RESUMO
In this paper, a novel path planning algorithm with Reinforcement Learning is proposed based on the topological map. The proposed algorithm has a two-level structure. At the first level, the proposed method generates the topological area using the region dynamic growth algorithm based on the grid map. In the next level, the Multi-SARSA method divided into two layers is applied to find a near-optimal global planning path, in which the artificial potential field method, first of all, is used to initialize the first Q table for faster learning speed, and then the second Q table is initialized with the connected domain obtained by topological map, which provides the prior information. A combination of the two algorithms makes the algorithm easier to converge. Simulation experiments for path planning have been executed. The results indicate that the method proposed in this paper can find the optimal path with a shorter path length, which demonstrates the effectiveness of the presented method.
RESUMO
OBJECTIVE: To investigate the characteristics of enhanced brain magnetic resonance imaging (MRI) with gadolinium-DTPA (GD) in patients with multiple sclerosis (MS). METHODS: Brain enhanced MRI were studied in 186 patients with clinically definite multiple sclerosis. 298 MRI enhanced lesions were followed every 4 weeks and the study lasted 3 months to 2 years. RESULTS: Of the 298 enhanced MRI lesions 207 (69.5%) lasted less than 4 weeks, 251 (84.2%) 8 weeks, and 272 (91.3%) 12 weeks. There were 3 lesions lasting more than 2 years. Round, oval, ring form, arcuate, spotty, or irregular MRI GD enhanced lesions were found in our MS data. CONCLUSIONS: Most of the MRI GD enhanced lesions disappear in 4 weeks. Very few can last more than 2 years. So it is necessary to perform the GD enhanced MRI in 4 weeks for studying MS intracranial GD enhanced lesions. The DA enhanced MRI lesions in MS may be round, oval, ring form, arcuate, spotty or irregular.