walking scenarios (head-on and crossing interactions) in a 2x2 within-subjects study. We collected both behavioural data and subjective reports on participants’ perception of the interaction. The results highlight that participants perceived the submissive robot as safer compared to the dominant one. The behavioural dynamics of interactions did not change depending on the robot’s appearance. Participants’ previous in-person experience with the robot was associated with lower subjective safety ratings but did not correlate with the interaction dynamics. Our findings have implications for the design of quadruped robots and contribute to the body of knowledge on the social perception of non-humanoid robots. We call for a stronger standing of felt experiences in human-robot interaction research.

关键词： Legged locomotion Human-robot interaction Safety Quadrupedal robots

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Estimating speaker direction on a humanoid robot with binaural acoustic signals

arXiv

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arXiv 2023年

作者： Barot, Pranav Mombaur, Katja MacDonald, Ewen N. Department of Systems Design Engineering University of Waterloo WaterlooON Canada Optimization and Biomechanics for Human-Centred Robotics Karlsruhe Germany and CERC Human-Centred Robotics and Machine Intelligence Department of Systems Design Engineering University of Waterloo Waterloo Canada

To achieve human-like behaviour during speech interactions, it is necessary for a humanoid robot to estimate the location of a human talker. Here, we present a method to optimize the parameters used for the direction of arrival (DOA) estimation, while also considering real-time applications for human-robot interaction scenarios. This method is applied to binaural sound source localization framework on a humanoid robotic head. Real data is collected and annotated for this work. Optimizations are performed via a brute force method and a Bayesian model based method, results are validated and discussed, and effects on latency for real-time use are also explored. © 2023, CC BY.

关键词： Anthropomorphic robots

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A Low Cost on-Device Intruder Detection System for Smart Home Environment

A Low Cost on-Device Intruder Detection System for Smart Hom...

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Conference on Information and Communication Technology (CICT)

作者： Chayan Maiti Vivekanand E Sreekumar Muthuswamy Department of Mechanical Engineering Centre for AI IoT and Robotics Indian Institute of Information Technology Design and Manufacturing Kancheepuram Chennai India

ISBN: (数字)9798331531539

ISBN: (纸本)9798331531546

Robust security is tritical for smart homes to protect families and goods from potential intruder threats. Vision-based intruder detection systems are commonly used for this task. However, only a few households have adopted such security technology because of its high cost, which includes both expensive devices and service costs. To address this issue, a low-cost intruder detection system is investigated in this study, leveraging a Raspberry Pi 4 with a camera module. Smart resource utilization strategies are employed to enable on-device local processing for privacy preservation of sensitive video data. To achieve real-time processing on resource constrain hardware, efficient motion detection is accomplished using the frame subtraction technique, while rapid face detection is accomplished through the haar cascade utilizing Kalman filter. Face identification using OpenFace model is speed up by subsequent template matching technique. The proposed algorithm achieved an average frame rate of 22 FPS making it capable for real-time intruder detection with environmental constrain.

关键词： Costs Subtraction techniques Smart homes Prediction algorithms Real-time systems Motion detection Face detection Kalman filters Security Faces

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Learning Complicated Manipulation Skills Via Deterministic Policy with Limited Demonstrations

Learning Complicated Manipulation Skills Via Deterministic P...

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International Conference on Advanced robotics (ICAR)

作者： Haofeng Liu Jiayi Tan Yiwen Chen Marcelo H Ang Department of Mechanical Engineering National University of Singapore Advanced Robotics Centre College of Design and Engineering National University of Singapore

Deep reinforcement learning, when combined with demonstrations, can effectively formulate policies for manipulators. However, the practical collection of ample high-quality demonstrations is time-consuming, and demonstrations generated by humans may not perfectly correspond with the operational demands of robots. These challenges are intensified by issues such as non-Markovian processes and excessive reliance on demonstrations. Our study indicates that in manipulation tasks, reinforcement learning (RL) agents are sensitive to the quality of demonstrations and struggle to adapt to those derived from humans. As a result, leveraging low-quality or scarce demonstrations to assist reinforcement learning in developing superior policies presents a significant challenge. In some cases, dependence on limited demonstrations may paradoxically impair performance. To address these challenges, we propose a novel algorithm, TD3fG (TD3 learning from a generator). This algorithm facilitates a seamless transition from learning from experts to learning from experience, enabling agents to assimilate prior knowledge while mitigating the negative impacts of the demonstrations. Our algorithm demonstrates notable improvement in the Adroit manipulator and MuJoCo tasks, even with limited demonstrations of mixed failure trajectory.

