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Reconfigurable robots are deployed for applications demanding area coverage, such as cleaning and inspections. Reconfiguration per context, considering beyond a small set of predefined shapes, is crucial for area coverage performance. However, the existing area coverage methods of reconfigurable robots are not always effective and require improvements for ascertaining the intended goal. Therefore, this article proposes a novel coverage strategy based on internal rehearsals to improve the area coverage performance of a reconfigurable robot. In this regard, a reconfigurable robot is embodied with the cognitive ability to predict the outcomes of its actions before executing them. A genetic algorithm uses the results of the internal rehearsals to determine a set of the robot's coverage parameters, including positioning, heading, and reconfiguration, to maximize coverage in an obstacle cluster encountered by the robot. The experimental results confirm that the proposed method can significantly improve the area coverage performance of a reconfigurable robot. [ABSTRACT FROM AUTHOR]

As autonomous cleaning robots advance, we expect certain features, such as higher area coverage and robustness. To explore these features and their challenges, we need tools and strategies that allow us to develop them rapidly. In this paper, we present lessons learned and results while performing 3 months long field trials on the autonomy of a self‐reconfigurable floor‐cleaning robot. The autonomy here includes path planning and navigation of the robot for coverage in a public food court. The environment of the food court is often subjected to alterations due to human activities. One of the main contributions of this paper is proposing a task‐level execution system to deploy the cleaning robot in an actual use case scenario. We also provide in‐depth discussions on the solutions and the implementation strategies we found in accomplishing goals. These findings would be helpful in conducting autonomy development targeted for field deployments of self‐reconfigurable robots and cleaning robots. [ABSTRACT FROM AUTHOR]