Darii, AndreiNistor, Marian SorinPickl, Stefan2025-07-032024DARII, Andrei; Marian Sorin NISTOR and Stefan PICKL. Neuroevolution and NEAT at Evolving Neurocontrollers for Obstacle Avoidance for a Robot Arm. In: International Conference dedicated to the 60th anniversary of the foundation of Vladimir Andrunachievici Institute of Mathematics and Computer Science, MSU, October 10-13 2024. Chisinau: [S. n.], 2024, pp. 280-286. ISBN 978-9975-68-515-3.978-9975-68-515-3https://msuir.usm.md/handle/123456789/18261This paper presents a comparative analysis of Neuroevolution and NEAT algorithms for evolving neural controllers capable of evading obstacles. The fitness criterion is the number of time steps a robot is able to avoid a moving obstacle that increases in speed over time. The experiments simulate the WLkata Mirobot, a small 6-joint robot, focusing on obstacle evasion using forward kinematics. The results show the average number of generations required by each algorithm to achieve a certain fitness and analyze the average fitness per generation. This comparison offers insights into the effectiveness and efficiency of each algorithm in optimising robotic obstacle avoidance.engenetic algorithmneuroevolutionNEATrobot armobstacle avoidanceArticle