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Shaping Drivers’ Understanding of Control: The Effect of Visual User Interfaces on Control Responsibilities in Automated Vehicles

SSRN

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SSRN 2024年

作者： Kim, Soyeon Nordhoff, Sina van Egmond, René Happee, Riender Department of Human-Centered Design Faculty of Industrial Design Engineering Delft University of Technology Netherlands Department Transport & Planning Faculty of Civil Engineering and Geosciences Delft University of Technology Netherlands Department of Cognitive Robotics Faculty of Mechanical Engineering Delft University of Technology Netherlands

As vehicles transition between driving automation levels, drivers need to be aware of their responsibilities and the function of automation mode. This study investigates the impact of visual user interfaces (UIs) on drivers' mode awareness in SAE Level 2 automated vehicles. It focuses on their understanding of lateral control, longitudinal control, and steering wheel requirements presented through UIs. Forty-five UIs were generated, presenting for activation of Lane Keeping Assist (LKA) and Adaptive Cruise Control (ACC) and requirements of Hands-on steering wheel. Through an online questionnaire with 1080 respondents with experience of SAE Level 2 partial driving automation, the study evaluated how visual UIs influenced users' understanding of control responsibilities, information usability, and trust in automated vehicles. The results show the important role of UI in shaping users' understanding of control responsibility. Hands-on steering wheel UIs significantly improved the understanding of hands-on steering wheel requirements, whereas ACC UIs and LKA UIs had no significant effects. The hands-on steering wheel UI combining the hands on the wheel icon and the text "Keep hands on steering wheel" yielded 94.4% correct understanding and outperformed the UI with hands but without text (87.8% correct) or no UI (82.5% correct). The response of longitudinal and lateral control responsibility was independent of the ACC UI and LKA UI. This study contributes to the understanding and design of visual UIs for effective communication of driver responsibilities in automated vehicles. © 2024, The Authors. All rights reserved.

关键词： User interfaces

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Development of the Physical Simulation Platform for Catenary Cantilever

Development of the Physical Simulation Platform for Catenary...

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IEEE International Conference on Mechatronics and Automation

作者： Jinjiao Xie Chuxiong Hu Zhenhua Li Mingli Liu Department of Mechanical Engineering Tsinghua University Beijing China Department of Research and Design THTC Robotics (Tianjin) Co. Ltd. Tianjin China

ISBN: (数字)9798350388077

ISBN: (纸本)9798350388084

Regarding to the problem of deviations in the cantilever pre-assembling, a physical simulation platform for cantilevers has been developed. This platform simulates the actual operating conditions of the high-speed rail pantograph-catenary and conducts simulated inspections and calculations to the pre-assembling cantilever before installation, obtaining stagger value data and predicting whether the cantilever is qualified or not. This allows for timely adjustments or re-manufacturing of the cantilever, thereby effectively reducing construction risks.

关键词： Laser theory Mechatronics Automation Measurement by laser beam User interfaces Inspection Rail transportation

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An Audio-Video Sensor Fusion Framework To Augment Humanoid Capabilities For Identifying And Interacting With Human Conversational Partners

An Audio-Video Sensor Fusion Framework To Augment Humanoid C...

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IEEE-RAS International Conference on Humanoid Robots

作者： Pranav Barot Ewen N. MacDonald Katja Mombaur Department of Systems Design Engineering University of Waterloo Canada Department of Systems Design Engineering University of Waterloo Optimization and Biomechanics for Human-Centred Robotics Karlsruhe Germany and CERC Human-Centred Robotics and Machine Intelligence Karlsruhe Institute of Technology (KIT) Institute of Anthropomatics and Robotics (IAR) Waterloo Canada

Human robot interaction often requires many sub-systems to work together in order to facilitate more natural and intelligent interactions with multiple humans. For this work, the relevant systems include audio and visual direction of arrival estimation that are used in an encompassing sensor fusion framework. The presented sub-systems are used concurrently online to allow for humanoid robots to identify active speakers in a scene, track human subjects, and identify when other subjects may require attention. We present evaluations of performance, while also implementing relevant humanlike behaviours on the REEM-C Humanoid Robot. A conducted user study delivers valuable feedback on these systems, which provide a strong foundation for improved humanoid intelligence and more innovative human-robot interaction.

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Online Estimation of 2D Human Arm Stiffness for Peg-in-Hole Tasks with Variable Impedance Control

Online Estimation of 2D Human Arm Stiffness for Peg-in-Hole ...

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

作者： Huayang Wu Hanwen Yang Yanan Li Department of Engineering and Design University of Sussex Brighton UK Robotics Institute Beihang University Beijing China

This paper proposes an online estimation model for 2D arm stiffness in humans. The proposed model is based on recent physiological findings which suggest that: (1) joint stiffness is linearly related to the magnitude of joint torque and increases to compensate for environmental disturbances; and (2) the endpoint stiffness of the arm is proportional to grasp force. To validate the proposed model, perturbation experiments were conducted under different grasp forces. The model parameters were identified and the accuracy of the model was assessed. The results showed that the proposed model has advantages over previous models for estimating human arm endpoint stiffness, in the sense of simplicity and robustness. The proposed model was also used to design a variable stiffness controller for peg-in-hole tasks, demonstrating the potential of the model for human-robot collaboration.

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