• Title/Summary/Keyword: one-wheeled robot

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Evolving live load criteria in bridge design code guidelines - A case study of India based on IRC 6

  • Karthik, P.;Sharma, Shashi Kant;Akbar, M. Abdul
    • Structural Monitoring and Maintenance
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    • v.9 no.1
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    • pp.43-57
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    • 2022
  • One of the instances which demand structural engineer's greatest attention and upgradation is the changing live load requirement in bridge design code. The challenge increases in developing countries as the pace of infrastructural growth is being catered by the respective country codes with bigger and heavier vehicles to be considered in the design. This paper presents the case study of India where Indian Roads Congress (IRC) codes in its revised version from 2014 to 2017 introduced massive Special vehicle (SV) around 40 m long and weighing 3850 kN to be considered in the design of road bridges. The code does not specify the minimum distance between successive special vehicles unlike other loading classes and hence the consequences of it form the motivation for this study. The effect of SV in comparison with Class 70R, Class AA, Class A, and Class B loading is studied based on the maximum bending moment with moving load applied in Autodesk Robot Structural Analysis. The spans considered in the analysis varied from 10 m to 1991 m corresponding to the span of Akashi Kaikyo Bridge (longest bridge span in the world). A total of 182 analyses for 7 types of vehicles (class B, class A, class 70R tracked, class 70R wheeled, class AA tracked, AA wheeled, and Special vehicle) on 26 different span lengths is carried out. The span corresponding to other vehicles which would equal the bending moment of a single SV is presented along with a comparison relative to Standard Uniformly Distributed Load. Further, the results are presented by introducing a new parameter named Intensity Factor which is proven to relate the effect of axle spacing of vehicle on the normalized bending moment developed.

Vision Sensor-Based Driving Algorithm for Indoor Automatic Guided Vehicles

  • Quan, Nguyen Van;Eum, Hyuk-Min;Lee, Jeisung;Hyun, Chang-Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.13 no.2
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    • pp.140-146
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    • 2013
  • In this paper, we describe a vision sensor-based driving algorithm for indoor automatic guided vehicles (AGVs) that facilitates a path tracking task using two mono cameras for navigation. One camera is mounted on vehicle to observe the environment and to detect markers in front of the vehicle. The other camera is attached so the view is perpendicular to the floor, which compensates for the distance between the wheels and markers. The angle and distance from the center of the two wheels to the center of marker are also obtained using these two cameras. We propose five movement patterns for AGVs to guarantee smooth performance during path tracking: starting, moving straight, pre-turning, left/right turning, and stopping. This driving algorithm based on two vision sensors gives greater flexibility to AGVs, including easy layout change, autonomy, and even economy. The algorithm was validated in an experiment using a two-wheeled mobile robot.

Fuzzy PD+I Control Method for Two-wheel Balancing Mobile Robot (퍼지 PD+I 제어 방식을 적용한 Two-wheel Balancing Mobile Robot)

  • Eom, Ki-Hwan;Lee, Kyu-Yun;Lee, Hyun-Kwan;Kim, Joo-Woong
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.45 no.1
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    • pp.1-8
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    • 2008
  • A two-wheel balancing vehicle, which helps people moving freely and fast, and is applied from inverted pendulum system, has been widely researched and developed, and some products are came into a market in actuality. Until now, the two-wheel balancing vehicles developed have chosen the general PID control method. In this paper, we propose a new control method to improve a control capacity for a two-wheeled balancing vehicle for human transportation. The proposed method is the fuzzy PD+I control that is one of the improved PID control, and it contains a 2input-1output fuzzy system. This fuzzy system processes signals from proportional and derivative controller, and the fuzzy output signal generates the final output by summing up integral signal. The non-linearity of the fuzzy system makes an optimal output control signal by changing weight of the proportional signal and the derivative signal in process of time. We have simulated the fuzzy PD+I control system and experimented by implementing the two-wheel balancing mobile robot to verify the advantages of the proposed fuzzy PD+I control method in comparison with general PID control. As the results of simulation and experimentation, the proposed fuzzy PD+I control method has better control performance than general PID in this system and improves it.