Path planning of a mobile robot in the presence of multiple moving obstacles is found to be a complicated problem.A planning algorithm capable of negotiating both static and moving obstacles in an unpredictable(on-lin...Path planning of a mobile robot in the presence of multiple moving obstacles is found to be a complicated problem.A planning algorithm capable of negotiating both static and moving obstacles in an unpredictable(on-line)environment is proposed.The proposed incremental algorithm plans the path by considering the quadrants in which the current positions of obstacles as well as target are situated.Also,the governing equations for the shortest path are derived.The proposed mathematical model describes the motion(satisfying constraints of the mobile robot)along a collision-free path.Further,the algorithm is applicable to dynamic environments with fixed or moving targets.Simulation results show the effectiveness of the proposed algorithm.Comparison of results with the improved artificial potential field(iAPF)algorithm shows that the proposed algorithm yields shorter path length with less computation time.展开更多
文摘Path planning of a mobile robot in the presence of multiple moving obstacles is found to be a complicated problem.A planning algorithm capable of negotiating both static and moving obstacles in an unpredictable(on-line)environment is proposed.The proposed incremental algorithm plans the path by considering the quadrants in which the current positions of obstacles as well as target are situated.Also,the governing equations for the shortest path are derived.The proposed mathematical model describes the motion(satisfying constraints of the mobile robot)along a collision-free path.Further,the algorithm is applicable to dynamic environments with fixed or moving targets.Simulation results show the effectiveness of the proposed algorithm.Comparison of results with the improved artificial potential field(iAPF)algorithm shows that the proposed algorithm yields shorter path length with less computation time.
