Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Combined grid and heat conduction optimization for staircase cleaning robot path planning
Abstract 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.
Highlights Presenting a reconfigurable cleaning robot with descent and ascent motions on staircase. A hybrid path planning method combining heat conduction with grid-based optimization. The presented multi-objective optimization technique is generic. A validation of path planning on both simulation and real scenario with robot. Path planning is feasible to apply to other reconfigurable robot platforms.
Combined grid and heat conduction optimization for staircase cleaning robot path planning
Abstract 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.
Highlights Presenting a reconfigurable cleaning robot with descent and ascent motions on staircase. A hybrid path planning method combining heat conduction with grid-based optimization. The presented multi-objective optimization technique is generic. A validation of path planning on both simulation and real scenario with robot. Path planning is feasible to apply to other reconfigurable robot platforms.
Combined grid and heat conduction optimization for staircase cleaning robot path planning
Do, Huy (Autor:in) / Veerajagadeshwar, Prabahar (Autor:in) / Sun, Fangbin (Autor:in) / Guo, Yujie (Autor:in) / Le, Anh Vu (Autor:in) / Weeger, Oliver (Autor:in) / Mohan, Rajesh Elara (Autor:in) / Nhan, Nguyen Huu Khanh (Autor:in) / Van Duc, Phan (Autor:in) / Vu, Minh Bui (Autor:in)
19.06.2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Mobile robot path planning algorithm by equivalent conduction heat flow topology optimization
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