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.
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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 inclu...
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