This paper proposes an online path planning method for multi-robot collision avoidance that accounts for uncertainties in robot positioning. Firstly, the online path planning problem for multiple robots is transformed...
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ISBN:
(纸本)9798331518509;9798331518493
This paper proposes an online path planning method for multi-robot collision avoidance that accounts for uncertainties in robot positioning. Firstly, the online path planning problem for multiple robots is transformed into a multi-objective optimization problem by considering some necessary factors that affect task efficiency and safety. Notably, the paper considers the uncertainty in robot positions, in which the position follows a Gaussian distribution. Then, by converting probabilistic collision conditions into deterministic constraints, the fitness function ensuring probabilistic collision avoidance is constructed. Next, an improvedsine-cosine algorithm is proposed to solve the ideal position. Finally, simulation experiments demonstrate that the proposed method effectively resolves collision issues under probabilistic uncertainty conditions.
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