1 citations · 1 across the 5 of their papers we have counts for
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SAS-Prompt: Large Language Models as Numerical Optimizers for Robot Self-Improvement
Heni Ben Amor, Laura Graesser, Atil Iscen +7
We demonstrate the ability of large language models (LLMs) to perform iterative self-improvement of robot policies. An important insight of this paper is that LLMs have a built-in…
Enabling Stateful Behaviors for Diffusion-based Policy Learning
Xiao Liu, Fabian Weigend, Yifan Zhou +1
While imitation learning provides a simple and effective framework for policy learning, acquiring consistent actions during robot execution remains a challenging task. Existing app…
Projecting Robot Intentions Through Visual Cues: Static vs. Dynamic Signaling
Shubham Sonawani, Yifan Zhou, Heni Ben Amor
Augmented and mixed-reality techniques harbor a great potential for improving human-robot collaboration. Visual signals and cues may be projected to a human partner in order to exp…
Imitation Learning based Auto-Correction of Extrinsic Parameters for A Mixed-Reality Setup
Shubham Sonawani, Yifan Zhou, Heni Ben Amor
In this paper, we discuss an imitation learning based method for reducing the calibration error for a mixed reality system consisting of a vision sensor and a projector. Unlike a h…