Search Results for author:
Found 4 papers, 2 papers with code
Tools for Data-driven Modeling of Within-Hand Manipulation with Underactuated Adaptive Hands
Precise in-hand manipulation is an important skill for a robot to perform tasks in human environments.
Model-based Reinforcement Learning
Reinforcement Learning (RL)
Robust, Occlusion-aware Pose Estimation for Objects Grasped by Adaptive Hands
The hand's point cloud is pruned and robust global registration is performed to generate object pose hypotheses, which are clustered.
6D Pose Estimation using RGB
6D Pose Estimation using RGBD
+4
Fast Model Identification via Physics Engines for Data-Efficient Policy Search
This paper presents a method for identifying mechanical parameters of robots or objects, such as their mass and friction coefficients.
Information-theoretic Model Identification and Policy Search using Physics Engines with Application to Robotic Manipulation
We consider the problem of a robot learning the mechanical properties of objects through physical interaction with the object, and introduce a practical, data-efficient approach for identifying the motion models of these objects.
