Cikkek nyilvánosan hozzáférhető megbízással - Mustafa MukadamTovábbi információ
Valahol hozzáférhető: 19
Habitat 2.0: Training home assistants to rearrange their habitat
A Szot, A Clegg, E Undersander, E Wijmans, Y Zhao, J Turner, N Maestre, ...
Neural Information Processing Systems (NeurIPS), 2021
Megbízások: US National Science Foundation, US Department of Defense, Natural Sciences …
Continuous-time Gaussian process motion planning via probabilistic inference
M Mukadam, J Dong, X Yan, F Dellaert, B Boots
International Journal of Robotics Research (IJRR), 2018
Megbízások: US National Science Foundation, US Department of Agriculture
Where2act: From pixels to actions for articulated 3d objects
K Mo, L Guibas, M Mukadam, A Gupta, S Tulsiani
International Conference on Computer Vision (ICCV), 2021
Megbízások: US National Science Foundation, US Department of Defense
Gaussian Process Motion Planning
M Mukadam, X Yan, B Boots
International Conference on Robotics and Automation (ICRA), 2016
Megbízások: US National Science Foundation
Motion Planning as Probabilistic Inference using Gaussian Processes and Factor Graphs
J Dong, M Mukadam, F Dellaert, B Boots
Robotics: Science and Systems (RSS), 2016
Megbízások: US National Science Foundation, US Department of Agriculture
Towards robust skill generalization: Unifying learning from demonstration and motion planning
MA Rana, M Mukadam, SR Ahmadzadeh, S Chernova, B Boots
Conference on Robot Learning (CoRL), 2017
Megbízások: US National Science Foundation, US Department of Defense
Neural Dynamic Policies for End-to-End Sensorimotor Learning
S Bahl, M Mukadam, A Gupta, D Pathak
Neural Information Processing Systems (NeurIPS), 2020
Megbízások: US Department of Defense
TASKOGRAPHY: Evaluating robot task planning over large 3D scene graphs
C Agia, KM Jatavallabhula, M Khodeir, O Miksik, V Vineet, M Mukadam, ...
Conference on Robot Learning (CoRL), 2021
Megbízások: Natural Sciences and Engineering Research Council of Canada
Neural Grasp Distance Fields for Robot Manipulation
T Weng, D Held, F Meier, M Mukadam
International Conference on Robotics and Automation (ICRA), 2023
Megbízások: US National Science Foundation, US Department of Defense
Joint Inference of Kinematic and Force Trajectories with Visuo-Tactile Sensing
A Lambert, M Mukadam, B Sundaralingam, N Ratliff, B Boots, D Fox
International Conference on Robotics and Automation (ICRA), 2019
Megbízások: US National Science Foundation
STEAP: simultaneous trajectory estimation and planning
M Mukadam, J Dong, F Dellaert, B Boots
Autonomous Robots (AuRo), 2018
Megbízások: US National Science Foundation, US Department of Agriculture
Motion planning with graph-based trajectories and Gaussian process inference
E Huang, M Mukadam, Z Liu, B Boots
International Conference on Robotics and Automation (ICRA), 2017
Megbízások: US National Science Foundation, US Department of Defense
Learning Reactive Motion Policies in Multiple Task Spaces from Human Demonstrations
MA Rana, A Li, H Ravichandar, M Mukadam, S Chernova, D Fox, B Boots, ...
Conference on Robot Learning (CoRL), 2019
Megbízások: US National Science Foundation
Sparse Gaussian Processes on Matrix Lie Groups: A Unified Framework for Optimizing Continuous-Time Trajectories
J Dong, M Mukadam, B Boots, F Dellaert
International Conference on Robotics and Automation (ICRA), 2018
Megbízások: US National Science Foundation, US Department of Agriculture
Simultaneous Trajectory Estimation and Planning via Probabilistic Inference
M Mukadam, J Dong, F Dellaert, B Boots
Robotics: Science and Systems (RSS), 2017
Megbízások: US National Science Foundation, US Department of Agriculture
Revitalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation
T Fan, KV Alwala, D Xiang, W Xu, T Murphey, M Mukadam
International Conference on Computer Vision (ICCV), 2021
Megbízások: US National Science Foundation
Riemannian Motion Policy Fusion through Learnable Lyapunov Function Reshaping
M Mukadam, CA Cheng, D Fox, B Boots, N Ratliff
Conference on Robot Learning (CoRL), 2019
Megbízások: US National Science Foundation
Approximately optimal continuous-time motion planning and control via probabilistic inference
M Mukadam, CA Cheng, X Yan, B Boots
International Conference on Robotics and Automation (ICRA), 2017
Megbízások: US National Science Foundation
Learning Generalizable Robot Skills from Demonstrations in Cluttered Environments
MA Rana, M Mukadam, SR Ahmadzadeh, S Chernova, B Boots
International Conference on Intelligent Robots and Systems (IROS), 2018
Megbízások: US National Science Foundation, US Department of Defense
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