## 1 Introduction
For Instance, Reference [11] presented a novel grid-based coverage approach where they considered time and energy as critical parameters to reduce directional constraints on path generation. The proposed approach was validated by benchmarking its performance to a conventional coverage scheme with respect to energy and time. In another grid-based coverage work, [PERSON] et al. [12] proposed a novel grid pattern where they used triangular cells instead of rectangular cells for efficient and faster navigation in cleaning robots. The efficiency of the proposed algorithm was validated through simulated experiments. Coverage task with multi-robot scenarios have a higher advantage by utilizing coverage path planning algorithm. For multi-robot coverage, [PERSON] et al. proposed multi-robot area coverage approach for a scenario in which a map is known with the minimum visibility range [13]. In this work, author initially locates the beacons in a known map to create a graph then they convert the generated graph into a forest of partial spanning tree (PST). The converted PST is then built as cycles which is then assigned to each robot for coverage. In an another multi-robot coverage work, [PERSON] and [PERSON] proposed a bio-inspired neural network approach for robots operating in a time-varying and unstructured environment [14]. The prosed model will generate the shunting neural equation which provides the path for each robot through dynamic activity landscape for efficient coverage. Author claims the proposed method is computationally efficient than traditional methods. Although numerous methods in coverage path planning have been proposed and demonstrates its significant in area coverage task, they are largely tested with fixed morphological robots. None of the previous works in coverage path planning was applied or proposed specifically for robots with shapeshifting capability. The reconfigurable mechanism is well studied and were actively applied to robotics platforms since 1980. Such efforts later translated to a number of reconfigurable robotic platforms that has been proposed. So far in the field of reconfigurable robots, three different architectures were proposed, namely, intra-reconfiguration, inter-reconfiguration and nested reconfiguration. Intra-reconfiguration deals with a single robotic system that could change its morphology by its own without any external supports. For instance, a versatile robot that could change its morphology from amphibious and terrestrial gait mechanism [15], a reconfigurable Janson mechanic robot that could generate a variety of gait patterns [16] and a bio-inspired crawling, rolling, climbing reconfigurable robot. Robots that was proposed under the inter-reconfigurable principle are basically modular robots that could possess different morphologies by undergoing assembling and disassembling process. One such example is Sambot [17], which can assume morphologies by attaching and detaching with multiple similar robots. CEBOT, Poly Bot, Crystalline, M-TRAN, ATRON, Molecube and CKBot are other relevant examples of inter-reconfigurable robots. The third architecture category in reconfigurable systems is Nest reconfiguration which is capable of performing both inter and intra reconfigurations. Hinged Tetro present in Reference [18], is the only such nested reconfigurable robot which is capable of switching between forms and could change its morphology by undergoing assembling and disassembling with peer robots. In spite of the fact that numerous studies in the literature address reconfigurable robotics, they are primarily limited to mechanism design and were never implemented to an area coverage task like floor cleaning. Also, none of the previous work in reconfigurable robot was validated with coverage path planning technique. To this end, in our previous work, we presented a novel reconfigurable floor cleaning robot called hTetro that can able to change its morphology to any of the one-sided Tetris pieces [19; 20].