本文介绍了用于自动赛车的多层运动计划和控制架构，能够避免静态障碍，进行主动超越并达到75 $ m/s $以上的速度。使用的脱机全局轨迹生成和在线模型预测控制器高度基于车辆的优化和动态模型，在该模型中，在基本的Pacejka Magic公式的扩展版本中，轮胎和弯曲效果表示。使用多体汽车运动库鉴定并验证了所提出的单轨模型，这些模型允许正确模拟车辆动力学，在丢失实际实验数据时尤其有用。调整了控制器的基本正规化项和约束，以降低输入的变化速率，同时确保可接受的速度和路径跟踪。运动计划策略由一个基于Fren \'ET框架的计划者组成，该计划者考虑了Kalman过滤器产生的对手的预测。策划者选择了无碰撞路径和速度轮廓要在3秒钟的视野中跟踪，以实现不同的目标，例如跟随和超车。该提议的解决方案已应用于达拉拉AV-21赛车，并在椭圆形赛道上进行了测试，可实现高达25 $ m/s^{2} $的横向加速度。

The preservation, monitoring, and control of water resources has been a major challenge in recent decades. Water resources must be constantly monitored to know the contamination levels of water. To meet this objective, this paper proposes a water monitoring system using autonomous surface vehicles, equipped with water quality sensors, based on a multimodal particle swarm optimization, and the federated learning technique, with Gaussian process as a surrogate model, the AquaFeL-PSO algorithm. The proposed monitoring system has two phases, the exploration phase and the exploitation phase. In the exploration phase, the vehicles examine the surface of the water resource, and with the data acquired by the water quality sensors, a first water quality model is estimated in the central server. In the exploitation phase, the area is divided into action zones using the model estimated in the exploration phase for a better exploitation of the contamination zones. To obtain the final water quality model of the water resource, the models obtained in both phases are combined. The results demonstrate the efficiency of the proposed path planner in obtaining water quality models of the pollution zones, with a 14$\%$ improvement over the other path planners compared, and the entire water resource, obtaining a 400$\%$ better model, as well as in detecting pollution peaks, the improvement in this case study is 4,000$\%$. It was also proven that the results obtained by applying the federated learning technique are very similar to the results of a centralized system.

监测和检测鱼类行为提供有关鱼类福利的基本信息，并有助于实现全球水产养殖中的智能制作。这项工作提出了一种有效的方法，分析了三个袜子密度（1,5和10个个人/水族馆）在水族馆维护的少年小丑鱼（Amphiprion Bicinctus）的空间分布状态和运动模式。估计的位移是评估分散和速度的关键因素，以表达在再循环水产养殖系统中表达小丑鱼的空间分布和运动行为的关键因素。实际上，我们的目标是使用光学流动方法计算速度，幅度和转动角度，以帮助水平养殖者有效地监测和识别鱼类行为。我们在包含在水族馆维护的少年小丑鱼视频流的数据库上测试系统设计。所提出的位移估计揭示了测量小丑鱼运动和色散特征的良好性能。此外，我们展示了提出的技术来定量在早上和下午拍摄的录音之间的小丑鱼活动水平变化的有效性。