「简报」化学大四学生 Frank Hu 获得了匹兹堡分析化学家协会奖；机器人专家开始编制可以用于训练自动驾驶 ATV 的数据

卡耐基梅隆大学的研究人员驾驶着一辆全地形车，穿越了高高的草丛，松散的砾石和泥浆，以收集有关 ATV 如何与具有挑战性的越野环境交互的数据。

生成的数据集被称为 TartanDrive，包含了大约 200,000 个真实世界的交互。研究人员认为，就交互数量和传感器类型而言，这些数据是现实世界中最大的多模式越野驾驶数据集。这五个小时的数据可能有助于训练自动驾驶汽车在越野中的导航。

了解更多:

https://www.cs.cmu.edu/news/2022/tartandrive

Researchers from Carnegie Mellon University took an all-terrain vehicle on wild rides through tall grass, loose gravel and mud to gather data about how the ATV interacted with a challenging, off-road environment.

The resulting dataset, called TartanDrive, includes about 200,000 of these real-world interactions. The researchers believe the data is the largest real-world, multimodal, off-road driving dataset, both in terms of the number of interactions and types of sensors. The five hours of data could be useful for training a self-driving vehicle to navigate off road.

Learn More: 

https://www.cs.cmu.edu/news/2022/tartandrive

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