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20192025
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cs.RO2025

SkillBlender: Towards Versatile Humanoid Whole-Body Loco-Manipulation via Skill Blending

Yuxuan Kuang, Haoran Geng, Amine Elhafsi +5

Humanoid robots hold significant potential in accomplishing daily tasks across diverse environments thanks to their flexibility and human-like morphology. Recent works have made si…

cs.RO2025

Scan, Materialize, Simulate: A Generalizable Framework for Physically Grounded Robot Planning

Amine Elhafsi, Daniel Morton, Marco Pavone

Autonomous robots must reason about the physical consequences of their actions to operate effectively in unstructured, real-world environments. We present Scan, Materialize, Simula…

cs.RO2024

Real-Time Anomaly Detection and Reactive Planning with Large Language Models

Rohan Sinha, Amine Elhafsi, Christopher Agia +3

Foundation models, e.g., large language models (LLMs), trained on internet-scale data possess zero-shot generalization capabilities that make them a promising technology towards de…

cs.RO2023

Semantic Anomaly Detection with Large Language Models

Amine Elhafsi, Rohan Sinha, Christopher Agia +3

As robots acquire increasingly sophisticated skills and see increasingly complex and varied environments, the threat of an edge case or anomalous failure is ever present. For examp…

cs.RO2020

MATS: An Interpretable Trajectory Forecasting Representation for Planning and Control

Boris Ivanovic, Amine Elhafsi, Guy Rosman +2

Reasoning about human motion is a core component of modern human-robot interactive systems. In particular, one of the main uses of behavior prediction in autonomous systems is to i…

cs.RO2019

Map-Predictive Motion Planning in Unknown Environments

Amine Elhafsi, Boris Ivanovic, Lucas Janson +1

Algorithms for motion planning in unknown environments are generally limited in their ability to reason about the structure of the unobserved environment. As such, current methods…