Energy Consumption Estimation Model for Complete Coverage of a Tetromino Inspired Reconfigurable Surface Tiling Robot

被引:26
作者
Manimuthu, Arunmozhi [1 ]
Anh Vu Le [1 ,2 ]
Elara, Mohan Rajesh [1 ]
Veerajagadeshwar, Prabahar [1 ]
Nguyen Huu Khanh Nhan [2 ]
Cheng, Ku Ping [1 ]
机构
[1] Singapore Univ Technol & Design, ROAR Lab, Engn Prod Dev, Singapore 487372, Singapore
[2] Ton Duc Thang Univ, Fac Elect & Elect Engn, Optoelect Res Grp, Ho Chi Minh City 700000, Vietnam
关键词
tiling robotics; reconfigurable system; energy saving; area coverage; reconfigurable mechanism; MOBILE ROBOT; STAYING-ALIVE; ALGORITHMS; DESIGN; SYSTEM;
D O I
10.3390/en12122257
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
As autonomous tiling devices begin to perform floor cleaning, agriculture harvesting, surface painting tasks, with minimal or no human intervention, a new challenge arises: these devices also need to be energy efficient and be constantly aware of the energy expenditure during deployments. Typical approaches to this end are often limited to fixed morphology robots with little or no consideration for reconfiguring class of robots. The main contribution of the paper is an energy estimation scheme that allows estimating the energy consumption when a tetromino inspired reconfigurable floor tiling robot, hTetro moves from one configuration to another for completing the area covering task. To this end, the proposed model applying the Newton-Raphson algorithm in combination with Pulse width modulation (PWM)-H bridge to characterize the energy cost associated with locomotion gaits across all valid morphologies and identify optimal area coverage strategy among available options is presented. We validate our proposed approach using an 8' x 8' square testbed where there exist 12 possible solutions for complete area coverage however with varying levels of energy cost. Then, we implemented our approach to our hTetro platform and conducted experiments in a real-life environment. Experimental results demonstrate the application of our model in identifying the optimal area coverage strategy that has the least associated energy cost.
引用
收藏
页数:18
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