Task and motion planning with large language models for object rearrangement
Multi-object rearrangement is a crucial skill for service robots, and commonsense reasoning
is frequently needed in this process. However, achieving commonsense arrangements …
is frequently needed in this process. However, achieving commonsense arrangements …
Skill transformer: A monolithic policy for mobile manipulation
Abstract We present Skill Transformer, an approach for solving long-horizon robotic tasks by
combining conditional sequence modeling and skill modularity. Conditioned on egocentric …
combining conditional sequence modeling and skill modularity. Conditioned on egocentric …
Large language models as generalizable policies for embodied tasks
We show that large language models (LLMs) can be adapted to be generalizable policies
for embodied visual tasks. Our approach, called Large LAnguage model Reinforcement …
for embodied visual tasks. Our approach, called Large LAnguage model Reinforcement …
Galactic: Scaling end-to-end reinforcement learning for rearrangement at 100k steps-per-second
We present Galactic, a large-scale simulation and reinforcement-learning (RL) framework for
robotic mobile manipulation in indoor environments. Specifically, a Fetch robot (equipped …
robotic mobile manipulation in indoor environments. Specifically, a Fetch robot (equipped …
Adaptive coordination in social embodied rearrangement
We present the task of" Social Rearrangement", consisting of cooperative everyday tasks
like setting up the dinner table, tidying a house or unpacking groceries in a simulated multi …
like setting up the dinner table, tidying a house or unpacking groceries in a simulated multi …
NEWTON: Are large language models capable of physical reasoning?
Large Language Models (LLMs), through their contextualized representations, have been
empirically proven to encapsulate syntactic, semantic, word sense, and common-sense …
empirically proven to encapsulate syntactic, semantic, word sense, and common-sense …
Leveraging commonsense knowledge from large language models for task and motion planning
Multi-object rearrangement is a crucial skill for service robots, and commonsense reasoning
is frequently needed in this process. However, achieving commonsense arrangements …
is frequently needed in this process. However, achieving commonsense arrangements …
Reinforcement Learning via Auxiliary Task Distillation
Abstract We present Reinforcement Learning via Auxiliary Task Distillation (AuxDistill), a
new method that enables reinforcement learning (RL) to perform long-horizon robot control …
new method that enables reinforcement learning (RL) to perform long-horizon robot control …
Enhanced Robot Navigation with Human Geometric Instruction
Recently, robot navigation methods using human instructions have been actively studied,
including visual language navigation. Although language is one of the most promising forms …
including visual language navigation. Although language is one of the most promising forms …
Grounding Multimodal Large Language Models in Actions
Multimodal Large Language Models (MLLMs) have demonstrated a wide range of
capabilities across many domains, including Embodied AI. In this work, we study how to best …
capabilities across many domains, including Embodied AI. In this work, we study how to best …