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检索条件"机构=The Robot Learning Lab"
849 条 记 录,以下是1-10 订阅
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Hierarchical Diffusion Policy for Kinematics-Aware Multi-Task robotic Manipulation
Hierarchical Diffusion Policy for Kinematics-Aware Multi-Tas...
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IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
作者: Ma, Xiao Patidar, Sumit Haughton, Iain James, Stephen Dyson Robot Learning Lab London England
This paper introduces Hierarchical Diffusion Policy (HDP), a hierarchical agent for multi-task robotic manipulation. HDP factorises a manipulation policy into a hierarchical structure: a high-level task-planning agent... 详细信息
来源: 评论
learning to Search in Task and Motion Planning With Streams
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IEEE robotICS AND AUTOMATION LETTERS 2023年 第4期8卷 1983-1990页
作者: Khodeir, Mohamed Agro, Ben Shkurti, Florian Univ Toronto Robot Vis & Learning Lab Robot Inst Toronto ON M5S Canada
Task and motion planning problems in robotics combine symbolic planning over discrete task variables with motion optimization over continuous state and action variables. Recent works such as PDDLStream [Garrett et al.... 详细信息
来源: 评论
Dream2Real: Zero-Shot 3D Object Rearrangement with Vision-Language Models
Dream2Real: Zero-Shot 3D Object Rearrangement with Vision-La...
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IEEE International Conference on robotics and Automation (ICRA)
作者: Kapelyukh, Ivan Ren, Yifei Alzugaray, Ignacio Johns, Edward Imperial Coll London Robot Learning Lab London England Dyson Robot Lab London England
We introduce Dream2Real, a robotics framework which integrates vision-language models (VLMs) trained on 2D data into a 3D object rearrangement pipeline. This is achieved by the robot autonomously constructing a 3D rep... 详细信息
来源: 评论
On the Effectiveness of Retrieval, Alignment, and Replay in Manipulation
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IEEE robotICS AND AUTOMATION LETTERS 2024年 第3期9卷 2032-2039页
作者: Di Palo, Norman Johns, Edward Imperial Coll London Robot Learning Lab London SW7 2BX England
Imitation learning with visual observations is notoriously inefficient when addressed with end-to-end behavioural cloning methods. In this letter, we explore an alternative paradigm which decomposes reasoning into thr... 详细信息
来源: 评论
Language Models as Zero-Shot Trajectory Generators
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IEEE robotICS AND AUTOMATION LETTERS 2024年 第7期9卷 6728-6735页
作者: Kwon, Teyun Di Palo, Norman Johns, Edward Imperial Coll London Robot Learning Lab London SW7 2AZ England
Large Language Models (LLMs) have recently shown promise as high-level planners for robots when given access to a selection of low-level skills. However, it is often assumed that LLMs do not possess sufficient knowled... 详细信息
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Adapting Skills to Novel Grasps: A Self-Supervised Approach
Adapting Skills to Novel Grasps: A Self-Supervised Approach
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2024 International Conference on Intelligent robots and Systems
作者: Papagiannis, Georgios Dreczkowski, Kamil Vosylius, Vitalis Johns, Edward Imperial Coll London Robot Learning Lab London England
In this paper, we study the problem of adapting manipulation trajectories involving grasped objects (e.g. tools) defined for a single grasp pose to novel grasp poses. A common approach to address this is to define a n... 详细信息
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Bathymetric Reconstruction From Sidescan Sonar With Deep Neural Networks
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IEEE JOURNAL OF OCEANIC ENGINEERING 2023年 第2期48卷 372-383页
作者: Xie, Yiping Bore, Nils Folkesson, John Royal Inst Technol Robot Percept & Learning Lab SE-10044 Stockholm Sweden
In this article, we propose a novel data-driven approach for high-resolution bathymetric reconstruction from sidescan. Sidescan sonar intensities as a function of range do contain some information about the slope of t... 详细信息
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Neural Network Normal Estimation and Bathymetry Reconstruction From Sidescan Sonar
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IEEE JOURNAL OF OCEANIC ENGINEERING 2023年 第1期48卷 218-232页
作者: Xie, Yiping Bore, Nils Folkesson, John Royal Inst Technol Robot Percept & Learning Lab SE-10044 Stockholm Sweden
Sidescan sonar intensity encodes information about changes in the surface normal of the seabed. However, other factors such as seabed geometry as well as its material composition also affect the return intensity. One ... 详细信息
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DINOBot: robot Manipulation via Retrieval and Alignment with Vision Foundation Models
DINOBot: Robot Manipulation via Retrieval and Alignment with...
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IEEE International Conference on robotics and Automation (ICRA)
作者: Di Palo, Norman Johns, Edward Imperial Coll London Robot Learning Lab London England
We propose DINOBot, a novel imitation learning framework for robot manipulation, which leverages the image-level and pixel-level capabilities of features extracted from Vision Transformers trained with DINO. When inte... 详细信息
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BiGym: A Demo-Driven Mobile Bi-Manual Manipulation Benchmark  8
BiGym: A Demo-Driven Mobile Bi-Manual Manipulation Benchmark
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8th Conference on robot learning, CoRL 2024
作者: Chernyadev, Nikita Backshall, Nicholas Ma, Xiao Lu, Yunfan Seo, Younggyo James, Stephen Dyson Robot Learning Lab United Kingdom
We introduce BiGym, a new benchmark and learning environment for mobile bi-manual demo-driven robotic manipulation. BiGym features 40 diverse tasks set in home environments, ranging from simple target reaching to comp... 详细信息
来源: 评论