Enhancing human–robot communication with a comprehensive language-conditioned imitation policy for embodied robots in smart cities
Z Ju, H Wang, J Luo, F Sun - Computer Communications, 2024 - Elsevier
Abstract Integrating Embodied Robots into a smart city's networked system can significantly
enhance the city's operational efficiency. These robots can be connected to the city's …
enhance the city's operational efficiency. These robots can be connected to the city's …
What matters in language conditioned robotic imitation learning over unstructured data
A long-standing goal in robotics is to build robots that can perform a wide range of daily
tasks from perceptions obtained with their onboard sensors and specified only via natural …
tasks from perceptions obtained with their onboard sensors and specified only via natural …
Calvin: A benchmark for language-conditioned policy learning for long-horizon robot manipulation tasks
General-purpose robots coexisting with humans in their environment must learn to relate
human language to their perceptions and actions to be useful in a range of daily tasks …
human language to their perceptions and actions to be useful in a range of daily tasks …
Language-conditioned imitation learning with base skill priors under unstructured data
The growing interest in language-conditioned robot manipulation aims to develop robots
capable of understanding and executing complex tasks, with the objective of enabling robots …
capable of understanding and executing complex tasks, with the objective of enabling robots …
Reshaping robot trajectories using natural language commands: A study of multi-modal data alignment using transformers
Natural language is the most intuitive medium for us to interact with other people when
expressing commands and instructions. However, using language is seldom an easy task …
expressing commands and instructions. However, using language is seldom an easy task …
Imitation learning of robot policies by combining language, vision and demonstration
In this work we propose a novel end-to-end imitation learning approach which combines
natural language, vision, and motion information to produce an abstract representation of a …
natural language, vision, and motion information to produce an abstract representation of a …
Uncertainty-Aware Deployment of Pre-trained Language-Conditioned Imitation Learning Policies
Large-scale robotic policies trained on data from diverse tasks and robotic platforms hold
great promise for enabling general-purpose robots; however, reliable generalization to new …
great promise for enabling general-purpose robots; however, reliable generalization to new …
Embodied Executable Policy Learning with Language-based Scene Summarization
Large Language models (LLMs) have shown remarkable success in assisting robot learning
tasks, ie, complex household planning. However, the performance of pretrained LLMs …
tasks, ie, complex household planning. However, the performance of pretrained LLMs …
LHManip: A Dataset for Long-Horizon Language-Grounded Manipulation Tasks in Cluttered Tabletop Environments
Instructing a robot to complete an everyday task within our homes has been a long-standing
challenge for robotics. While recent progress in language-conditioned imitation learning and …
challenge for robotics. While recent progress in language-conditioned imitation learning and …
Interpretable Robotic Manipulation from Language
B Zheng, J Zhou, F Chen - arXiv preprint arXiv:2405.17047, 2024 - arxiv.org
Humans naturally employ linguistic instructions to convey knowledge, a process that proves
significantly more complex for machines, especially within the context of multitask robotic …
significantly more complex for machines, especially within the context of multitask robotic …