--- title: Robot Learning Landscape emoji: ๐Ÿค– colorFrom: indigo colorTo: purple sdk: gradio sdk_version: 6.14.0 app_file: app.py pinned: false --- # ๐Ÿค– Robot Learning Landscape An interactive map of how robots learn to act โ€” plus an animated unified-model story, a chronological evolution timeline, and focused VLM / world-model views. - **๐ŸŽฌ Unified Story** โ€” a smooth animated walkthrough from classical control to RL/IL, generative action heads, VLM/VLA foundation policies, world models, and the current unified robot-model stack. It includes a 165-paper evidence matrix and source links. - **๐Ÿงช Algorithm Lab** โ€” a synchronized explainer for every Robot, VLM, and World Model landscape node: stepper, animation, formulas, code snippets, and plain-language trace move together, following the DiT / cross-attention explainer style. - **๐Ÿงฌ Contribution Atlas** โ€” an animated, contribution-first history across Robot, VLM, and World Model work: each step shows the prior reference point, the new work, and the smallest conceptual/algorithmic delta that mattered. - **๐ŸŒŒ Landscape** โ€” a constellation of 27 paradigms across 11 families (Behavioral Cloning, Reinforcement Learning, Offline RL, Inverse RL, World Models, Sequence Models, Goal-Conditioned, Hierarchical, Meta-Learning, LLM/VLM, and Classical Control). Click a star for a plain-English explanation, a looping mini-animation of what the robot is doing, the equations (with related equations in its family), how it connects to other methods, and a link to the best explainer. - **โณ Evolution Timeline** โ€” 53 milestones (1922โ€“2025) showing what was developed from what; hover to trace a method's lineage, click any card to read its best explainer. Toggle between the views with the bar at the top.