论文标题
眼镜蛇：机器人应用程序的合成基准
CoBRA: A Composable Benchmark for Robotics Applications
论文作者
论文摘要
当前，选择一个最佳机器人，其基本姿势和针对给定任务的轨迹主要是由人类专业知识或反复试验完成的。为了评估此组合优化问题的自动方法，我们引入了一个基准套件，其中包含用于机器人，环境和任务描述的统一格式。我们的基准套件对于模块化机器人特别有用，可以组装的大量机器人会创建许多其他参数以优化。我们包括在合成环境中的机器倾斜和焊接等任务，以及对现实世界机器的3D扫描。所有基准都可以通过https://cobra.cps.cit.tum.de访问，这是一个方便共享，参考和比较任务，机器人模型和解决方案的平台。
Selecting an optimal robot, its base pose, and trajectory for a given task is currently mainly done by human expertise or trial and error. To evaluate automatic approaches to this combined optimization problem, we introduce a benchmark suite encompassing a unified format for robots, environments, and task descriptions. Our benchmark suite is especially useful for modular robots, where the multitude of robots that can be assembled creates a host of additional parameters to optimize. We include tasks such as machine tending and welding in synthetic environments and 3D scans of real-world machine shops. All benchmarks are accessible through https://cobra.cps.cit.tum.de, a platform to conveniently share, reference, and compare tasks, robot models, and solutions.
