Search Results for author:
Found 8 papers, 4 papers with code
Learning General-Purpose Controllers via Locally Communicating Sensorimotor Modules
We observe a wide variety of drastically diverse locomotion styles across morphologies as well as centralized coordination emerging via message passing between decentralized modules purely from the reinforcement learning objective.
VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models
The composed value maps are then used in a model-based planning framework to zero-shot synthesize closed-loop robot trajectories with robustness to dynamic perturbations.
PaLM-E: An Embodied Multimodal Language Model
Large language models excel at a wide range of complex tasks.
Ranked #2 on
Visual Question Answering (VQA)
on OK-VQA
Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents
Recent progress in large language models (LLMs) has demonstrated the ability to learn and leverage Internet-scale knowledge through pre-training with autoregressive models.
Inner Monologue: Embodied Reasoning through Planning with Language Models
We investigate a variety of sources of feedback, such as success detection, scene description, and human interaction.
Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents
However, the plans produced naively by LLMs often cannot map precisely to admissible actions.
Generalization in Dexterous Manipulation via Geometry-Aware Multi-Task Learning
We show that a single generalist policy can perform in-hand manipulation of over 100 geometrically-diverse real-world objects and generalize to new objects with unseen shape or size.
One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control
We observe that a wide variety of drastically diverse locomotion styles across morphologies as well as centralized coordination emerges via message passing between decentralized modules purely from the reinforcement learning objective.
