CoRL

The Conference on Robot Learning, a yearly peer-reviewed meeting for work that uses machine learningmachine learning, n.: A way of building software that learns from examples instead of following rules written by a programmer. Shown thousands of labeled photos, for instance, a program can learn to recognize cats. to make robots perceive and act, covering robot learningrobot learning, n.: Teaching robots skills from data and experience, such as watching demonstrations, practicing by trial and error or training in simulation, instead of programming every movement by hand., imitation learningimitation learning, n.: Teaching an AI by showing it examples of an expert doing a task, so it learns to copy the behavior instead of discovering it through trial and error., reinforcement learningreinforcement learning, n.: A way of teaching a computer program by trial and error: it tries actions, earns points for good results and penalties for bad ones, and gradually learns which choices pay off over time. for control, perception for manipulation and locomotion, sim-to-real transfersim-to-real transfer, n.: Training a robot's AI in a computer simulation, where practice is fast, cheap and safe, and then making it work on the real robot despite the differences between simulation and reality. and, increasingly, robot foundation modelsrobot foundation model, n.: One large AI model trained on huge amounts of robot and internet data so that it can control many robots on many tasks, and be adapted quickly to new ones. and vision-language-action modelsvision-language-action model, n.: An AI model that looks through a robot's cameras, reads an instruction such as 'put the cup in the sink', and turns both straight into the robot's movements.. It was created because robot-learning papers fit poorly both in traditional robotics conferences such as ICRAICRA, prop. n.: The largest yearly robotics conference, run by the engineering society IEEE, covering everything from robot arms and drones to self-driving cars., which emphasize systems, and in machine learning conferences, which emphasize benchmarks. Its papers are published in the Proceedings of Machine Learning Research, and it has grown rapidly with the rise of learning-based robotics.