Topic: sim-to-real

Ai2's Robotics team is hiring a research scientist to investigate foundation models for robotics and develop open methods, datasets, benchmarks, and models. The work combines large-scale simulation with real robots, spanning manipulation, planning and control, reinforcement or imitation learning, sim-to-real transfer, world models, and broadly competent robotic systems.

Artifical neural network (ANN) approaches to motor control commonly adopt generic architectures like fully connected multi-layer perceptrons (MLPs) and recurrent neural networks (RNNs). As such architectures contain few inductive biases, it is common to require priors in the form of rewards, training curricula, imitation data, or trajectory generators. In nature, animals are born with priors in the form of their nervous system's architecture, which has been shaped by evolution to confer innate ability and efficient learning. For instance, a horse can walk within hours of birth and quickly impr