Raptor: A Design of a Drain Inspection Robot

被引:6
|
作者
Muthugala, M. A. Viraj J. [1 ]
Palanisamy, Povendhan [1 ]
Samarakoon, S. M. Bhagya P. [1 ]
Padmanabha, Saurav Ghante Anantha [1 ]
Elara, Mohan Rajesh [1 ]
Terntzer, Dylan Ng [2 ]
机构
[1] Singapore Univ Technol & Design, Engn Prod Dev Pillar, 8 Somapah Rd, Singapore 487372, Singapore
[2] LionsBot Int Pte Ltd, 03-02,11 Changi South St 3, Singapore 486122, Singapore
关键词
drain inspection; inspection robotics; reconfigurable robotics; navigation control; public health and safety; FLOOR CLEANING ROBOT; SYSTEM;
D O I
10.3390/s21175742
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Frequent inspections are essential for drains to maintain proper function to ensure public health and safety. Robots have been developed to aid the drain inspection process. However, existing robots designed for drain inspection require improvements in their design and autonomy. This paper proposes a novel design of a drain inspection robot named Raptor. The robot has been designed with a manually reconfigurable wheel axle mechanism, which allows the change of ground clearance height. Design aspects of the robot, such as mechanical design, control architecture and autonomy functions, are comprehensively described in the paper, and insights are included. Maintaining the robot's position in the middle of a drain when moving along the drain is essential for the inspection process. Thus, a fuzzy logic controller has been introduced to the robot to cater to this demand. Experiments have been conducted by deploying a prototype of the design to drain environments considering a set of diverse test scenarios. Experiment results show that the proposed controller effectively maintains the robot in the middle of a drain while moving along the drain. Therefore, the proposed robot design and the controller would be helpful in improving the productivity of robot-aided inspection of drains.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Remote drain inspection framework using the convolutional neural network and re-configurable robot Raptor
    Melvin, Lee Ming Jun
    Mohan, Rajesh Elara
    Semwal, Archana
    Palanisamy, Povendhan
    Elangovan, Karthikeyan
    Gomez, Braulio Felix
    Ramalingam, Balakrishnan
    Terntzer, Dylan Ng
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [2] Remote drain inspection framework using the convolutional neural network and re-configurable robot Raptor
    Lee Ming Jun Melvin
    Rajesh Elara Mohan
    Archana Semwal
    Povendhan Palanisamy
    Karthikeyan Elangovan
    Braulio Félix Gómez
    Balakrishnan Ramalingam
    Dylan Ng Terntzer
    Scientific Reports, 11
  • [3] The design of an inspection robot for boiler tubes inspection
    Lu Xueqin
    Qiu Rongfu
    Liu Gang
    Huang Fuzhen
    2009 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, VOL II, PROCEEDINGS, 2009, : 313 - 317
  • [4] Modelling and design of a drain cleaning robot
    Sulthana, S. Fouziya
    Vibha, K.
    Kumar, Sudhanshu
    Mathur, Sneha
    Mohile, Tarang Ashutosh
    3RD INTERNATIONAL CONFERENCE ON ADVANCES IN MECHANICAL ENGINEERING (ICAME 2020), PTS 1-6, 2020, 912
  • [5] Estimation of Sloshing Motion in a Wheel-based Drain Inspection Robot
    Parween, Rizuwana
    Palanisamy, Povendhan Arthanaripalayam
    Wen, Tan Yeh
    Terntzer, Dylan Ng
    Elara, Mohan Rajesh
    2022 IEEE 12TH ANNUAL COMPUTING AND COMMUNICATION WORKSHOP AND CONFERENCE (CCWC), 2022, : 688 - 693
  • [6] Hardware Design of a Pipeline Inspection Robot
    Zhang, Hui
    Zhao, Lina
    Dai, Xuefeng
    NEW TRENDS IN MECHATRONICS AND MATERIALS ENGINEERING, 2012, 151 : 116 - 120
  • [7] Design and analysis of welding inspection robot
    Pengyu Zhang
    Ji Wang
    Feng Zhang
    Peiquan Xu
    Leijun Li
    Baoming Li
    Scientific Reports, 12
  • [8] Design and experiments on cable inspection robot
    Wang, Xingsong
    Xu, Fengyu
    IECON 2007: 33RD ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, VOLS 1-3, CONFERENCE PROCEEDINGS, 2007, : 2870 - 2875
  • [9] Design and analysis of welding inspection robot
    Zhang, Pengyu
    Wang, Ji
    Zhang, Feng
    Xu, Peiquan
    Li, Leijun
    Li, Baoming
    SCIENTIFIC REPORTS, 2022, 12 (01)
  • [10] Drain Structural Defect Detection and Mapping Using AI-Enabled Reconfigurable Robot Raptor and IoRT Framework
    Palanisamy, Povendhan
    Mohan, Rajesh Elara
    Semwal, Archana
    Melivin, Lee Ming Jun
    Gomez, Braulio Felix
    Balakrishnan, Selvasundari
    Elangovan, Karthikeyan
    Ramalingam, Balakrishnan
    Terntzer, Dylan Ng
    SENSORS, 2021, 21 (21)