262 citations · 503 across the 32 of their papers we have counts for
6 papers · 1 filter
Hierarchical Planning for Long-Horizon Manipulation with Geometric and Symbolic Scene Graphs
Yifeng Zhu, Jonathan Tremblay, Stan Birchfield +1
We present a visually grounded hierarchical planning algorithm for long-horizon manipulation tasks. Our algorithm offers a joint framework of neuro-symbolic task planning and low-l…
Fast Uncertainty Quantification for Deep Object Pose Estimation
Guanya Shi, Yifeng Zhu, Jonathan Tremblay +4
Deep learning-based object pose estimators are often unreliable and overconfident especially when the input image is outside the training domain, for instance, with sim2real transf…
Joint Space Control via Deep Reinforcement Learning
Visak Kumar, David Hoeller, Balakumar Sundaralingam +2
The dominant way to control a robot manipulator uses hand-crafted differential equations leveraging some form of inverse kinematics / dynamics. We propose a simple, versatile joint…
Indirect Object-to-Robot Pose Estimation from an External Monocular RGB Camera
Jonathan Tremblay, Stephen Tyree, Terry Mosier +1
We present a robotic grasping system that uses a single external monocular RGB camera as input. The object-to-robot pose is computed indirectly by combining the output of two neura…
Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning
Michelle A. Lee, Carlos Florensa, Jonathan Tremblay +4
Traditional robotic approaches rely on an accurate model of the environment, a detailed description of how to perform the task, and a robust perception system to keep track of the…
PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data
Zheng Tang, Milind Naphade, Stan Birchfield +5
In comparison with person re-identification (ReID), which has been widely studied in the research community, vehicle ReID has received less attention. Vehicle ReID is challenging d…