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Abstract Complete area-coverage path planners are essential for robots performing tasks like cleaning, inspection, and surveying. However, they often involve complex calculations, mapping, and determining movement directions, leading to high computational or processing overheads and the risk of deadlocks. This paper proposes an approach for cleaning, i.e., by linear wiping of generic and discontinuous surfaces in hospital settings using inhouse assembled mobile dual-arm (MDA) robotic system. The proposed framework introduces key features: (a) a less resource-intensive approach for MDA positioning and cleaning surface mapping, (b) Modified Glasius Bioinspired Neural Network through use of heuristics (GBNN+H) to optimize surface linear wiping while obstacle avoidance, and traversal across discontinuous surfaces. The advantages of the proposed algorithm are highlighted in simulation with GBNN+H significantly reduces the number of steps and flight time required for complete coverage compared to existing algorithms. The proposed framework is also experimentally demonstrated in a hospital setting, paving the way for improved automation in cleaning and disinfection tasks. Overall, this work presents a generic and versatile, applicable to various surface orientations and complexities.

Robots have been reportedly seen serving food in several restaurants in many parts of the world. New ventures have been deploying mechanical partners which promote the growth in service robotics. However, robots are considerably incompetent when it comes to beverage and soup delivery. The physical challenge behind the clumsy motion of these machines is found to be its jerky motion control. Jerk control solutions are widely studied in a constrained environment but not well introduced in dynamic environments. In this paper, we will begin by examining developed kinematics solutions, open-source packages from Robot Operating System and the constraints of motion planning. The proposed solution in this paper provides a quick system response with jerk limits using spline velocity profiles. The solution will introduce the concepts of a state machine design that enables the robot to behave and move reactively; effectively balancing its desired velocity and position without spilling a drop of customer satisfaction. Experiments have proven that robots can move at higher velocity without any crashing, spilling, or docking issues. The smooth velocity control proposed will improve the capabilities of waiter robot and service operations in restaurants.