Abstract
In this study, we aim to optimize and improve the efficiency of a Tetris-inspired reconfigurable cleaning robot. Multi-criteria decision making (MCDM) is utilized as a powerful tool to target this aim by introducing the best solution among others in terms of lower energy consumption and greater area coverage. Regarding the Tetris-inspired structure, polyomino tiling theory is utilized to generate tiling path-planning maps which are evaluated via MCDM to seek a solution that can deliver the best balance between the two mentioned key issues; energy and area coverage. In order to obtain a tiling area that better meets the requirements of polyomino tiling theorems, first, the whole area is decomposed into five smaller sub-areas based on furniture layout. Afterward, four tetromino tiling theorems are applied to each sub-area to give the tiling sets that govern the robot navigation strategy in terms of shape-shifting tiles. Then, the area coverage and energy consumption are calculated and eventually, these key values are considered as the decision criteria in a MCDM process to select the best tiling set in each sub-area, and following the aggregation of best tiling path-plannings, the robot navigation is oriented towards efficiency and improved optimality. Also, for each sub-area, a preference order for the tiling sets is put forward. Based on simulation results, the tiling theorem that can best serve all sub-areas turns out to be the same. Moreover, a comparison between a fixed-morphology mechanism with the current approach further advocates the proposed technique.
Highlights
Robots are deployed in a wide range of applications and are, rapidly becoming an integral component of our everyday life
In pursuance of [14], this paper utilizes the polyomino tiling theory to propose tiling sets as navigation strategies of the Tetris-inspired cleaning robot in a static environment but goes a step further to definitively select the optimal tiling set for each area under cleaning
In our previous experiments on shape-shifting cleaning robots, we only considered area coverage as a single parameter for assessing the robot’s performance, which is insufficient when the robot is functioning in real-time scenarios [13,14]
Summary
Robots are deployed in a wide range of applications and are, rapidly becoming an integral component of our everyday life. In pursuance of [14], this paper utilizes the polyomino tiling theory to propose tiling sets as navigation strategies of the Tetris-inspired cleaning robot in a static environment but goes a step further to definitively select the optimal tiling set for each area under cleaning This will suggest the navigation strategy that improves the overall efficiency from the viewpoint of area and energy. In this study, we consider these two key factors as decision criteria in a Multi-Criteria Decision Making (MCDM) process in order to choose the best navigation strategy (defined by the tiling set) for achieving higher efficiency in terms of less energy with superior area coverage.
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