State of Robot Learning, December 2025

State of Robot Learning, December 2025

State of Robot Learning, December 2025 State of Robot Learning — December 2025 Basically all robot learning systems today (December, 2025) are pure Behavior Cloning (BC, also called Imitation Learning) systems. Humans provide (near) optimal demonstrations of a task, and machine learning models try to imitate those actions. Formally, a policy is trained in a supervised fashion — given the robot’s state (i.e. the camera images, robot joint angles, and maybe task description text), predicts the demonstrated actions (often an action chunk , e.g. the next second of ~50hz). This doc aims to describe

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• Elizabeth Qiu
• HudZah
• Blake Dee
• Shiza Charania
• Donald
• Dhruv Sheth
• Alex K

related reading

• Behavioral cloning mysteryseohong.me
• Generalist - GEN-0 / Embodied Foundation Models That Scale with Physical Interactiongeneralistai.com
• Supervised Policy Learning for Real Robotssupervised-robot-learning.github.io
• Emergence of Human to Robot Transfer in Vision-Language-Action Modelspi.website
• [2607.15275] RoboTTT: Context Scaling for Robot Policiesarxiv.org
• A Unified Model for Motion-Conditioned Robot Co-designtransformer-transformer.github.io
• Ch. 21 - Imitation Learningunderactuated.mit.edu
• Scalable Behavior Cloning with Open Data, Training, and Evaluationabc.bot
• What Do Robotics Leaderboards Tell Us About The State of Robot Learning?itcanthink.substack.com
• GitHub - adam-maj/robotics: A deep dive on the history of robotics and the future of humanoidsgithub.com
• How do We Quantify Progress in Robotics? - by Chris Paxtonitcanthink.substack.com
• Frontier of General-Purpose Robotics (2025)adampatni.com