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title
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Iterative Keypoint Reward: Multi-Step Robotic Manipulation through Real-to-Sim-to-Real
image
site name
author
updated
2026-02-24 11:30:34
raw text
Iterative Keypoint Reward: Multi-Step Robotic Manipulation through Real-to-Sim-to-Real A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Shivansh Patel 1* , Xinchen Yin 1* , Wenlong Huang 2 , Shubham Garg 3 , Hooshang Nayyeri 3 , Li Fei-Fei 2 , Svetlana Lazebnik 1 , Yunzhu Li 4 1 University of Illinois at Urbana-Champaign, 2 Stanford University, 3 Amazon, 4 Columbia University * indicates equal contributions Paper Abstract Task specification for robotic manipulation in open-world environments is inherently challenging. Importantly, this process requires flexible and adaptive objectives that align with human intentions and can evolve through iterative feedback. We introduce Iterative Keypoint Reward (IKER), a framework that leverages VLMs to generate and refine visually grounded reward functions serving as dynamic task ...
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