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Modeling and Assessing of Self-Reconfigurable Cleaning Robot hTetro Based on Energy Consumption

Author

Listed:
  • Abdullah Aamir Hayat

    (Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore)

  • Parasuraman Karthikeyan

    (Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore)

  • Manuel Vega-Heredia

    (Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore)

  • Mohan Rajesh Elara

    (Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore)

Abstract

The autonomous floor-cleaning self-reconfigurable robots have entered into the practical stage by establishing enhanced area coverage over the fixed morphology counterparts. Energy consumption during the self-reconfiguration, i.e., changing the shape of the robot from one form to another, becomes a primary focus in these robots that carry finite energy sources. In this paper, hTetro platform with two hinge dissections namely, Left–Left–Left (LLL) and Left–Left–Right (LLR) are modeled and assessed for the energy consumption during the reconfiguration. The geometry of the two dissections, its workspaces, and the set of inverse kinematics solutions for the seven forms are presented. The inverse dynamics using the Newton–Euler approach was adopted to calculate the wrench, i.e., forces and moments at the hinge joints, and subsequently assess the power consumed during the reconfigurations of two hinge dissections in the simulation. Extensive experiments were performed across the two assembled platforms to estimate the power consumption by logging the current data. The comparison was made with the simulation results. The results are particularly useful in the selection of reconfiguration with minimal energy consumption during the floor cleaning.

Suggested Citation

  • Abdullah Aamir Hayat & Parasuraman Karthikeyan & Manuel Vega-Heredia & Mohan Rajesh Elara, 2019. "Modeling and Assessing of Self-Reconfigurable Cleaning Robot hTetro Based on Energy Consumption," Energies, MDPI, vol. 12(21), pages 1-19, October.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:21:p:4112-:d:281009
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    References listed on IDEAS

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    1. Arunmozhi Manimuthu & Anh Vu Le & Rajesh Elara Mohan & Prabahar Veerajagadeshwar & Nguyen Huu Khanh Nhan & Ku Ping Cheng, 2019. "Energy Consumption Estimation Model for Complete Coverage of a Tetromino Inspired Reconfigurable Surface Tiling Robot," Energies, MDPI, vol. 12(12), pages 1-18, June.
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    Citations

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    Cited by:

    1. Lim Yi & Anh Vu Le & Joel Chan Cheng Hoong & Abdullah Aamir Hayat & Balakrishnan Ramalingam & Rajesh Elara Mohan & Kristor Leong & Karthikeyan Elangovan & Minh Tran & Minh V. Bui & Phan Van Duc, 2022. "Multi-Objective Instantaneous Center of Rotation Optimization Using Sensors Feedback for Navigation in Self-Reconfigurable Pavement Sweeping Robot," Mathematics, MDPI, vol. 10(17), pages 1-22, September.
    2. Manivannan Kalimuthu & Abdullah Aamir Hayat & Thejus Pathmakumar & Mohan Rajesh Elara & Kristin Lee Wood, 2023. "A Deep Reinforcement Learning Approach to Optimal Morphologies Generation in Reconfigurable Tiling Robots," Mathematics, MDPI, vol. 11(18), pages 1-22, September.
    3. Manivannan Kalimuthu & Thejus Pathmakumar & Abdullah Aamir Hayat & Prabakaran Veerajagadheswar & Mohan Rajesh Elara & Kristin Lee Wood, 2023. "Optimal Morphologies of n-Omino-Based Reconfigurable Robot for Area Coverage Task Using Metaheuristic Optimization," Mathematics, MDPI, vol. 11(4), pages 1-23, February.

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