Few-Shot Goal Inference for Visuomotor Learning and Planning

Understand

Reinforcement learning and planning methods require an objective or reward function that encodes the desired behavior.

• Yet, in practice, there is a wide range of scenarios where an objective is difficult to provide programmatically, such as tasks with visual observations involving unknown object positions or deformable objects.
• In these cases, prior methods use engineered problem-specific solutions, e.g., by instrumenting the environment with additional sensors to measure a proxy for the objective.
• Such solutions require a significant engineering effort on a per-task basis, and make it impractical for robots to continuously learn complex skills outside of laboratory settings.