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A multi‐objective approach for local path planning of autonomous mobile robot based on metaheuristics

The traditional methods of mobile robot (MR) path planning very often fail in finding the optimal path in a cluttered, complex, and unknown environment. Therefore, in this article, a novel constrained multi‐objective function involving route length, smoothness of the path, and path safety is formulated for a disc‐shaped MR integrated with sensors. The imposed constraints to the problem are the size of the robot and the collision‐free path. A new population‐based algorithm called the chemical reaction optimization algorithm is used to solve the path planning problem. The results obtained through the proposed controller are compared with the results of other methods available in the literature. To demonstrate the effectiveness and usefulness of the proposed algorithm in finding the solution to the path planning problem, statistically significant tests, that is, the coefficient of variation analysis and Friedman's test are conducted. It is observed that the proposed method outperforms the state‐of‐the‐art methods in terms of route length, path smoothness, average sensing, and planning time, and time is taken to reach the goal.