Path Planning for Navigating Robots Based on Improved Grey Wolf Optimization Algorithm
Path planning is extremely important for navigational robotics,and finding the optimal path allows the robot to avoid obstacles autonomously while improving efficiency and reaching the target location.A path planning method for navigating robots based on an improved grey wolf optimisation algorithm is proposed.The algorithm combines the grey wolf optimisation algorithm with a dimensional learning based information sharing strategy and constraints to achieve excellence in path planning for navigating robots.Then,an experimental study was conducted based on this method,including simulation experiments and real scenario experiments.The experimental results show that the method achieves significant optimisation results in terms of path length,search time and path feasibility.
navigation robotpath planningimproved grey wolf optimisation algorithmconstraints
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