Turn and orientation Sensitive A* for Autonomous Vehicles in Intelligent Material Handling Systems

A Survey on Navigation Approaches for Automated Guided Vehicle Robots in Dynamic Surrounding

“…While Chui et al [68] and Wang et al [69] proposing an improve A* algorithm based on time-window to solve conflictfree in path planning problem for AGV. Next, Yang et al [70] and Ballamajalu et al [71] simulated the A* search method by applying in real warehouse application for materials handling. While, Chen et al [72] proposing a two-stage congestion-aware routing strategy based on A* algorithm.…”

“…To find the lowest-cost path in a geometric graph Proposed algorithm successful selfconfiguring based on the graph and parameters such as turning costs Zheng et al [66] Improved A* To quickly find the optimal path for AGV Success to search the optimal path and path search speed is faster than traditional A* Zhang et al [67] Improved A* To optimize the motion path, reduction of path length, number of AGV turns and path planning time Success to provide efficient path planning with shorter routes, less turn times and shorter operation time compared with traditional A* algorithm and ACO Cui et al [68] Improved A* To solve the conflict-free in AGV path planning problem Success to speed up the path searching process Li et al [69] Improved A* To eliminate the limitation of node movement direction in traditional A* algorithm Success to simulate the working security and efficiency of mobile robot compared to traditional A* Yang et al [70] Improved A* To avoid collisions and search the idle path Success to simulated effectively schedules in the warehouse with lower time complexity for multi-AGV Ballamajalu et al [71] A*…”