Combined grid and heat conduction optimization for staircase cleaning robot path planning

Staircase climbing, particularly in complex environments of multi-storey buildings, is a challenging task for robotics. By leveraging the similarities between robot path planning and heat conduction, this paper presents a novel path planning to direct with optimal energy consumption the self-reconfigurable staircase cleaning robot called sTetro, able to transform its shape to perform both descent and ascent motions on the staircase. Finding optimal path is modeled as heat traveling between heat source and heat sink through thermal conductive materials. We utilize the temperature gradient on grid-based optimization method to search for optimal paths by minimizing path length and energy consumption. The proposed path planning method successfully applies to six virtual environments with various obstacle placements. Additionally, validation tests on a real sTetro robot in 2 real staircase scenarios show that the energy consumption of the optimized paths from the proposed method is about 21% lower than that from conventional methods.