4 citations · 4 across the 3 of their papers we have counts for
5 papers
Robotic Object Insertion with a Soft Wrist through Sim-to-Real Privileged Training
Yuni Fuchioka, Cristian C. Beltran-Hernandez, Hai Nguyen +1
This study addresses contact-rich object insertion tasks under unstructured environments using a robot with a soft wrist, enabling safe contact interactions. For the unstructured e…
Accelerating Robot Learning of Contact-Rich Manipulations: A Curriculum Learning Study
Cristian C. Beltran-Hernandez, Damien Petit, Ixchel G. Ramirez-Alpizar +1
The Reinforcement Learning (RL) paradigm has been an essential tool for automating robotic tasks. Despite the advances in RL, it is still not widely adopted in the industry due to…
Robotic Imitation of Human Assembly Skills Using Hybrid Trajectory and Force Learning
Yan Wang, Cristian C. Beltran-Hernandez, Weiwei Wan +1
Robotic assembly tasks involve complex and low-clearance insertion trajectories with varying contact forces at different stages. While the nominal motion trajectory can be easily o…
Variable Compliance Control for Robotic Peg-in-Hole Assembly: A Deep Reinforcement Learning Approach
Cristian C. Beltran-Hernandez, Damien Petit, Ixchel G. Ramirez-Alpizar +1
Industrial robot manipulators are playing a more significant role in modern manufacturing industries. Though peg-in-hole assembly is a common industrial task which has been extensi…
Learning Force Control for Contact-rich Manipulation Tasks with Rigid Position-controlled Robots
Cristian Camilo Beltran-Hernandez, Damien Petit, Ixchel G. Ramirez-Alpizar +4
Reinforcement Learning (RL) methods have been proven successful in solving manipulation tasks autonomously. However, RL is still not widely adopted on real robotic systems because…