Akademik Veri Yönetim Sistemi
9th International Conference on Natural and Engineering Sciences (ICNES 2024), Siirt, Türkiye, 22 - 24 Kasım 2024, ss.112-113, (Özet Bildiri)
Navigating complex and uneven terrains efficiently is a critical challenge for autonomous mobile robots, particularly when vertical displacement and energy efficiency are prioritized. Conventional 2D motion planning algorithms often overlook the effects of terrain slope, leading to paths that underestimate the additional effort needed to traverse steep inclines. This paper introduces a new slope-aware motion planning algorithm, incorporating a cost function that reduces both path length and energy expenditure by factoring in terrain slopes. The algorithm was tested across various 3D terrains, including single-peak, multi-peak, and randomized landscapes. Simulation results highlight the algorithm's capability to generate paths that circumvent steep areas, balancing energy efficiency with optimal coverage. Comparisons between the slope-aware approach and traditional planning methods reveal substantial reductions in energy use, enabling the robot to navigate difficult terrains with minimal energy expenditure. This method shows strong potential for autonomous navigation applications in fields like search and rescue, agricultural robotics, and planetary exploration, where energy conservation is essential. Our motion planning approach leverages pre-existing slope data from a 3D terrain map, enabling the robot to evaluate slopes between its current position and potential next moves. This slope information is integrated into a cost function designed to minimize both travel distance and the effort required to navigate sloped regions. The ultimate objective is for the robot to efficiently cover all grid cells while minimizing repeated passes and overall energy usage.
Keywords: Terrain map;Boustrophedon;Trajectory planning