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I am reviewing some CoRL (Conf. on Robot learning) and Humanoids papers (6 papers total). None of them are reporting tests with a real robot (only simulation) => When did the robotics community stop caring about actual robots? these papers should be submitted to SIGGRAPH!
I disagree. There are now realistic large scale simulation tools that enable us to experiment in a completely different way compared to getting measurements with a real robot. algorithmic questions on how to design robust sample-efficient interactive learning is best studied here
Siggraph would be a terrible fit for such papers. The emphasis there is on visual appeal not on learning algorithms or physically valid simulations. Robotics community needs to treat simulations as a core topic
I would love to have more papers about better simulations of robots, especially if there is some data to compare them to the reality!
First, none of these papers is using "realistic large scale simulations". Most of them are using the "mujoco tasks" with only a few dof, no environment and no realistic actuator/sensor. Second, I love simulations as tools, but the results should still be validated in reality.
Asking one research team to do is not fair. Focus on scientific contributions of the paper rather than a strict rule that all papers should be on a real robot. good algorithmic development it should be accepted. That's how we enable interdisciplinary research in robotics.
By first limiting to simulations we democratize robotics research to a broader community. We can focus on design and analysis of learning algorithms. These simulations are much closer to real systems as opposed to idiotic atari games that have no real world impact
When it comes to simulation engines, there needs to be a fine balance especially when including simulation of complex systems I.e. the real world. We learnt the hard way that uncertainty induced and propagated from assumptions render the good results as mere coincidence! 1/2
This is especially true when the simulation engines are multi-step and observational constraints are also varying across the multi-steps. Simulation systems no matter how complex work best as scenario generators which I think is akin to what you are describing। My Two cents. 2/2
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