Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents an improved path planning algorithm to avoid obstacles of critical shapes (obstacles having angles of around 90°). The proposed algorithm outperforms the reported bug algorithms by reaching the target safely in relatively less time and avoiding multiple obstacles without suffering into local minima. The main reason of such improvement is to schedule the speed and direction of the agent according to the edges of obstacles. More specifically, the agent's speed is set as a function of goal and the obstacle location. The direction to follow obstacle edges is not predefined, but generated online by taking the dot product beten obstacle edges and the target behavior. In this way the optimal path can be achieved to reach the final target with safe, smooth and short trajectory. Simulation results and practical implementation validated the effectiveness of our proposed algorithm. Moreover, performance comparison of the proposed algorithm and other approaches confirms the efficiency of the presented approach.
['Muhammad Majid Gulzar', 'Qiang Ling', 'Muhammad Yaqoob', 'Sajid Iqbal']
I am writing a research paper on a idea Realization of an improved path planning strategy
[{"from": "human", "value": "I am writing a research paper on a idea Realization of an improved path planning strategy"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents an improved path planning algorithm to avoid obstacles of critical shapes (obstacles having angles of around 90\u00b0). The proposed algorithm outperforms the reported bug algorithms by reaching the target safely in relatively less time and avoiding multiple obstacles without suffering into local minima. The main reason of such improvement is to schedule the speed and direction of the agent according to the edges of obstacles. More specifically, the agent's speed is set as a function of goal and the obstacle location. The direction to follow obstacle edges is not predefined, but generated online by taking the dot product beten obstacle edges and the target behavior. In this way the optimal path can be achieved to reach the final target with safe, smooth and short trajectory. Simulation results and practical implementation validated the effectiveness of our proposed algorithm. Moreover, performance comparison of the proposed algorithm and other approaches confirms the efficiency of the presented approach."}]